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Framework for Interpretation of Construction Concept Representations

Permanent Link: http://ufdc.ufl.edu/UFE0021272/00001

Material Information

Title: Framework for Interpretation of Construction Concept Representations
Physical Description: 1 online resource (242 p.)
Language: english
Creator: Mutis-Sin, Ivan A
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2007

Subjects

Subjects / Keywords: clusters, cognitive, concepts, construction, contexts, exchange, information, integrate, interoperability, interoperation, interpretation, misinterpretation, models, ontology, project, representations, semantics, semiotics, share, signs, situation, standards, transfer
Design, Construction, and Planning -- Dissertations, Academic -- UF
Genre: Design, Construction, and Planning thesis, Ph.D.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: Construction actors have the ability to operate regularly and concurrently on ongoing activities with other actors, or to interoperate, during the project life cycle. They socially interoperate according to particular situations and project needs, once they have identified their needs for interacting with others by manipulating or computing the information. The elements or products of the interoperations have the quality of information. Actors interoperate through the exchanging, sharing, transferring, or integrating of information. However, actors on construction projects experience interoperability problems that increase the use of resources, raise projects costs, and intensify the complexity of the project. As a consequence of these interoperability problems, the construction industry has concentrated its efforts on finding new methods for exchanging, sharing, transferring, and integrating information. These efforts advocate that interoperability is possible through the use of logical models to share common domain concepts in a conceptual model. Logical models have an advantage based on the efficiency in accessing the model. These efforts fail to derive a common model due to the significant fragmentation of the domain, the multiple views of the participant's, and the combinatorial explosion that is achieved when one attempts to define the relationships among construction concepts. Our research develops a systematic approach that aids construction participants in identifying the potential inconsistencies of the information within the interoperation. This strategy facilitates the construction project actors in the acknowledgement of their misconceptions concerning the observed information. The strategy establishes a framework for reducing errors produced from the assertions or conclusions about the observed pieces of information. This framework addresses the need of a mediation mechanism in interoperability. The framework brings the necessary elements to interpret the information supplied from other participants in a project. The mediation mechanism reacts as a source of verification of the construction concepts employed in the interoperability activities. Our strategy focuses on a semantic interoperability step, which is the understanding of the information representations generated from different parties. The research scrutinizes the interpretation of the representations performed by an actor as a cognitive agent, by searching for the understanding of the fundamental elements involved within the actions of interpretation. The purpose is to bring into existence a strategy that aids the actors in reducing the time, the resources, and the errors generated during their interpretation operations.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Ivan A Mutis-Sin.
Thesis: Thesis (Ph.D.)--University of Florida, 2007.
Local: Adviser: Issa, R. Raymond.
Local: Co-adviser: Flood, Ian.
Electronic Access: RESTRICTED TO UF STUDENTS, STAFF, FACULTY, AND ON-CAMPUS USE UNTIL 2009-08-31

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2007
System ID: UFE0021272:00001

Permanent Link: http://ufdc.ufl.edu/UFE0021272/00001

Material Information

Title: Framework for Interpretation of Construction Concept Representations
Physical Description: 1 online resource (242 p.)
Language: english
Creator: Mutis-Sin, Ivan A
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2007

Subjects

Subjects / Keywords: clusters, cognitive, concepts, construction, contexts, exchange, information, integrate, interoperability, interoperation, interpretation, misinterpretation, models, ontology, project, representations, semantics, semiotics, share, signs, situation, standards, transfer
Design, Construction, and Planning -- Dissertations, Academic -- UF
Genre: Design, Construction, and Planning thesis, Ph.D.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: Construction actors have the ability to operate regularly and concurrently on ongoing activities with other actors, or to interoperate, during the project life cycle. They socially interoperate according to particular situations and project needs, once they have identified their needs for interacting with others by manipulating or computing the information. The elements or products of the interoperations have the quality of information. Actors interoperate through the exchanging, sharing, transferring, or integrating of information. However, actors on construction projects experience interoperability problems that increase the use of resources, raise projects costs, and intensify the complexity of the project. As a consequence of these interoperability problems, the construction industry has concentrated its efforts on finding new methods for exchanging, sharing, transferring, and integrating information. These efforts advocate that interoperability is possible through the use of logical models to share common domain concepts in a conceptual model. Logical models have an advantage based on the efficiency in accessing the model. These efforts fail to derive a common model due to the significant fragmentation of the domain, the multiple views of the participant's, and the combinatorial explosion that is achieved when one attempts to define the relationships among construction concepts. Our research develops a systematic approach that aids construction participants in identifying the potential inconsistencies of the information within the interoperation. This strategy facilitates the construction project actors in the acknowledgement of their misconceptions concerning the observed information. The strategy establishes a framework for reducing errors produced from the assertions or conclusions about the observed pieces of information. This framework addresses the need of a mediation mechanism in interoperability. The framework brings the necessary elements to interpret the information supplied from other participants in a project. The mediation mechanism reacts as a source of verification of the construction concepts employed in the interoperability activities. Our strategy focuses on a semantic interoperability step, which is the understanding of the information representations generated from different parties. The research scrutinizes the interpretation of the representations performed by an actor as a cognitive agent, by searching for the understanding of the fundamental elements involved within the actions of interpretation. The purpose is to bring into existence a strategy that aids the actors in reducing the time, the resources, and the errors generated during their interpretation operations.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Ivan A Mutis-Sin.
Thesis: Thesis (Ph.D.)--University of Florida, 2007.
Local: Adviser: Issa, R. Raymond.
Local: Co-adviser: Flood, Ian.
Electronic Access: RESTRICTED TO UF STUDENTS, STAFF, FACULTY, AND ON-CAMPUS USE UNTIL 2009-08-31

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2007
System ID: UFE0021272:00001


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1 FRAMEWORK FOR INTERPRETATION OF CONSTRUCTION CONCEPT REPRESENTATIONS By IVAN A MUTIS-SIN A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGR EE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2007

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2 2007 Ivan A. Mutis -Sin

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3 To my family, Roberto, Lucia, Aura, Adriana, and Hernan Mutis

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4 ACKNOWLEDGMENTS I am especially grateful to Dr. Raymond Issa, my mentor, advisor and teacher. His encouragement, guidance, and generous support gave me the opportunity to understand my research work as a science. Our resulting discussions and suggestions forged me to inquire other areas of knowledge for challenging the ideas of my research paradigm. I am very grateful to Dr. Ian Flood, and Dr. Randy Chow for their continuous support and suggestions during the developing of this dissertation. I also thank Dr. Larry C. Muszynski for his insights and help. It is an honor for me to have all of them in my committee.

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5 TABLE OF CONTENTS page ACKNOWLEDGMENTS ...............................................................................................................4 LIST OF FIGURES .........................................................................................................................9 ABSTRACT ...................................................................................................................................12 CHAPTER 1 INTRODUCTION ..................................................................................................................14 Interoperability in a Construction Project ...............................................................................14 Limitations of Current Information Representations in Supporting Interoperability .............16 The Interpretation Step ...........................................................................................................19 Practical Problems in the Interoperability Process .................................................................24 Interoperability ................................................................................................................24 Semantic Interoperability ................................................................................................26 A Semantic Syntax Matching Example ...........................................................................29 Summary .................................................................................................................................32 2 RESEARCH INQUIRY..........................................................................................................34 From the Problem to the Research Initiatives .........................................................................34 Fundamental Inquiry Assumptions .........................................................................................37 Objects and Research Questions .............................................................................................38 3 APPROACHES FOR INTEROPERABILITY IN CONSTRUCTION .................................41 Introduction .............................................................................................................................41 Approaches for Information Systems .....................................................................................42 A Priori Consensus ..........................................................................................................45 A Posteriori Integration ...................................................................................................46 Mapping Strategy ............................................................................................................49 Approaches in the Construction Domain ................................................................................51 Use and Composition of Information ..............................................................................51 Modeling the information for interoperability .........................................................53 The role of the documentation component ...............................................................57 Other Efforts at Ontological Engineering in Construction ..............................................59 Shortcomings of the Current Modeling Efforts ......................................................................62 The Reconciliation: A Case Example of the Semantic Interoperability Paradigm ...............65 Complexity for Reasoning ......................................................................................................72 Summary .................................................................................................................................74

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6 4 CONCEPTS IN THE CONSTRUCTION DOMAIN: DEFINITIONS AND PARADIGMS .........................................................................................................................75 Forms of Representations in the Construction Domain ..........................................................75 Capturing the Richness of the Domain ...................................................................................77 Grounding the Representations and the Domain ....................................................................77 Imperfect Representations ......................................................................................................79 Characterization of the Concepts ............................................................................................82 Implications of Employing Concepts for Interoperability ......................................................84 Situations and Contexts ..........................................................................................................85 Situations .........................................................................................................................86 The Translation of Situations into Representations .........................................................88 Stability of Situations ......................................................................................................89 Stable Situations and Evolution of Concepts ..................................................................92 Contexts ..................................................................................................................................95 Characterization of Situations and Contexts .........................................................................101 Top Ontological Distinctions ................................................................................................102 5 A DISJUNCTIVE OF THE MODEL PARADIGM ............................................................105 and Embodied Concepts .........................................106 The Limitation of the Modeling Paradigm ...........................................................................109 Correspondence .............................................................................................................110 Embodied Concepts .......................................................................................................113 Semantic Holism ...................................................................................................................114 Granularity ............................................................................................................................117 Conceptualization .................................................................................................................122 Summary ...............................................................................................................................126 6 NATURAL MODUS OPERANDI OF CONCEPTS ...........................................................128 Sensory Experience and its Role on Concept Interpretation ................................................129 Representations and Interpretations ......................................................................................131 Observational and Non-Observational Factors for Interpretations .......................................131 Interpretation as a Cognitive Process ...................................................................................132 Reasoning on Interpretations ................................................................................................134 Concept Generation: A Translation ......................................................................................137 Social, Context Character of the Concepts ...........................................................................139 Concept Communication ......................................................................................................141 Discussion .............................................................................................................................143 7 A SEMIOTIC PROPOSTION ..............................................................................................145 Semiotic Analysis .................................................................................................................145 Qualisign ........................................................................................................................147 Sinsign ...........................................................................................................................148 Legisign .........................................................................................................................149

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7 Icon ................................................................................................................................150 Index ..............................................................................................................................151 Symbol ...........................................................................................................................154 Rheme ............................................................................................................................156 Dicent Sign ....................................................................................................................157 Argument .......................................................................................................................158 Summary ...............................................................................................................................158 8 CONCEPTUAL ROLE SEMANTICS FOR INTERPRETATION .....................................162 Conceptual Role Semantics and the External World ............................................................162 Representation Forms and Significance of Conceptual Role Semantics ..............................165 Deficiencies of Forms of Representation .............................................................................166 Examples with Some Forms of Representations ...........................................................168 Visual and Syntactic Forms Example ............................................................................168 Formal Form Example ...................................................................................................170 Summary ...............................................................................................................................174 9 A FRAMEWORK FOR ANALYSIS of CONSTRUCTION CONCEPT ...........................175 Analysis of Construction Concepts and a Methodology for Aiding Their Interpretations ...175 Knowledge Acquisition ........................................................................................................177 Conceptualizations ........................................................................................................181 Conceptual Analysis ......................................................................................................182 Knowledge Organization ......................................................................................................191 Querying ...............................................................................................................................200 Summary ...............................................................................................................................206 10 RESEARCH VALIDATION................................................................................................207 Case Study as a Strategy for Validation ...............................................................................207 Validation Mechanisms ........................................................................................................208 Evaluation of the Validation .................................................................................................209 ..209 Context ..........................................................................................................................210 The Sharing Information Case for Interoperability .......................................................211 Semantic Interoperability Step ......................................................................................213 .........215 Identification of the concept from the representations ...........................................216 How do these representations describe a concept and how do the actors identify the concept in the documents? ..............................................................216 How is a concept identified by the estimator? .......................................................222 Are the representations within the construction documents accurate to perform interpretations? ...................................................................................................226 11 CONCLUSIONS AND CONTRIBUTIONS .......................................................................228 LIST OF REFERENCES .............................................................................................................235

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8 BIOGRAPHICAL SKETCH .......................................................................................................242

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9 LIST OF FIGURES Figure page 1-1 Interpretation process. ............................................................................................................23 1-2 Interoperability and information analysis to find correspondences. .......................................28 1-3 Request for information from other construction participants. ..............................................29 1-4 One-to-one matching. .............................................................................................................32 2-1 Research roadmap...................................................................................................................35 3-1 Mapping complexity: Different syntax, same semantics. .......................................................47 3-2 Mapping problem cases in relational data representations. ....................................................48 3-3 Components of the information in the architecture, engineering, and construction domain................................................................................................................................52 3-4 Process model. Four generic information process activities and their interactions (Bjrk 1999). .................................................................................................................................55 3-5 Industry foundation classes (IFC). Architecture diagram with kernel model components. ...56 3-6 Comparison of ontology engineering approaches with concept clusters. ..............................62 3-7 Structure of an ad-hoc construction business. ........................................................................67 3-8 Ad hoc construction ontologies. .............................................................................................70 3-9 Concept structures from different sources. ................................ ................................ ............. 73 3-10 Complexity of reasoning for the reconciliation of two concept structures. ..........................74 4-1 Representations, agents, and domain relationships. ...............................................................79 4-2 Visual representations of situational conditions ........83 4-3 Image of a situation. ...............................................................................................................89 4..................................................93 4-5 Constraints that indicate a situation of the concept squared, shaped windows. .....................94 4-6 Evolution of concept representation which keep initial semantics. ........................................95 4-7 Context relations. ....................................................................................................................98

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10 4-8 Focus on a context relation for complementing the granularity level to interpret a ...................................................................................101 4-9 Conceptualization on a domain. ...........................................................................................103 5-1 Qualitative relationship between quantity of explicitly given information and accuracy of its interpretation. ..........................................................................................................121 5-2 Conceptualization on a domain. ...........................................................................................123 5-3 Context relations and details for conceptualization. .............................................................125 6..............................................130 6-2 Mapping representations (layers) that describe the same concept. ......................................133 6-3 Relations between visual and text-based symbol representations. .......................................134 6-4 The meaning triangle. ...........................................................................................................135 6-5 Proposed reasoning process for interpretations ....................................................................137 6-6 Generation and interpretation of the translated concept. ......................................................139 7-1 Visual ................................ ................................ .......................... 147 7-2 Sinsign. .................................................................................................................................148 7-3 Legisign. ...............................................................................................................................150 7-4 Icons......................................................................................................................................151 7-5 Index. ....................................................................................................................................154 7on a computer screen. ...........................................................................................156 7-7 Meta-level representation. ....................................................................................................160 8-1 Visual and syntactic forms of representation. ......................................................................167 8-2 Reasoning forms of representation. ......................................................................................170 8-3 Example of formal forms of representations. .......................................................................173 9-1 Intervening actors and subsequent components of the conceptual framework. ...................176 9-2 Scheme for concept analysis and the associated top ontological categories. .......................180 9-3 Top ontologi ............................182

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11 9-.............................185 9.......................................187 9........................................188 9.............................190 9-8 Concept Cluster structure. ....................................................................................................195 9-9 Scheme for concept analysis and the associated top ontological categories. .......................196 9.........................................................199 9-11 Query workflow. .................................................................................................................202 9-12 Graphical user interface of a query. ....................................................................................204 9-13 A graphical user interface that queries the topology clusters. ............................................205 10-1 Continuous sharing information among construction actors. .............................................214 10-2 A metaphor represented within the construction documents. .............................................217 10-.......................................................................................218 10-4 Computer Aid...............219 10-....................................220 10-6 Text-..221 10-fixed-aluminum windows ............................................................223 10--representation. ..................................................................................................................226

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12 Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy FRAMEWORK FOR INTERPRETATION OF CONSTRUCTION CONCEPT REPRESENTATIONS By Ivan A. Mutis-Sin August 2007 Chair: Raymond Issa Cochair: Ian Flood Ma jor: Design, C onstruction and Planning Construction actors have the ability to operate regularly and concurrently on ongoing activities with other actors, or to interoperate, during the project life cycle. They socially interoperate according to particular situations and project needs, once they have identified their needs for interacting with others by manipulating or computing the information. The elements or products of the interoperations have the quality of information Actors interoperate through the exchanging, sharing, transferring, or integrating of information. However, actors on construction projects experience interoperability problems that increase the use of resources, raise projects costs, and intensify the complexity of the project. As a consequence of these interoperability problems, the construction industry has concentrated its efforts on finding new methods for exchanging, sharing, transferring, and integrating information. These efforts advocate that interoperability is possible through the use o f logical models to share common domain concepts in a conceptual model. Logical models have an advantage based on the efficiency in accessing the model. These efforts fail to derive a common model due to the significant fragmentation of the domain, the multiple views of the

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13 relationships among construction concepts. Our research develops a systematic approach that aids construction participants in identifying the potential inconsistencies of the information within the interoperation. This strategy facilitates the construction project actors in the acknowledgement of their misconceptions concerning the observed information. The strategy establishes a framework for reducing errors produced from the assertions or conclusions about the observed pieces of information. This framework addresses the need of a mediation mechanism in interoperability. The framework brings the necessary elements to interpret the information supplied from other participants in a project. The mediation mechanism reacts as a source of verification of the construction concepts employed in the interoperability activities. Our strategy focuses on a semantic interoperability step, which is the understanding of the information representations generated from different parties. The research scrutinizes the interpretation of the representations performed by an actor as a cognitive agent, by searching for the understanding of the fundamental elements involved within the actions of interpretation. The purpose is to bring into existence a strategy that aids the actors in reducing the time, the resources, and the errors generated during their interpretation operations.

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14 CHAPTER 1 INTRODUCTION Interoperability in a Construction Project Many specialized and professional teams concurrently perform tasks in capital intensive and complex construction projects. These dynamic relationships demand more cost-effective interactions in the manipulation of the information used in projects and it has pushed actors to find strategies for the faster manipulation of the information they share with others and at lower costs. The manipulation of information with others takes place through the actions of exchanging, sharing, transferring, or integrating of information. The information they manipulate is a set of information packed in forms of representation. The process of exchanging, sharing, transferring, and integrating of information from multiple sources is called interoperability. In the construction industry, project actors also have the ability to interact with other actors, or to interoperate. They regularly and concurrently intervene within activities, or interoperate, during the project life cycle. This interoperation takes place at any time on demand during any construction activity. Construction participants have long attempted the development and deployment of information technologies as mechanism to deliver productivity and efficiency to interoperate throughout the life cycle of their projects. Actors interoperate through any role played in a construction project. These roles are not only dynamically played within the organization but also dynamically played with external agents. However, within the process of exchanging, sharing, transferring, or integrating information, project actors experience significant problems that increase the use of resources, raise the costs, and intensify the complexity of a project. Roughly, the practical problems are lack of coordination, inconsistencies, errors, delays, or misunderstandings. As a consequence,

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15 efforts in the construction industry have been focused on finding efficiency as well as economy for exchanging, sharing, transferring, and integrating information. The efforts have been exerted in finding new techniques or methods for these operations. The purpose is the reduction of time, resources, and errors within the interoperability activities with the objective of overcoming the lack of effectiveness as well as their costs. An assumption of the construction industry is that the adoption of strategies that employ existing technologies will significantly reduce interoperability problems. The adopted strategies are various and include (1) designing standards, models, and conceptual models in a consensus approach --e.g. Industry Foundation Classes IFC and aecXML (IAI 2005)--for exchanging, sharing, and transferring, (2) designing mappings for integrating information from different sources (Amor 1997; Amor 2004) (3) and semi-automatically mapping disparate sources (Katranuschkov 2001). However, multiple problems have pervaded the efforts within the strategies adopted by the community. They range from the impossibility of reaching consensus on evolving standards, the differences on systems, to the methods of representing information (Partridge 2002). In addition, another significant problem is the existing differences in the representations of information generated by dissimilar, independent sources in spite of their use of the same conceptual model for generating the representations. These differences, for example, are evident in the levels of detail among representations that were generated from different actors. As our research recognizes the multiple problems that pervade the community efforts, it also identifies failures in addressing the inherent paradigm that hinders interoperability. The paradigm that needs to be addressed is semantics within interoperability or semantic

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16 interoperability, which is based on the understanding of what is represented within the transferring, and integrating the meanings of information are the goals of semantic interoperability. This research explores this paradigm and proposes new insights for the construction domain. Limitations of Current Information Representations in Supporting Interoperability The information supplied by external project sources such as regulations or legal standards or by internal project sources such as budgets, contracts, and schedules is conveyed in dissimilar documents. These documents are sets of information packed in a different form of representation. The focus of interoperability is to address the information about construction projects that is generated by different sources. The forms of representation of the information consist of construction documents. Construction participants convey the information concerning their activities though the life cycle of the project. The content of these documents are characterized by employing either human readable, paper-based forms or by employing human readable, computerized forms. A common misconception concerning the documents represented in computerized forms is that they can be exchanged, shared, transferred, or integrated without any human intervention or manipulation in the process. The description of information through representations in computational systems does not guarantee continuous, workflow scenarios among construction s, computers mediate for representing a concept. Computers serve as mediation mechanisms by transforming and computing a representation of construction concepts from computer readable forms to human readable form. Information is taken as representation of the concepts of a domain in the

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17 semantic interoperability arena. A concept is an abstract universal notion, of an entity of a domain that serves to designate a category of entities, events or relations The fact that concepts are represented through the employment of computational systems does not indicate that the information could automatically systems, or in other words, automatically be exchanged, shared, transferred or integrated within other project participants. The representations of construction concepts are transformed and such as exchanging or integrating of information requires a priori, complex, agreements among the context related to their intentions and purposes. In the simplest interoperability case, by employing human, readable, computerized re limited to storage, reproduction, sharing, distribution or exchanging with the objective of being This investigation recognizes that the role of actors within the interoperability activities cannot fully be eliminated by performing computations on the forms of representations. The technologies that the actors employ serve to assist them in computing and transforming machine to human readable forms in these interoperability activities. In computations can be performed for completing an interoperability activity. However, the technological assistance n the manipulation of the representations. The benefits of employing the technologies for computations are the facilitation of elaboration of the

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18 manipulation for storage, reproduction, sharing, distribution or exchanging. The Case of Integrating Information for Interoperability Construction projects are common, physical environments where actors socially interact for integrating their information, according to particular situations and based on particular information, they process the information by manipulating or computing it in their own system, or, in other words, by integrating the information. The requested information from other actors is lations of the representations of information cannot fully be replaced by computation. For example, one purposes of optimization of time or of resources. They need to interpret and re-elaborate the schedules. The actor that performs the integration needs to interpret the schedule that can be expressed in a form of representation such as tables, structured database schemas, or electronic files. The representation of the schedule is displayed in human readable forms through the computer systems in order to be manipulated. The integration of information as an interoperability activity is known as the processing of integration is a process where one or more documents or forms of representation from other actors are requested in order to be employed tables that follow structured conceptual models, documents assembled in markup languages (e.g.

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19 XML), and through documents in natural language built in CSI standards (e.g. Masterformat), among others. It is important to note that the construction research community has recently exerted major efforts in attempting to solve the information integration problem. Their efforts are targeted at supporting many modes of communication and collaboration on all projects with the purpose of aiding processes involved with computerized systems, or Information Technology (IT) (Amor 2000). The objective is to work on methodologies on achieving automation in processing one Since fully automatic interoperability with the representation is not feasible, human manipulations on any form of representation are part of the process. There is an explicit relationship between the actor and the representation that is further analyzed in this study. As was mentioned concerning the manipulation of representations within the schedule example, one of the actions is the interpretation of what is represented in the paper-based or computer-readable forms by one or more actors during the interoperability activity. Although interpretations are mostly cognitive operations, there are fundamental aspects addressed in this research for advancing the understanding of the semantic interoperability paradigm. The following section of this chapter presents a further explanation of this point. The Interpretation Step understandinginterpretation step of the meanings of the manipulated information. What has been named as information is taken as representation of the concepts of a domain in the semantic interoperability arena. The interpretation step moves our analysis to inquiries concerning how a construction participant sees the real world or how he/she maps the views of the world into representations that reflect these views. For this purpose, this research takes into account aspects

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20 concerning the nature of knowledge representation per se, the method for characterizing domain concepts into representations, and the act or step of interpreting concepts from other representations generated by other domain agents, among others. An Analogy of the Interpretation Step For clarity on the interpretation step, a parallel in the process can be illustrated within a speech act theory (Searle 1969). The speech act characterizes what the speaker communicates to the listener by relying on the mutually shared background of the information or contexts and the intention of the utterance. In the simplest case, two actors, a speaker and a listener, participate in a speech act. Thus, when there is an utterance within a communicative act, an understanding of the facts and relevance of the conversation, a setting up of the background information pertinent to the conversation, and assumptions and inferences are needed to capture the intended meaning within the expressed utterance. In the case of the interpretation step as part of an interoperability activity, what is shared among the actors is not an utterance but a representation of concepts. Some actors are the ones that generate the information and others are the interpreters. In the speech act, there is the listener and the speaker. Actors are participants in a construction project, and the project is the environment where the motivated interactions of the actors take place. The actors who share the representations with other peers within the project have a predefined role. The concepts are translated into different forms of representation in order to semantically communicate them and suggest some actions to the interpreter. These actions are the result of the inferences and assumptions made by the interpreter. It is not a requirement for the actors to share the same space or synchronically and deliberately be arranged for performing the interpretation within the interoperability activity, as they are within speech acts. The interpreters identify the intention

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21 based on the representation generated by the sources and assert their meanings. The result of these assertions is the interpradditional requisitions of information from the sources will be needed. Within the speech act, the listener asserts and commits him or herself to an action or rejects the utterance when its intention was not captured. In the interpretation step within the context of a construction project, additional aspects can be taken into consideration for a full commitment to the actions that follow the interpretation. Figure 1-1 is an illustration of this step. When a need emerges for information from other project participants during a construction activity, there is a course of action for requesting the information from these sources. As shown in Figure 1-1 the actors request information through previously defined and identified channels of information flow. The channel defines the method for requesting and providing information which can be specified contractually between contractors and subcontractors. The form of representation of the requested information can also previously be defined between the interpreter and the source. Alternatively, the interpreter relies on the forms, syntax, and vocabulary of the sources for representing concepts as a viable, readable form for performing the interpretation. Once the actor or interpreter has received the information from the sources, an identification activity of the concepts that has been represented is performed. The identification consists of an analysis of the observed representation in order to perform reasoning hat motivates the requisition of information. In other words, the interpreter focuses on the representation sections which motivated the request for information and that are useful for his or

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22 her activity. The interpreter can also further articulate the sections or parts of the representation to complete the interpretation. The reasoning for identifying meanings consists of finding knowledge. As illustrated in Figure 1-1 if the semantic associations cannot be found by the interpreter the concepts are not satisfactory for the observer. The interpreter or observer searches for additional sources of information in order to find associations for identifying the concepts in the knowledge bases, or even by experts. If the supplied information for finding semantic associations is not sufficient to help the interpreter identify the concept, the interpreter has to request additional information from the sources in order to have a better level of sufficiency for performing the interpretation. This flow of information is shown in Figure 1-1 interpreter performs an action as a result of the interpretation. The conditions are satisfied when the intentionality with the observed representations is accomplished or, in other words, when an action can be committed by satisfying the purpose of interpreting the representation. This action is generally recorded in the actors systems, or it is a part of a more complex, subsequent reasoning process by the interpreter, which can be manipulated and calculated.

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23 This research claims that it is not possible to develop fully automatic and integrated technologies for the construction industry in general to provide productivity and efficiency. Human intervention is necessary in some component of the interoperability case. In consequence, strategies that enhance productivity and efficiency for the human intervention component of the interoperability process need to be derived. This research explores and understanding Figure 1-1. Interpretation process.

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24 Practical Problems in the Interoperability Process As mentioned earlier, the frequent problems encountered in interoperability are lack of coordination, inconsistencies, errors, delays, or misinformation. The exchanging, sharing, transferring, or integrating of information among construction participants is burdensome with their high costs and need for human intervention. The consequence is a reduction in the productivity and efficiency of current interoperability activity. When actors find these problems in a construction project, they are forced to either partially solve coordination errors, or to totally rework the construction documents. This additional step produces project delays and requires the use of additional resources, as well as producing disruptions in the construction workflow. In consequence, rework due to inconsistencies, misinformation, or other problems that cause a lack of interoperation can result in project delays. The delays can be propagated throughout the whole set of activities that result in the escalation of the complexity and cost of the whole project. The following are motivating examples that illustrates the dynamic of the problem of interoperability within the construction domain. Interoperability Suppose a general contractor (GC) is responsible for completing a large project with tight scheduling constraints. The GC uses cost control to track the schedule progress of the work, to control material costs, and to monitor subcontractor costs. This activity anticipates the intervention of multiple participants, for instance: the GC, a Project Manager, and Subcontractors. Thus, the GC constantly needs to know whether the Project Manager (PM) has is enough time for subcontractors to complete Task B. Then the GC has to request some

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25 information from other construction participants. When the GC receives the information sent or transferred from other project parties, he or she interprets such information and then integrates it into his or her system. With the new information, the GC controls the costs, tracks the schedule progress of the work, controls material costs, monitors subcontractor costs, and is able to perform additional operations as well. For instance, the GC will be able to predict the anticipated costs and the scheduled completion dates, since the cash flow for a particular work package The GC performs an interoperability activity at a certain time of the project in response to examine tracking of costs, quantities, and resource performances, and that update his or her project schedules. This process is manually performed. The tracking and updating operation are interprets the required sections of construction documents that were supplied by these other actors. The GC intervenes in the interoperability process by requesting and integrating the information generated by the PM or Subcontractors. The PM and Subcontractors share their information with GC. There is a disruption in the workflow of the information when the GC intervenes for integrated. The use of human intervention results in project cost escalation and in the reduction of productivity and efficiency. For example, when the tracking and updating operation in the GC system takes place, a re-elaboration of the other actors information is performed, in order to information into the GC systems. Other, additional problems

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26 the GC needs. In this case, additional delays may occur in solving the inconsistencies of the other Semantic Interoperability Semantic interoperability stands for the understanding of what is represented within the information generated by other domain agents. In the previous example, the explained situation resources change as the construction project progresses. The change produces a modification in certain activity durations as well. Subsequently, the GC must manually update his or her schedule and other project control tools associated with the change. The GC and the Subcontractors are performing interoperability by requesting and sharing information contained in the documents. Figure 1-2 illustrates a flow of the construction documentation of project actors within an interoperability activity. Sharing information, for example, indicates that the documentation is distributed to the actors involved in the interoperation. The GC needs to fully understand the meaning of description of the resources. It is assumed that the Subcontractor sends the information in readable representation to the GC. In the previous example, the resources are the ones that the subcontractor intends to share and the ones that the GC searches the subcontractors describe their resources in the construction documents. The understanding of the description implies the comprehension of the meaning of the description of the resources. For compressor, air, dry pipe systemunderstanding of this resource implies that its description within the su

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27 documentation, say Z. Then the GC finds associations to a concept, say Y, which corresponds to the resources that the GC works within his or her system or documents. If the GC is capable of performing these associations, then the GC understands what the subcontractors described as resources in their construction documents. The GC manually finds these associations. As a further illustration, the reasoning process looking for the selected resources that should have represented in these documents. The search is a matching operation of what the GC understands about the selected resource that needs to be The matches are found through similarities of syntax of description of the source. If a match is not found, the search process is repeated. In this case, an analysis of the context of the documents can also be included. This analysis consists of observing additional -to-case basis. If during the search of the matches the GC finds inconsistencies, errors or lack of syntax details for defining the required resources, the GC is forced to request additional sources of information either from other sources or from the agent who generated the documentation. For example, when the GC needs clarification about the definition of a resource used in the contractor by fax or telephone. One aspect to take into account with the example is that the distribution and the representation of the information elaborated with computer do not imply that the interoperation is executed automatically. This interoperation consists of request and sharing the documentation

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28 updates and, if inconsistencies or lack of details are found, finding other information sources or contacting the Subcontractors is required. In summary, the GC needs to manually formalize semantic associations between their good time management and cost-effective activities. The GC should be able to reuse these In construction projects, any significant change of resources, times, or activities should be propagated through multiple construction participants. This type of operation requires coordination efforts among the parties involved. It is easy to observe from this scenario that any sharing, exchanging, distribution, and integration of data among parties should be done in a collaborative fashion and in an efficient way. Figure 1-2. Interoperability and information analysis to find correspondences.

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29 A Semantic Syntax Matching Example The following example involves an actor or a construction participant who is faced with the task of manually resolving a discrepancy between two sources of information. As the reader can notice, this example involves three actors: two subcontractors and the PM. The example illustrates a higher complexity in an information sharing case. The situation of the case is a cost estimation process for a construction project which is performed by a project manager (PM). In this activity, the PM requested two estimates from two subcontractors; Subcontractor A and Subcontractor B (see Figure 1-2 and Figure 1-3). The request for information from other sources is a sharing of information operation. As an example, the objective of the PM can be stated as the selection of the most inexpensive Subcontractor based on the cost of the installed linear feet (L.F.) of PVC. Figure 1-4 shows the Subcontractors documents. The purpose of the PM items in each subco Figure 1-3. Request for information from other construction participants.

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30 Briefly, the reasoning process involved in this interoperability activity can be enumerated as: searching and selecting the item or concept to be estimated in the subcontractors documents, interpreting the concept described in the sources, finding the potential or similar descriptions of the concept by comparing their syntax, finding mappings by comparing syntax or by finding semantic associations between the description of the concepts through the context, evaluating the equivalence of the concepts for the intended cost estimated activity, and, if the evaluation is satisfactory, proceeding with the cost optimization activity. As the reader can notice in Figure 1-4, the PM should perform a manual comparison of the PVC items for these two sources. The activity starts by identifying the mechanical division Construction Estimating Institute (CSI) Division 15 in the piping section (CSI 2004). The PM identifies the sections within the documents of the sources represented by two tables in Figure 1-4. The reader must take into account the fact that the optimization encompasses tasks concerning comparisons of costs from the two sources. Tables A and B in the Figure 1-4 consist of a set of tuples (rows), where each tuple has one value that corresponds to each column in the relation. Thus, Table A has the tuple (15.41504, Pipe PVC, SCH 40, 1" & Fittings, 16.43, L.F., 7.76, 1.10, 8.88), which allocates the value from each estimate in order to perform a cost optimization activity. Once the PM has identified within the document, semantic associations are performed by mapping between these two sources.

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31 Therefore, for achieving a valid comparison in the cost optimization of L.F. of PVC, the PM searches for a set of semantic associations that satisfy consistent similarities between the two the semantic associations between these two data sources. This is less feasible to execute if the PM does not associate the actual values that each table. The PM finds additional semantic relations within the context of these sources such as the units to characterize the PVC in each table. The PM semantically maps instances or values ponds to semantic mapping process is needed. The reader, who already has some knowledge of the In addition, the PM can identify other correspondences of the PVC from the two sources. -and finds semantic associations that are not reliable, the PM must verify the descriptions of each

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32 item with the actor that generated the tables by contacting each source by phone or fax. Clearly, this mapping activity together with the interpretation step is a time consuming and inefficient activity especially when verification or clarification of the documents is needed. Interoperability could become an overwhelming activity if the PM needs to find semantic associations from more than two construction participants. Figure 1-4. One-to-one matching. Summary The common practice concerning the generation of information for construction projects is that the construction participants create their information independently rather than in a collaborative environment. There are no a priori agreements or coordination on the automation of the interoperability activities. These agreements are complex and expensive to achieve. Agreements for automation on interoperability activities should address characteristics of the

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33 understanding of the forms of representations, such as syntactical forms and domain vocabulary, the conceptual model, the intentional conditions, and additional properties of the employed construction concepts. Therefore, strategies of consensus such as a priori agreements or as standards over the content of what is described within the information will not guarantee an effective and productive interoperation. The construction industry seems to be focusing on finding other strategies for integration, for mapping or for consensus the information generated by other construction participants. This research claim that strategies for an understanding of what is going to be added, processed, or manipulated should primarily be addressed. In this research view, the strategies undertaken by the community will not provide solution for fully automatic and integrated information workflows. Since these strategies, including others for integration and for mapping, for achieving consensus are not feasible, actors in construction projects are forced to manipulate the information. As the fully automatic interoperability with the representation is not feasible, the manipulations on any form of representation are part of the interoperability process. The manipulations involve an interpretation step performed by the actor or construction participant, One or more components of the interoperability process demand human intervention. A strategy for improving the efficiency and productivity of the human intervention is needed. The research identifies the interpretation step of observed representations as the paradigm for defining a framework with the objective of achieving efficiency and productivity within interoperability. In this framework, this research addresses fundamental aspects of the interpretation step of what is represented in the paper-based or computer-readable forms that significantly advances the understanding of the semantic interoperability paradigm.

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34 CHAPTER 2 RESEARCH INQUIRY This chapter outlines the line of inquiry explored by this research. It also describes the spectrum of the undertaken paradigm within the construction domai n, the specific assumptions that bound the problem, the contributions and implications to the construction community, as well as the research questions that further define the context and the objectives of this investigation. For an illustration of our res earch inquiry, Figure 2 1 shows a roadmap of the main research steps as well as the proposed s trategies taken for solving our research questions. From the Problem to the Research Initiatives Construction project actors have the ability to operate regularly and concurrently on ongoing activities with other actors, or to interoperate, during the project life cycle. The elements or products of the interoperations have the quality of information. They interoperate through the exchanging, sharing, transferring, or integrating of information. However, within these activities, agents of the construction projects experience problems that increase the use of resources, raise the costs, and intensify the complexity of the project. From the two examples cited in Chapter 1, one notes that interoperability embraces multiple steps and requirements in order to be made possible. As a consequence, the research community has centered its efforts on finding new techniques or methods for exchanging, sharing, transferring, and integrating information. The trends of these approaches have been that construction concepts are represented by symbolic representations for their implementation on database systems or knowledge-base catalogues. This form of construction representation of the concept facilitates data storage and retrieval, and results in better system efficiency. However, the classification method used to categorize the representation fails to define the concept at an

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35 Figure 2-1. Research roadmap. Problem definition and research paradigm Description and exam ples of the practical problem of exchanging, sharing, and integrating information employed in construction projects Definition of the interpretation step of the information generated from other sources Chapter 1 Introduction Identification of the need for research concerning the understanding of information from other sources Research assumptions Definition of th e research questions and objectives of the investigation Chapter 2 Research Inq uiry E xisting strategies for interoperability in the information systems field and in the construction industry Shortcomings of the modeling and the standards efforts R econciliation of information as a paradigm of interoperability Chapter 3 Approaches for Interoperability Inquiry Analysis of the fundamental notions of information and the prima nature of the interpretation of information Characterization of concepts through ontological categories Evolution of concepts and their characterization into representations Context as a method to define relations to situations to semant ically enrich its definition Purpose, intention, and reasons to communicate concepts Chapter 4 Concepts in the Construction Domain Defintions and paradgimsIntroduction The embodied nature of construction concepts The r ejection of the definition of concept s through the observation to construct representations or models Proposition of granularity notion that relates the explicitly given information to its accuracy of interpretation Chapter 5 A Disjunctive of the Model Paradigm The representation as a translation of concepts fr om Metaphors as a source of semantics for reasoning The social character of the representations and its contextual social dynamics. Chapter 6 Natural Modus Operandi of Concepts Existing theories of semantics concerning interpre ta t ion of signs Analysis of the interpretation of a representation generated from other sou rces through signs Ontological analysis of the relationship between actor and sign Chapter 7 The Semiotics Proposition Study of communicating concepts through the Chapter 8 Conceptual Role Semantics Proposed strategy to aid construction concept representations Mediation approach strategy Concept clusters as a meta ontology to define categories on concepts for the construction domain Knowledge acquisition through an ontological analysis Chapter 9 Framework for Interpretations Propositi on Interpretation of a representation within construction documents through the proposed framework for interpretation Chapter 10 Illustrative Case Example

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36 accurate level of detail. This fact raises questions about consensus obsolesce or the usefulness of the method to represent the construction concept representations. Other efforts advocate the use of logical models to share common domain concepts in a conceptual model. The use of a logical model gives an efficiency advantage in accessing the model. However, these efforts fail to derive a common model due to the significant fragmentation of the domain, the combinatorial explosion that is achieved when one attempts to define the relations of concepts. Our research focuses on a semantic interoperability step, which is the understanding of the information representations generated from different parties. The research scrutinizes the interpretation of the representations performed by an actor as cognitive agent. This research also quests for the understanding of the fundamental elements involved within the actions of interpretation. The purpose is to bring into existence and to assemble a strategy that aids the actors in reducing time, resources, and errors within their interpretation operations. The quest for efficiency as well as for economy of these operations is the motivation of our present research efforts. The purposes of these efforts are the reduction of time, resources, and errors within the interoperability activities. There is a need to develop a systematic approach that aids construction participants in identifying the potential inconsistencies of the observed information. The systematic approach guides the actor to interpret the information in the construction documents. This need is a motivation to design a strategy that allows construction project actors to recognize that they are missing elements concerning the observed information contained in the construction documents. The strategy is an incentive for establishing a framework for reducing errors produced from the assertions or conclusions of the observed pieces of information. This strategy has to respond to

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37 the need for a mediation mechanism in interoperability that aggregates the necessary elements to interpret the information supplied from other construction participants in a project. The mediation mechanism has to react as a source of verification of the construction concepts employed in the interoperability activities. Fundamental Inquiry Assumptions It is clear that the interpretations are executed from previously elaborated representations by other construction participants. These representations are described in the construction documents as well as characterized by employing either human readable, paper-based forms or by employing human readable, computerized forms. The description of these representations in computational systems does not guarantee continuous, workflow scenarios among construction An important assumption to outline is that information is taken as representation of concepts of a domain. The domain is defined by the areas or disciplines involved within a construction project and whose agents participate in interoperability activities within the project life cycle. Outline of the Theoretical Propositions Our investigation searches for explanations of the limitations of current representations of information used for interoperability. The purpose is to illustrate the spectrum of the representation problem and to suggest an additional overlooked step. This step is based on a novel way to see the problem supported by semantic associations of a representation. The objective is to acquire an understanding of the role of semantics through representations, and to conduct an analysis to visualize the semantic representations for ambitious challenges like integration or collaboration

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38 This investigation aims at understanding the fundamentals of the problem for sharing, exchanging, or integrating of information. As was explained, the focus of the fundamentals of the problem is on the interpretation step of the observed representation. Information is a broader term used for naming representations, in either human or computable forms, of concepts. Our research proposes the understanding of the nature of these representations through the Pierce triadic relations of (1) quality material or existence of things, (2) reaction to the signs or the conception of being relative to the things which determine the way the sign is related to its object, and (3) representation of tthrough some formal rule that associates the observed sign to an object (Peirce 1991). Also, this investigation advocates the employment of construction concepts as a main form for semantic operations within sharing, exchanging, and integrating information. Therefore, our study suggests as a postulate that the employment of concepts defines the modus operandi through interoperability. Objects and Research Questions As was mentioned in chapter 1, the search for efficiency and for economy in interoperability with construction documents is the motive of this research. The need for actor intervention in interpreting the construction concepts as an essential piece for creating interoperability is recognized. The action of interpreting is a process that involves the relationship between thee construction project actors as cognitive agents and the explicit information represented within the construction documents. The objective is the exploration of this relationship as the onset of our research efforts. However for achieving efficiency and economy within the identified action of interpretation, a conceptual framework that provides a theoretical proposition for interpreting construction concepts has been constructed. It provides guidance for understanding the phenomenon immersed in the semantic interoperability activity.

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39 Therefore, strategies that search for efficiency and for economy can be designed from this framework. The conceptual framework is the result of the analysis of the fundamentals of information represented within construction documents and of the relationship between actors as cognitive agents and explicit symbols or representations. The purpose is to explore why and how this paradigm represents a challenge to the construction industry community. The objective is to find the conclusions and the discussions as a result of this research. From the resulting conclusions and discussions, the line of reasoning logically follows theoretical propositions that will be stated in our research. Therefore, the theoretical propositions grouped in the conceptual framework are the pillar of inquiries concerning the motivating aspects of the effectiveness and the economy this research. The conceptual framework provides a scheme for understanding the theoretical proposition within the studied paradigm. The framework furnishes new insights and a revolutionary contribution to the understating of interoperating with information used in construction projects. The objective is to facilitate to the reader the logic or the theoretical propositions for designing strategies or mechanism for interoperation with the purpose of acquiring the effectiveness and the economy of the interoperability actions. Experiments and behavioral studies can be easily designed for testing the assembled logic by addressing particular relationships from this conceptual framework. These studies can be done through controlling variables or through the direct, precise and systematic manipulation of cognitive agent behavior, such as the reduction on the interpretation time in an interoperation activity. The framework facilitates where to look for relevant evidence in a construction project situation as well as reflecting important theoretical issues.

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40 The reader should notice that searching for efficiency and for economy is the motivation but not the object of our research. Therefore, our research primarily addresses the understanding of the semantic interoperation action of interpretation which the cognitive agent and the representation of information are involved with. The objective is the construction of the conceptual framework for interpretation of the construction concepts. Therefore, the central idea of this research is to explore the fundamentals concerning why and how the interoperation with construction documents represents a paradigm and how the articulation of the resulting conclusions is possible through a conceptual framework. A set of case studies are presented as a validation strategy. The case studies are focused on the theoretical propositions exposed in the conceptual framework. The logic relationships of the framework are included within the context of construction project situations. The case studies give the reader the ability to associate the phenomenon of interpreting construction concepts in a semantic interoperation within the context of construction project activities. The reader, then, will be able to identify real life situations when they perceived the logic of the relationships exposed in the conceptual framework for interpreting construction concepts. The case study benefits the reader in understanding the theoretical proposition constructed within the conceptual framework. The research questions that capture what this research is interested in answering are the following: How can an actor effectively interpret what is represented within the information generated by other construction project actors with the purpose of sharing or integrating the representation during a construction project activity? Having identified and analyzed the relationship between an actor as construction participant and the construction concepts represented in human readable paper based or computer forms, how can an actor semantically interoperate with an observed representation of the concepts as described in the construction documents?

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41 CHAPTER 3 APPROACHES FOR INTEROPERABILITY IN CONSTRUCTION Introduction The effective exchange, sharing, transfer, and integration of information are studied within the semantic interoperability arena. Semantic interoperability can be defined as the understanding can be approached from two different angles or perspectives: information systems and problem domain. The former is addressed within the sphere of the computer science domain, and the latter is addressed by a particular domain where interoperability takes place (i.e. heavy construction, building construction). The approaches have different input to find semantics. surveys to find semantic definitions. Other mechanisms to find semantic definitions are the prescription of models that structure manageable pieces of work and that are aimed at agents that have the same view of the models (e.g. framework models that propose the breakdown of construction products). Solutions from the information systems attempt to find axiomatizations and models of information (Ziga 2001). These solutions use complex algorithms and other tools from fields such as artificial intelligence. These solutions from each perspective have been driven independently by specialists from the domain and from the scientific community. For example, a project participant is interested in how to make other participants understand the information furnished by each agent in any interoperability activity, while computer scientists and knowledge engineers are interested in how to model a domain. This chapter contains a review and an analysis of recent efforts in the construction and information systems domains. It will briefly explain current approaches and strategies from information systems and refer to them with illustrations of the construction domain problem. At

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42 the end of this chapter, this research focuses on the reconciliation problem within semantic interoperability. The reconciliation process deals with finding common semantics about sources of information from different agents. The purpose of focusing on this problem is to enhance the understanding for reconciling sources of information by addressing the reconciliation process for integrating, mapping or merging information. The resulting conclusions define aspects of the fundamentals of information and the knowledge representation paradigms for determining semantic associations between two sources generated by different agents. These aspects will be further explained in the next sections of this chapter. The finding of semantic associations is an action of interoperability with semantics, i.e. semantic interoperability. Approaches for Information Systems The term information systems is commonly used in the sphere of interoperability literature under several areas of specialization such as knowledge representation, databases, computational linguistics, knowledge sharing, and artificial intelligence among others. This research refers to information systems as a non-specific area of specialization. This section presents an analysis of the strategies used within the semantic interoperability paradigm. Two issues to remember from understandinginformation from different actors, and second, information that is used for interoperation is symbolized by representations such as visual and textual representations. As the reader may notice, the interoperability arena examines areas of specialization under information systems that cover different problems. For example, paradigms such as This research focuses on the representation of the information rather than on the technologies used to connect agents in interoperability.

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43 representations that the computer systems are able to manipulate and process. In other words, data representations are logical, coherent structures of information that are manipulated by computer applications and humans. These data representations could be structured or non-structured. They are structured when they reflect information based on logic or reflect a description of the logical relations between data elements in a way that computer languages or systems can process them, while non-structured information is a raw representation that does not have any kind of logic arrangement (e.g. an image). When the structured data representations are organized in a logical model that defines data contents and relation, they form a schema. This model defines a pattern of the represented s the entity relation method that describes procedures to model a schema in a database arena and which describes entities, data types, relations, user operations, and constraints (Elmasri and Navathe 2000; Garcia-Molina et al. 2002). When schemas are addressed to model a particular domain, they are called conceptual schemas. Conceptual schemas attempt to outline a particular domain in terms of modeling elements, by creating a general characterization of the environment of the domain. Therefore, from the information system standpoint, engineers or computer scientists endeavor to exchange, transfer, share, and integrate information within a domain by using schemas or conceptual schemas. However, this characterization of the domain by conceptual schemas is challenged with significant problems when an interoperability solution is implemented. These problems appear when a relation needs to be established between two conceptual model schemas elaborated by different agents. For an example refer to Figure 1-3

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44 which shows the efforts within an interoperability process to map two information systems schemas, represented by two tables from two different participants. In the information system standpoint, it is clear that the main problem to interoperate is to find relations between two conceptual schemas. The problem can be divided into four categories (Spaccapietra et al. 1992): Semantic Conflicts, which are the conflicts that appear when independent developed data representations do not represent the same abstraction of the concepts of the real world, or when the abstractions overlap; Descriptive Concepts, which occur when concepts defined in different data representations represent identical concepts of the real world but are described by different properties or attributes; Structural Conflicts, which appear when the same real world concept is defined by using different modeling concepts in different data representations (e.g. one type of attributes and value attributes); Heterogeneity Conflicts, which appear when the integration of two types of data representations is attempted (e.g. object oriented and STEP). The scientific community has no solution for the aforementioned conflicts. The conflicts are fundamental problem is built upon philosophical questions concerning the method to represent aimed at contributing with insights together with philosophy, psychology, knowledge representation, and computer science disciplines. From the information system standpoint, computer scientists have worked on developing strategies toward semantic interoperability. Although they might not be complete solutions, they are methods that aid in interoperability by integrating, mapping, and harmonizing conceptual

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45 schemas. These strategies can be grouped according to methodologies to harmonize, to integrate, or to map conceptual models (Katranuschkov 2001). The following analysis of current strategies is made in order to understand interoperability approaches. For a better illustration, examples that are found in the construction domain are presented in each strategy. Several of these aforementioned concepts of the construction domain in this strategy are fully detailed in the following section that describes the approaches for interoperability in the construction domain. A Priori Consensus This strategy embraces all the standards where the main models of conceptualization are first created and subsequent data models are developed by referring to that created conceptualization model. Actors or developers harmonize their models with the intention of integrating their data models with other actors in the interoperability activity. This strategy consists of finding common concepts of the universe of discourse of the domain. In the case of the construction industry domain, the definition of those concepts is focused not only on construction products but also on construction processes during a project life cycle. In other words, this strategy establishes a priori how conceptual models represent the information and how it is dictated syntactically and semantically in a logical perspective. A conceptual model indicates the framework of reference where the domain community has formulated their particular definition of concepts and, from this reference a data model. Interoperability participants, information system developers, computer application developers, and others, refer to that conceptual model in order to help structure any concept in the data model. Examples of conceptual models in the construction industry classification are Master Format Standard (CSI 2004) and the IFC models (CSI 2004; IAI 2005). Data models created under the conceptual models are expected to facilitate the

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46 the data representations that fit the data models will assure that the concepts of the domain are represented at least in the same way. The conceptual models work as higher layer models from which consistent specific data representation are derived. This consistency builds a framework that diminishes the disagreement over the meaning, interpretation, or intended use of the same concept. Examples of conceptual models in the construction industry are standards and catalogs (ISO 13584), CIS/2 (Crowley et al. 2000), and IFC (IAI 2005). However, the consistency of this strategy has significant limitations. The fragmentation of the domains makes it difficult to elaborate complete modules of reference and modules of interpretation. The construction industry not only is a fragmented domain but it is also dominated by concepts that overlap with other industries. A Posteriori Integration This strategy aims at obtaining integration consistency for previously elaborated data models. The integration is intended to contain one coherent data model. This strategy is particularly driven by the database arena. The strategy consists of finding relations between concepts from the data models or schemas. The criterion to find the relations is based on finding concepts within the schemas. The latter criterion consists of the identification of the organization compositions. After these analyses are made, this strategy addresses an examination of the schemas to generate an integrating model by resolving the conflicts of relating concepts from two different sources. In summary, this strategy detects differences, defines correspondences, and creates new schema or merges the existing ones. In databases, the technique used to determine correspondences between data representations is called a matching operation (Rahm and Bernstein 2001). These operations

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47 tackle integration from different sources applications, data warehouses, web-oriented data integrations, e-commerce, etc. Matching works on an operation called mapping. Matching is a schema manipulation operation that takes two schemas as input and creates a mapping that identifies corresponding elements in the two schemas (Madhavan et al. 2001). The strategy pursues consistency of the final integrated schema, involving more use of manual operations than semi-automatic or automatic operations. This strategy has significant limitations derived from its own nature. The strategy intends to find semantic correspondences based on relating concepts through similarities in the syntax and in the structure of the data representations. However, finding the accurate relations by using similarities is extremely complex. For example, finding the relations of concepts in the schemas by similarities when aggregated is not possible without the aid of an external agent. For a better illustration consider the examples illustrated in Figure 31 and Figure 3-2. Figure 3-1 shows that despite the identification of data representation in simple schemas, which in Figure 31 are the two tables, mapping or finding a relation among the correspondences is extremely cumbersome: schemas may possess structural and naming differences; they may have similar but not identical content; they may dissimilarly express data representation; they may use similar syntax but have different semantics, etc. Figure 3-1. Mapping complexity: Different syntax, same semantics. Name Co. Name Project Estimating Xz Airport 32600 Turner Hospital 14000 Name Company Project N. Budget Xz Airport 32600 Turner Hospital 14000 Table s chema 1 Table schema 2

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48 Most of the solutions through this strategy are targeted for Entity Relation type data representations where 1:1 mapping relations are more suitable to handle. However, when complex or aggregate relations exist, the mapping process is difficult to support. In Figure 3-2, (a) One-to-One Mapping (b) Complex Mapping Figure 3-2. Mapping problem cases in relational data representations.

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49 there is a comparative example of one to one and complex relation cases. As was mentioned previously, the mapping component of the a posteriori integration strategy is one of the most challenging and demanding processes. Mapping Strategy This strategy analyzes data representation sources and finds their relations through a set of formalized mappings. These mappings are derived from the knowledge domain or from conceptual models using mapping languages. Although mappings could be considered as part of the integration process of the a posteriori integration strategy, they are different because the mapping strategy employs conceptual models, which are derived from a priori consensus, to aid the mapping process. The Mapping strategy use concept models in order to find appropriate relations on conceptual levels. This strategy embraces the methods to finding mapping formalisms. It takes into account the type of data representations, the possible conflicts among them, and the correspondences of the mapped concepts. Furthermore, the mapping on more sophisticated types of data representation, such as ontology is a more ambitious process (Partridge 2002). For an illustration of this complexity in the construction domain, consider the following example. Take two ontology representations, named A and B. Each one of them has the concept: {spread footing}. Assume concepts A and B take the form of assemblies. Thus, concept A includes other elements such as {reinforcement, concrete, dowel bolts, bulk excavation} and concept B includes {reinforcement, concrete, dowel bolts, compacted backfill}. The relation between the concept and the elements are denoted as A as partof {reinforcement, concrete, dowel bolts, bulk excavation} and as B as partof {reinforcement, concrete, dowel bolts, compacted backfill}. The problem is determining how an actor can semantically map one node similar

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50 illustrate this problem in a simple way, observe that the nodes A and B partially match; they semantically match although they are not equal In fact, the nodes are similar and overlap into more specific elements of the concepts of the nodes. Then we say concept A{spread footing} and B{spread footing} are similar ; they overlap in the more specific elements {reinforcement, concrete, dowel bolts}, and they mismatch in the elements{bulk excavation} from A and {compacted backfill} from B. In order to execute a match at the element level between concept A{spread footing} and concept B{spread footing}, we map only concept A{spread footing} with only concept B{spread footing}. Note that A and B are mapped at the {spread footing} level, not on the A and B elements. However, element {concrete} from A, denoted as part of{concrete, A}, mapped with element {concrete} of B, denoted as part of{concrete, B}, can be matched at a simpler level. In this case, we have the mapping of these two elements at the element level. The element level performs mappings between individual concepts, and the structural level maps the semantics of two concepts, where each one holds other concepts (Giunchiglia and Shvaiko 2003b). In addition, we can have a structure level case such as whole concept A holds whole concept B. In this case, this matching is not fully matched because concept A semantically differs from concept B. Element A is a A{spread footing} and element B is a B{spread footing}, but on a more specific or simpler level {reinforcement, concrete, dowel bolts, bulk excavation} is part of A and {reinforcement, concrete, dowel bolts, compacted backfill} is part of B. They differ in the elements {bulk excavation} and {compacted backfill}. This result is called a partial match. The mapping strategy involves the roles of two components: the mapping language and mapping patterns. The mapping language is used to express the concepts of the data

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51 representation, such as entities and attributes, in a formal representation of the language in order to perform mappings between two sets of concepts of two data representations by means of language specifications. Examples of these languages are Express X (Hardwick and Denno 2000), Agent Communication Languages such a KQML (Knowledge Query and Manipulation Language proposed by DARPA), and VML View Mapping Language (Amor 1997), among others. Mapping types are the common mapping cases, which can take place between two elements, such as attribute-to-attribute, entity-attribute, etc. Approaches in the Construction Domain Most of the efforts to develop approaches for the interoperability problem in the constrend on modeling in the industry is based on construction processes or construction products. Products are manifestations of physical objects (i.e. windows) and processes are the transformation of these objects from one state to another (i.e. installing windows). In order to understand the modeling trend and to have a better picture of the use of information in the construction industry, an analysis of its composition is discussed in the next section. Use and Composition of Information The information used in the construction industry, which in the broad sense includes architecture, engineering, and construction, can approximately be broken down by specialization, by life cycle, and by the type of source where the information is generated. The analysis of the composition is presented in Figure 3-3. Other groups that are used in other fields of the domain could be added to the composition (i.e. facility managers). Figure 3-3 shows a top-down view that is an abstraction and a simplification of the information that it is used by a construction project. For exam

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52 that is used in the first stages of a project in estimating and planning tools and, in latter stages, is contractual documents (e.g. is the result of mapping an intended artifact and a representation. In the same way, a process is the map of an intended activity into a representation, and documentation is the description with high levels of details of products and activities in a construction project. The construction of a life cycle within a project. If the composition is broken down, the resulting parts are formalized into components that are mapped and modeled into computational representations. For example, a request for information (RFI) is an internal document from a construction organization, which contains a certain level of detail of information and conserves a level of abstraction of the group, and the structure of which is mapped and elaborated into computational representations. A door is a physical object that is modeled as a construction product and which it supposed to contain levels Figure 3-3. Components of the information in the architecture, engineering, and construction domain.

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53 participants who perform the interoperability tasks. Although, this way of addressing the information is a natural way to perform abstractions of construction projects and map them into computational representations, this level of generality uniqueness example, specifications are construction documents which conserve a structure organized by standards but the content is exclusively used for a particular project. Then, the levels of details of the specifications contrast with the goal of the standards to find generalities. This is an additional fact that will affect the effectiveness and adoption of solutions for interoperability. Modeling the information for interoperability Most of the efforts for interoperability in the construction domain have been made regarding modeling. These initiatives attempt to structure schemas that contain logic relations and concepts of the information found in the construction domain. These schemas are abstractions of possible instances that the construction participant finds in a particular area of the domain that is being modeled. The reader may notice that the definition of the schemas is similar to that of the conceptual models. Conceptual models indicate the framework of reference where the domain community formulates particular definitions of the concepts, while a schema is a map of concepts and their relations. In other words, conceptual models provide formal definitions of the basic concepts and their relations, but the schemas serve as templates to map the concepts and relations. In the same way, conceptual models have an affinity with conceptual schemas abstractions or understanding of that domain. The difference lies in the fact that the conceptual schema is not coupled with any modeling language.

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54 are built in data representations. The reader should be reminded that these data representations can be structured or non-structured. In the construction domain, the structured data or when representing products or processes respectively. In any case, these will fit a predefined conceptual model. For clarity, developers use formalizations that describe the modeling principles. An example of these formalizations is Integrated Definition Methods (IDEF), which is used for modeling processes. IDEF is a group of modeling methods that can be used to describe operations. IDEF was created by the United States Air Force and is now being further developed by Knowledge Based Systems, Inc. Originally developed for the manufacturing environment, IDEF methods have been adapted for wider use and for software development in general. These methods are used to create graphical representations of various systems, to analyze the model, create a model of a desired version of the system, and to aid in the transition from one to the other (KBSI 2004). The possible proliferation of conceptual models motivated developers to come up with conceptual models to be integrated into conceptual models. The common optic to manage these pieces of models was proposed through the use of a high layer model. High layer models are also labeled reference models. These models explicitly define a kernel type structure from which the concepts can be derived. For example, Bjrk (1999) proposed the reference model shown in Figure 3-4 for construction information processes and Industry Foundation Classes (IFC)

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55 defines constructs of processes and products through the use of the kernel model (IAI 2005) (see Figure 3-5). pes of specification documents: the first define concepts of different disciplines (e.g. HVAC, architecture), and the second serve as a guide where software engineers implement any computer application with structured data by mapping them into IFC data files, (see Figure 3-5). In this efficiently share and exchange information (Froese 2003). Figure 3-4. Process model. Four generic information process activities and their interactions (Bjrk 1999).

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56 Figure 3-5. Industry foundation classes (IFC). Architecture diagram with kernel model components. The efforts for establishing interoperability on models are more advanced on product modeling than process modeling (Eastman 1999; Froese 1996). An example of the product modeling initiative is RATAS, which is a building product model that breaks down products in a network decomposition scheme into five levels: building, system, sub-system, part, and details (Bjrk 1992). Other efforts on product modeling are aimed at sharing information by using protocols. The Building Construction Core Model (BCCM) provides a common framework for data exchange through a set of application protocols and facilitates the implementation of the

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57 coherent Application Reference Models (ARMs). The BCCM was identified as ISO-10303 Part 106 of a STEP activity. The BCCM model addresses products, as tangible items; processes, as the logistics and activities; resources, human, plant and constructed items; and controls, which are constraints applied to products, processes, and resources. There are also other initiatives that capture functional and behavioral information about building components. One example is the Semantic Model Extensions (SME) (Clayton et al. 1996), which interprets a design by assigning meaning to graphic forms. The role of the documentation component As was illustrated in the composition of information in Figure 3-3, documents and legal data are fundamental pieces of information that construction participants use to interoperate. Documents contain the necessary information at a certain level of abstraction for describing construction concepts. This description is packaged in various levels of details until a formal document is created and the rest of the description relies on the level of knowledge of the pthis product means to a construction participant. Therefore, documents in the construction industry, in order to describe a product or process during the building life cycle, have been expanded with further details within more specialized functional fields. The trend is that construction project operations have been broken down into more specialized areas according to the division of labor. The tendency of having more detailed creates an effective exchanging, sharing, and transferring of information and an understanding of the information concepts by construction participants.

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58 There is no significant advancement from the construction domain community for interoperability by using these components. The initiatives have relied on the software -rds (Zamanian and Pittman 1999) or on exchanging information syntaxes such as XML format. For example, aecXML provides XML schemas that describe information that is specific for data exchanges among participants involved in the design, construction, and operation of buildings, plants, infrastructures, and facilities. The aecXML schemas that are currently under development include: Structural, Infra-structural, FM, Procurement, Project Management, Plant, and Building Performance. Part of the documentation component traditionally has used classifications in taxonomical order to find ways to make partners understand the division of labor. The taxonomy is a method that helps construction participants conceptualize a construction project, and, therefore, perform interoperability activities. These classifications are simple conceptual models for representing the division of labor, which is a way of conceptualization that helps perform clear communication among all construction participants. Most of the classifications have been developed by practitioners and industry committees. For example, the Construction Specifications Institute, CSI, which is an association of architects, engineers, contractors, suppliers, owners, and facility managers, which boast of more than 16,000 members involved in commercial and institutional construction, has developed the MASTERFORMAT classification (CSI 2004). This joint effort consists of a list of numbers and titles classified by work results or construction practices, primarily used to organize project manuals and detailed cost information and to relate drawing notations to specifications. There are other efforts that have been made by other associations such as the new Overall Construction Classification System, OCCS, a

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59 classification system that organizes data in a common language from the conception to the whole life cycle of the construction project (OCCS 2006). Construction participants employ these classifications as higher layer models from which more consistent, specific data models are derived and used in custom construction applications i.e. ad hoc construction estimating databases based on CSI. The consistency maintained in the higher layer models or conceptual models diminishes the disagreement over the meaning, interpretation, or intended use of the same concept among construction participants. Other Efforts at Ontological Engineering in Construction In this section, a brief description of the main features of other ontological efforts is explained as well as an explanation of how the cited approaches differ from the current research. At the end of this section, a matrix is presented that aids the illustration for comparison purposes. The ontology model developed at Stanford (Bicharra et al. 2003; Staub-French et al. 2002) is an exercise of applying ontologies for case studies. Case studies are used to identify exercises do not attempt to create a formalization of the ontologies; they are simple exercises of construction processes. The conceptualization does not achieve the axiomatic level and is committed to the domain knowledge of the ontology developer. The work at Loughborough University related to ontological engineering is focused on intelligent computing (Aziz et al. 2004). Their work is oriented in creating technologies on mobile construction for collaboration. In the main architecture, they proposed an ontology layer that handles the relation between concept description and logic. They now have gone further and have advanced this work towards the semantic web architectures. They proposed an intelligent agent base system that is capable of controlling its own decision-making and action based on its

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60 perception of the environment. This effort proposes a series of methods for intelligent remote collaboration and one of the layers for conceptualization is an ontological one, which they call semantic tier. This tier enables knowledge description and knowledge access by supporting information retrieval, extraction and processing. The ontology is accessed to support inter-agent information transfer and it is used as a neutral source to access and exchange information. El Diraby (2006; 2005; 2003) has worked on the development environment for interoperability in the construction domain. He envisions an architecture that integrates engineering, economic, and social aspects. His efforts have started in infrastructure projects (El-Diraby 2003) and optimization of construction projects by using decision models. Perhaps his joint effort with the Lima et al. (2005) in developing e-COGNOS is the most important contribution. e-COGNOS is an ontology that conceptualizes knowledge management scenarios of construction projects. It was built to address the support of consistent and extendable representation of construction knowledge. The interesting part of this project is the methodology used to induct knowledge. It benchmarks other construction projects and validates the results with domain experts. The first step to build e-COGNOS ontologies is the recognition of IFC and British Standards BS6100 (BSI 1992) taxonomies as well as the Unified Classification for the Construction Industry UNICLASS (UNICLASS 1997) taxonomy in order to reflect mainly the IFC structure and International Organization for Standardization (ISO) 12006-3 (ISO 2007). In this sense, e-COGNOS recognizes and resembles taxonomies found in the IFC model such as Products, Processes, Actors, Projects, and Resources. El Diraby ( 2006) has continued his work in ontology engineering through the definition of the distributed architecture for knowledge management in highway construction. This work consists of the extension of the e-COGNOS ontology model to the taxonomies of domain

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61 concepts in highway construction. This new taxonomy is called HiOnto. The extension to this domain pertains to highway construction. It includes a full ontological description of the main entities of highway construction. In this ontology, a set of sub domain levels of abstraction was developed: domain, application, and users. Each level inherits the concept, relations, or axioms of the preceding level(s). This architecture resembles a set of taxonomies linked: e-COGNOS ontology, application ontology, and user ontology. In his latest work, El Diraby (2005) proposed a framework for a formalization through ontologies of the construction domain. The claim is that a micro-theory for construction can be formalized in order to capture the main entities in construction as well as their attributes and interrelationships. Again, this work is based on e-COGNOS and its extension to general construction concepts of the domain through formalizations. There are additional works in the industry based on ontologically engineering. Basically, they are attempts to find a neutral common model to share information for particular construction processes. These researchers employ an ontological approach as the back bone of their architectures to exchange and share information. For example, Kitamura et al. (2004) designed cases. Other efforts have been aimed at resolving conflict resolution in documents for collaborations by finding semantic consistency through syntactic patterns (Gu et al. 2005). This finding inter-domain interoperability such as the case of Geographical Information Systems and the construction industry. Peachavanish et al. (2006) explored a new methodology for CAD-GIS integration at the semantic level. Again, these works differ from concept cluster due to their goal of defining a common denominator between two different conceptualization models.

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62 The matrix in Figure 3-6 illustrates the aforementioned differences between the various mechanisms for knowledge organization. Our approach named concept cluster will be further explained in Chapter 9 In the matrix, e-Cognos is the work of Lima and El-Diraby and functional design knowledge is the work performed in Stanford (Bicharra et al. 2003; Staub-French et al. 2002). The others are the ontology engineering approaches (Gu et al. 2005; Kitamura et al. 2004; Peachavanish et al. 2006) as discussed previously. Figure 3-6. Comparison of ontology engineering approaches with concept clusters. Shortcomings of the Current Modeling Efforts The current modeling approach that is used in the construction industry is inadequate and plagued with several shortcomings. This section addresses these shortcomings of current

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63 modeling practices and presents a clearer illustration concerning the conditions that should be achieved for an effective approach, harmonized with current interoperability practices. In Chapter 4 an exploration on the fundamentals of the limitation of the modeling paradigms are discussed. The reader should take into account that the aforementioned models were defined to contribute to creating interoperability in the construction domain by functioning as high layer models from which more consistent, specific models are derived. In other words, the abstraction made by the models predicts the reality that a construction participant will find during the life cycle of a project by prescribing that situation. This is a good starting point to analyze the shortcomings of the current efforts. The first shortcoming of the current models is due to the fact that the models themselves created from a successive abstraction method. Models are not built through methods that analyze domain concepts according to their nature and then initiate a description of such concepts by limited consensus among some modelers. One consequence of this preconceived view is that users struggle when defining understandings of what a construction project is. The models reflect the real worldview of their developer, but not a reality that guarantees a common interpretation of the construction Other shortcomings encountered are due to the incompleteness of the models. The models are incomplete in their specifications and they lack comprehensive information (Amor 2000;

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64 Zamanian and Pittman 1999). This incompleteness makes it impossible to use them in practice in the industry. For example, the absence of any concept in the conceptual model would force a merging or a reconciliation of the concepts into others, diminishing the reliability of the real semantics. Other problems with the current modeling efforts are related to the heterogeneity of information and to the various levels of systematization or sophistication of the construction Considering the aforementioned shortcomings, interoperability initiatives should address: the sufficiency of the concept descriptions, which addresses the ability of the concept representation to provide construction participants the necessary information for performing interpretations; flexibility, which allows the concept representation to add additional semantics in order to define a concept; adaptability, which is the ability to recognize other particular types of representations of the domain; and efficiency, which is the capability to perform interoperation with economical factors. The sufficiency involves the specifications of the level of details of concept representations and the methods of generalization and abstraction for performing interpretations. The flexibility predefined concept descriptions. The adaptability recognizes the inclusion of other types of representations such as visual representations for practical purposes. The efficiency involves the s with minimum consumption of time and resources. The next section shows the complexity that would take place when the conceptual models are elaborated and a further step needs to be taken. This step corresponds to the semantic reconciliation of concepts of models from different sources. The complexity in further steps of

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65 semantic interoperability will be discussed in the next section in order to contrast it with the simplification adopted by the modeling strategy. The Reconciliation: A Case Example of the Semantic Interoperability Paradigm With the purpose of finding strategies within the reconciliation paradigm, part of our research is aimed at finding insights into the problem of reconciling representations of concepts within the construction domain. The reconciliation problem deals with finding common semantics about sources of information from different agents. The database community describes the reconciliation as one of the obstacles on the road toward solving the heterogeneity of information problem (Garcia-Molina et al. 2002). Reconciliation is a fundamental step of, sharing, and integrating information. To illustrate the complexity of the reconciliation problem an example will be shown in this section. This example employs ontologies, which are structures of knowledge representation that contains explicit information from the construction domain. The example is narrowed to the step of performing a mapping on the ontologies. As the examples show, further efforts should be spent on step, the reconciliation of two or more sources of information. Ad hoc ontologies of certain construction businesses are shown in Figure 3-7 and Figure 3-8, (a) and (b). The ontologies represent the construction business model. The reader is reminded that ontologies are often associated with taxonomic hierarchies of classes and the subsumption relations, but they are not limited to this structure, which could be easily confused with the rigid inheritance structures from object oriented representations. Ontologies acquire knowledge about the world and frame them into categories and add terminology and constrain them with axioms from traditional logic. An ontology is based on the formalization process of the knowledge of a domain. The knowledge contains domain concepts that are explicitly described in common vocabulary in order to be formalized. A domain expert

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66 extracts and translates the concepts into a common vocabulary and formalizes the resulting translation through a formal language, and axiomatic rules. This operation is called a conceptualization. The nodes in Figure 3-7 represent the Concepts in a graphical representation of an ontology. Figure 3-7 shows some specializations of the root, represented by Concept 1, such as {Functional Areas, Administration and Buildings}, which in turn are represented by Concepts 2, 3, and 4 respectively. The concept Project Manager, Concept 7, has instances like {Bill all UF} with fixed attributes like {Name, Hierarchy, is a set of relations among concepts like {is a, part of, has}. The relations are generally denoted as PartOf(Project Manager, Administration). These relations describe associated defined relations within classes, inheritance relations, and instances of properties. If the analysis is reduced to finding mappings that express semantic equivalence between the two ontologies, then the reconciliation problem can be expressed in terms of how an actor of another ontology. It is clear, then, that the mappings for this example are semantic associations between two or more concepts.

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67 Graphically, it is possible to bring up a clear picture of the complexity in finding a reconciliation of two ad hoc ontologies. Consider the two ontologies which are shown in Figure 3-8 (a) and (b). The nodes in the ontology represent concepts that have levels of specializations from their parent concept. In addition, the reader can identify relationships among concepts, for example, Isa(CPVC, Plastic Pipe Fittings) among the Concepts 11 and 9, as shown in Figure 3-8 (b). Figure 3-7. Structure of an ad-hoc construction business. corresponds to a semantic link between two concepts that have a subsumption that represents part of the concept y, or in other words, a component of x. The directional relation of containment (Brachman 1979; Woods 1975). How and when is reconciliation needed in the semantic interoperability process? With Figure 3-8 as an example, suppose that the construction participant queries information about the

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68 availability and costs of specific items from different material suppliers, say pipes for internal water distribution in a building. Specifically, the construction participant or actor need to perform a semantic association between the most similar concepts of the two ontologies that contain the information sought. The problem is in how a construction participant can semantically associate a concept or concepts of one data representation to another concept of the other data representation. Moreover, as can be intuitively noticed in Figure 3-8 (a) and (b), the question of how a construction participant will be able to semantically associate more complex matchings when one concept is semantically similar to a group of two or more concepts into another ontology needs to be addressed. In addition, the mappings shown in Figure 3-8 resemble one-to-one and complex matching problems that have been studied extensively within the database community (Doan 2002) For instance, consider a one-to-one semantic match at one of the levels. With the aid of auxiliary Figure 3-8 (a) (Steel Pipe, Black Weld, Screwed) is matched with Concept 8 from Figure 3-8 (b) (Metal, Pipes & Fittings). Note that although they semantically match, they fully syntactically miSteel Pipe, Black Weld, ScrewedMetal, Pipes & FittingsConcept 7 of Figure 3-8 (a) and Concept 8 of Figure 3-8 (b). Consider the case where the construction participant queries more detailed information other words, the participant needs to map specific instances from one source to another source or from one conceptual structure to another conceptual structure. For example, the user semantically maps Concept 4 (Plumbing Piping) in Figure 3-8 (a) to Concept 6 (Pipes and

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69 Tubes) in Figure 3-8 (b). But this mapping does not resolve the aforementioned query concerning the availability and costs of specific items from different material suppliers such as pipes for internal water distribution in buildings. The user should follow the subsumption relations of the concepts. This approach is similar to following down the hierarchy of a taxonomy. A taxonomy is a central component of an ontology (Noy and McGuinness 2001). Assume the exper1/2internal water distribution, e.g. PVC (Polyvinyl Chloride) pipe. Hence, the user matches Concepts 9 () from Figure 3-8 (a) to Concepts 10 (PVC) and Concept 13 (Diameter) from Figure 3-8 (b). Observe that Concept 10 is concatenated with Concept 13 to perform the match. Concept 10 is a more general concept than Concept 13 and vice versa, Concept 13 is more specific than Concept 10. This is a complex type of match that includes a joint of two concepts from one source to another concept of another source. Figure 3-8 (a) and (b), shows how the relationships between concepts of two representations could match at a more general or specific forms, or they could overlap or they could mismatch. These types of intuitively semantic relationships have what is called a level of similarity (Doan 2002; Giunchiglia and Shvaiko 2003a). Thus we can say that Concept 4 (Plumbing Piping) in Figure 3-8 (a) is similar to Concept 4 (Building Service Piping) in Figure 3-8 (b), at least intuitively due to specialization relation from Concept 2 (Mechanical) in Figure 3-8 (a) and Concept 2 (Mechanical) in Figure 3-8 (b), and due to similar syntax description of Concept 4 (Plumbing Piping) in Figure 3-8 (a) is similar to Concept 4 (Building Service Piping) in Figure 3-8 (b).

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70 (a) Ontology of a construction consulting firm. (b) Ontology of a construction business Figure 3-8. Ad hoc construction ontologies.

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71 In addition, it is important to note that the relationship between concepts such as Isa(HVAC, Mechanical) is also a possible map to other concepts of the ontology. These mappings between different types of elements make the process more complex. For further analysis, note that some concepts from Figure 3-8 (a) and (b), are similar and overlapped into more specific elements of the concepts. In these cases, in order to perform reconciliation an expert with sufficient level of knowledge about certain concepts in the domain would be needed for executing the reasoning process. For example, in an attempt to perform reconciliation among node 7 in Figure 3-8 (a) and node 8 in Figure 3-8 There is no possibility of asserting truth when actors observe explicitly represented information, such as the ontologies of Figure 3-8 (a) and (b), even in the scenario where an observer is able to perform plausible interpretations on the boundary of sufficiency. An agent that endeavors to interpret Concept 9 in Figure 3-8 (a), which is explicitly defined as PVC 1", can identify the concept as Polyvinyl chloride produced from the monomer, vinyl chloride (chemical formula CH2=CHCl). The actor, however, ignores the PVC level of flexibility that is described by the ontology's modeler in Concept 9 as PVC 1". Concepts cannot be taken for granted as derivations from properties of entities, of events, or of relationships inherited from the physical world. The meaning or semantics of a concept is established a priori and the complexities of a phenomenon cannot be accommodated in the limited resources of symbols and propositions. The modeler assumed an objective relation between the symbolic representation and a phenomenon. The modeler disregarded the level of phthalates (plasticizers) in the description of PVC 1", Concept 9, in their description of the flexibility of the PVC.

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72 For example, when an actor attempts to reconcile two or more explicitly represented structures of information, generated from different sources, the resulting complexity is a major paradigm. The actor can reconcile Concepts 9 (PVC 1") from Figure 3-8 (a) to Concepts 10 (PVC) and Concept 13 (1" Diameter) from Figure 3-8 (b). However, observe that Concept 10 is concatenated with Concept 13 to perform the match. Concept 10 is more general than Concept 13, and vice versa, Concept 13 is more specific than Concept 10. In summary, the examples of Figure 3-8 (a) and (b) illustrate the reconciliation problem of two ontology representations that are from the same domain, but have different terminologies. This semantic heterogeneity is a conflict that is categorized as an ambiguous reference (Ding et al. 2004), because the same term has a different meaning in different ontologies. In addition, the example shows how one concept of one ontology has similar but not exactly the same semantics as that of another ontology and how two concepts with a similar meaning can be structured differently in different ontologies. Complexity for Reasoning The previous examples showed the complexity of the reconciliation problem in attempting to relate two or more concepts from two different sources. The process of identifying similarities, in which an expert or actor intuitively finds semantic relationships according to the affinities, in which the expert intends to find the reasoning step. Experts read the concept structure and perform an abstraction of the structures to identify relationships in order to find semantics and assert interpretations. However, this reasoning is a complex problem that, in turn, makes difficult to reconcile concepts from two or more different sources. For clarity, consider the following example. Two concept structures from two different sources need to be reconciled by an expert. Figure 3 9 (a) and (b), shows these structures in which the nodes

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73 represent concepts and the links between the nodes represent an explicit relationship between the concepts. The structure shown in Figure 3 9 (a) has three nodes and three relationships and the structure shown in Figure 3 9 (b) has two nodes and one relationship. The two structures are dissimilar for the purpose of illustrating the nature of the reconciliation problem The components and forms of conceptual structures cannot possibly be found to be exactly similar when they come from different sources. (a) 3 Nodes (b) 2 Nodes Figure 3-9. Concept structures from di fferent sources. Figure 3-10 shows the association that the expert performs in order to reconcile the previous concept structures. The shadows on the structures illustrate what portion of the concept structures are selected to find semantic similarities and to fit concepts in the context of usage the most accurate associations among the multiple set of possible mappings. In addition, is important to take into account that the associations of the two conceptual structures presented in Figure 3-10 are not mapping patterns. The reasoning process for reconciliation does not find mapping patterns. It finds the closest meaning through mappings between two concepts from different concept structures.

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74 Figure 3-10. Complexity of reasoning for the reconciliation of two concept structures. Summary As shown by the example from Figure 3-10 human intervention by a domain expert is needed for reasoning with the objective of finding semantic associations. Deciphering and reasoning for associating each one of the structures is a complex task even for experts in the field. In addition, associating semantically two or more nodes from each structure to the other structure does not result in an accurate association even though they are syntactically, similarly expressed. There are other aspects to consider for identifying closer and similar, semantic associations between two structures. Next Chapter 4 will explore the fundamentals of the model paradigm in order to acquire other insights from other disciplines to bring and to discuss answers about the complexity of reconciliation.

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75 CHAPTER 4 CONCEPTS IN THE CONSTRUCTION DOMAIN: DEFINITIONS AND PARADIGMS Interoperability in the construction industry implies the interpretation of syntactically defined symbolic notations and of other forms such as visual representations. These notations are deliberate ly organized to define concepts. The understanding and characterization of concepts into symbols and other forms of representations are also addressed in this Chapter. Forms of Representations in the Construction Domain The agents of a community generate descriptions of hypothetical objects and states of affairs of their domain through forms of representations with the purpose of communicating them. These descriptions are abstract and are grounded in the possibility of their existence, although they can be imaginary. An architect, as an agent of the construction-project network, can generate the description of a clay tile roof though a set of symbols, which can be systematically expressed in natural language. The syntactic set of symbols can be interpreted as an utterance in natural language and those utterances are indeed systematically interpretable as to what they mean (Harnad 1994). This description is a characterization of the clay-tile roof objects. The characterization can be expressed through the advantages of being energy efficient, fireproof, and long lasting compared to asphalt or fiberglass shingles. The clay-tile roof description can also include the state of affairs within the space-time region, such as the suitability of use in hot and dry climates. of representation to be communicated to other actors in the domain. This concept is represented through a set of symbols in the preceding example. The archdescription of the abstract object is to make a reference to the possible identifiable physical

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76 describes their abstract creation of the clay-tile roof assembly. In the construction domain, the represented concept through symbols, models, or visual representations is intended to be related to the physical domain, i.e. be physically realized. The construction participant reifies and finds relationships between the interpreted concept and the physical domain. The agents in that world perform this association and transform physical objects through actions. Some of these actions are prescribed within the representations. For example, a construction schedule is a document and a representation that contains axiomatic rules, and it is employed for planning activities on a construction project. These activities are actions that are going to be taken in the space-time domain. The space domain corresponds to the physical domain of the construction project and the time domain, to the planned order in which the actions (tasks) are executed by the project participants. The construction schedule is a representation that is interpreted by the actors, and it can also be symbolic composition of the representations. The operations of some activities performed on the operations are based on a systematic symbol manipulation following a set of rules. The part of the semantic operations although they are interpretable, but they are manipulations of a systematic set of symbols. The semantic operations representation in order to perform actions in the construction domain. These links, which can be either from the representations to the domain or to other components of other forms of

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77 the domain, actions, or relations to other representations are semantic operations. Capturing the Richness of the Domain The creation of forms of representations, when actors capture aspects from the domain, is intended to reflect perceived features that were assessed as relevant. This judgment sacrifices other features from the infinite richness of the domain for gaining efficiency over the complexity for the operations of these forms of representations. As was mentioned previously, these operations are from the semantics or the computation domain. The richness is limited to the to be represented. The same judgment occurs when the representations are generated in the the world shared by the community. A model, which is a form of representation, conceives the world within this limited description. The judgment of the modeler is the mechanism to explicitly build the representations based on assumptions and commitments. The sacrifice made through these judgments is an essential factor for understanding the failures of the operations of the representations in the construction domain. The agents that manipulate the representations ignore the assumptions and the commitments made by the creator of the representations. This misconception is the cause of misinterpretations and of non-acknowledgment of the captured features which have been explicitly described in the representation. Grounding the Representations and the Domain The role of the construction participants as agents is to link poor representations through representations and the agents actions in the domain are the connection of the concept which is embedded in a representation, to the

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78 physical domain. The actions can also be performed by other agents without interpretation of representations. These agents, however, follow another prescribed set of actions from the models and they do not perform interpretations. The prescribed set of actions of an elevator, an agent in a construction project, is to vertically transport materials a certain distance, at a given speed, over performance of the mechanical movements. A model corresponds to the non-guarantee of operating under any circumstance in the project. The model may prescribe the basic actions for transporting materials. However it may not prescribe the necessary speed for transporting hazardous material. For a better understanding of the relationship among agents, representations, and the domain, consider Figure 4-1 The two activities in a PERT model are representations of a prescribed series of steps, with certain constrains such as early start, early finish, late start, late finish and their corresponding relationships with subsequent activities, which an agent has to follow. Clearly, this form of representation models the execution process of two activities, which represent a specific concept, for example the timing of vertical movements for transporting materials. The agents, a computer and a construction project actor, perform actions that are prescribed by the model in the domain. The computer agent performs the action by computing the model that consists of manipulating symbolic notations. Then, by some mechanism, such as computing the operation of the crane, the model acts upon or interacts with physical elements in the domain. The construction actor, who is an agent as well, performs interpretations on the represented model in order to execute the indicated process with physical components in the domain.

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79 Figure 4-1. Representations, agents, and domain relationships. When a relationship is set up among a model and an agent or an agent and a domain, an interoperability act takes place. This research recogn izes that the automation by computation of the representation is costly and difficult to implement due to the numerous set of operations that constitute construction activities. Hence, it focuses on the relationships between the construction actor and the representation and the construction actor and the domain. The goal is to suggest methods for interpreting representations effectively by developing better methods to represent concepts. A motivating analysis concerning the nature of the representations an d these relationships is presented in the following sections of this chapter. Imperfect Representations The representations in the construction industry do not fully pick out aspects of features that intervene in an activity on a project. The representations are not complete. The industry has developed other forms for finding the description of the concepts. The partiality or incompleteness of representations in delimiting situations in the construction domain is balanced

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80 with other forms of formal descriptions or conceptualizations, i.e the specifications. The objective is to help the construction project actor perform more accurate interpretations by enriching the description of the represented concept. The specifications are formal descriptions of a concept expressed in natural language. They express a desired behavior of the concept in particular. If the concept has already been represented in a form such as in a model, the model will describe the series of steps of what is modeled. The specifications ractions, which follow this form of representation, will be complemented with additional information through formal description of the concept by employing the specifications. The model describes the relations, steps, and the order of the actions to be taken by the actor, while the specifications describe the intended requirements or conditions that need to be met by the concept in the domain. The specifications indicate a declarative form of describing a concept and model a procedural construction project. This model indicates how the elements should be organized in construction documents. The specifications of an element indicate formal characteristics of the element such as the operating temperature range. A brief observation of these forms of representations, the MasterFormat taxonomy and the temperature range expressed in natural language, suggests a description of a concept that captures a particular intention of the modeler. The taxonomy describes a set of elements that are made of plastics and the specification, the intended operating range temperature. The modeler describes through these representations the construction

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81 Clearly, the taxonomy explains how the breakdown of the plastic elements concept is defined, and the specification describes an intended temperature constraint. Therefore, the specifications are sets of descriptions that capture the intention of the actor with the representation, as described in the preceding taxonomy model example. In other words, the specifications attempt to describe the intention of the modeler or construction participant with constraints or action constraints on the elements in the domains. Furthermore, the modeler specifies the conditions of the situation of the element described in the taxonomy through the specifications in order to balance poor, explicit descriptions of the concept in the taxonomy. From the taxonomy model example, two elements have to be outlined. The first element is the construction participant or interpreter, who is the mediator between the domain and the representations or the model. The second element is the representation that prescribes the behavior of the agent that manipulates it as well as the intention of the modeler or the actor that builds the representation. The actor that builds the representation, or modeler, attempts to make explicit the constraints of the concept in the world. This task cannot be fully satisfied due to the infinite and diversified nature of the world. The use of the representations on a project by the construction participant is not a is based on representations that are incomplete or poor. Small domains can be systematically represented with acceptable and reliable results when the representations are grounded in the domain. However, the unique nature of construction projects makes them a source for infinite richness that has to explicitly be conceptuthe poor representations is essential for grounding them in the domain. In other words, the interpreter as a cognitive agent should solve the complexity of applying poor representations in

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82 the real world. Accordingly, there is a need for constructing new forms or representations that Characterization of the Concepts The assumed characterization notion in this investigation involves the description of abstract, mental structures, of entities, of events, or of relationships from a domain performed by an actor as cognitive agent. The description is the translation of the concept into syntactic or natural languages, visual representations, or formal structures such as models with the purpose of sharing or communicating the concepts to other actors in the community. The undertaken course of action of the community for characterizing concepts is through the definition of the details and conditions of an entity or object. These entities and objects are resources that play a particular the role in a construction project. Details and Conditions The details and conditions are common words used by the construction community for defining the characteristics of any concept used in a project. The use of the terms details and conditions is a simple form to describe concepts as opposed to complex and formal forms. These complex forms of describing concepts involve ontological distinctions and designations of category of entities, events, or relationships. The description through details and conditions comprises geometric features, components or parts, additional or assembled items, and functional characteristics. The details are modes of description with features (e.g. geometrical) and other relationships (e.g. dependency relations). For example, the details of a concept which describe functional characterist

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83 The conditions construction concept is involved. For any concept, specific situations, which are bounded in a space-time region, are considered and are labeled as situational conditions. In the construction domain, situational conditions includes state of affairs, which emposition, site, place, and settings; status condition, which is the stage of the concept (e.g. completed, installed, delayed) during its life in the time-space region; and the relations with other products or context relations (e.g. set by, part of). In this research, context relations are strictly locative to the object the concept describes. This means that the space or region of analysis is limited to next locative entity. Situational conditions aids in analyzing the states of affairs and context relations. As an illustration, Figure 4-2 conditions of the visual symbol representation and the possible situational condition (e.g. relative position of the wood window in the wall, and the window settings). As such Figure 4-2 sketches the construction concept context relations and indicates the state of affairs of this particular entity. Figure 4-2. Visual representations of situational conditions

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84 For example, in Figure 4-2 another physical concept; the wood window is vertically placed in the wall. The wood window two concepts. Implications of Employing Concepts for Interoperability As was explained in the examples about the reconciliation of two conceptual structures the existence of dissimilar sources of information that generate representations of concepts, is the source of the problems encountered in developing semantic interoperability. Evidence of this problem is found in the difference between the semantics of the conceptual models found in representations such as standards in the construction industry (Mutis et al. 2005). A compromise is suggested in this study between the cognitive and pragmatic approaches that transthe concepts per se. The central characteristic of the translation is thasimilaritieswithin the results by virtue of the perspectives of the actors who have generated the representations of such concepts. Concepts are furnished a priori by the experience of the actors in the learning process. Thus, if the agents attempt to translate them into a representation, they may have different results. This investigation concludes that the representations that are interpreted and translated fully and directly understood by another actor. The existence of a direct link between the supplied representation and the interpreters does not guarantee full understanding of the translated concept. The main implication of this conclusion is that the consideration of a set of sufficient conditions to represent a concept in a representation does not guarantee the understanding of the

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85 concept. If formal languages such as logic, which employs symbols, are used as forms of representations, they can represent constraints and, at the same time, are rules of containment. These formal languages express a form of understanding, but do not fully express the characterization of a concept. The representation expressed in these formal languages is a result of assignments of symbols that refer to some entity in the world with the purpose of expressing meaning. For clarity, the assignments represent a set of theoretical structures that include the elements as members of a category that satisfies certain conditions. Consequently, under this assumption, an interpretation that satisfies the set of conditions for symbols is considered true; otherwise it is a false interpretation. This rigid form of assertion of truth for interpreting a set of symbols is further examined within this investigation together with the compromise between cognitive and pragmatic traditions. The purpose is to suggest new strategies for finding levels of knowledge representations that contribute to the understanding of the interoperability paradigm. The modus operandi by employing concepts under aforementioned assumptions is fully explained in the following chapter. Situations and Contexts A contribution of the understanding for the characterization of concepts is complemented with the notions of situation and contexts. This examination navigates through the ideas of distinctions on these ideas are the purpose and conceptual similarity principles. Roughly, purpose inducts the identification of explicit information to describe concepts and conceptual similarity is recognition of the description of a concept in different ways without adopting only one description. The central idea of conceptual similarity is to acknowledge the embodied condition of a concept and the possibility to have similar, but not identical, concepts for sharing

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86 among other members of the community. These principles are brought to illuminate the characterization-interpretation cycle in the construction industry scenario. Situations A Situation is processes or an attempt to provide an interpretation for modal assertions. The description implies the interpretation of what the perceived world could be. This investigation does not search for formalization within a modality that addresses concepts like possibility, impossibility, contingent, and necessity. It addresses the interpretation and characterization cycle of the situation and contexts. In this analysis, the assumption is that the situation and contexts conserve the same modal status within the cycle. The conservation of a modal status puts the situation in a scenario where its characterization and its interpretation, although complex, are viable. If it is considered that the situation is possible to be described, then the interpretation is possible to be performed. If the context is impossible to describe, then the situation is impossible to interpret. A Situation continuant processes or an attempt to provide an interpretation for modal assertions. The description implies the interpretation of what the perceived world could be. This investigation does not search for formalizations within the modality that addresses concepts like possibility, impossibility, contingent, and necessity. It addresses the interpretation and characterization cycle of the situation and contexts. In this analysis, the assumption is that the situation and contexts conserve the same modal status within the cycle. The conservation of a modal status put the situation on a scenario where its characterization and its interpretation, although complex, are viable. If a situation is considered that is possible to be described, then the interpretation is possible to be performed. If the context is impossible to describe, the interpretation is impossible to interpret.

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87 Situation involves a maximum set of propositions that can be expressed in a representation. Situations can be characterized as extracts opossible worldsstates of affairs of the world or map conditions of the imaginary world. The notion of situation possible worlds semantics (Quine 1981). The nature of the incommensurability of situations and the number of domains where the situation can be derived from are central for understanding the characterization difficulty of situations. In imaginary domains, the characterizations of situations are extremely complex to represent. They are only possible through the use of poor metaphors that are created or assembled on representations. Imaginary situations have to be assumed by the interpreters, and they cannot be characterized as formal representations by the creative, cognitive agent. This research recognizes the impossibility to define unique states of affairs due to the infinite number of situational conditions that can exist. As a consequence, construction industry practitioners struggle to define them by employing the paradigm model. The description of a situation in a representation is intended to accurately translate the perception within a representation. There is not a complete description of what is captured by the senses when the cognitive agent translates what it has perceived from the world into a repperception and interpretation of a concept are reliable (Margolis 1999), for instance: If an

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88 interpreter, in the dark, at certain angle, considers that a crumpled bag looks like a cat, he or she interprets, under this conditions, the bag as a cat (example from Magolis 1999). The Translation of Situations into Representations The organized knowledge, which can be grouped as domains, shapes abstract regions such as the pragmatics domain among other forms of organized knowledge where situations can take place. Actors translate the situations within the sphere of this organized knowledge into representations. Situations, as well as concepts, can be represented through several forms. Their that stand for visual representations, can be used to describe situations and their corresponding explicit information. If an actor attempts to translate a situation representation, the translation involves the explicitness of the information. The translation of a situation includes the constraints that explain the conditions of the conceived situation. In the construction industry, the descriptions of concepts are typically developed into representations created within the space-time domain. The situations, then, are commonly described in the space-time region. The construction actors who participate in social activities share these domains. The situations need to be characterized through social conventions for being shared and communicated. A construction project is a common, social context that actors share on a physical and a temporal region. In these common domains, multiple situations can take place and they must be described through multiple representations within conventional, social forms. Situations can either require or captured image by a lens of a camera is an example of a description of a situation that does not required a translation. It can be easily noticed that the actors who interpret the captured situation share the same space-time dimensions. Consider the situation shown in Figure 4-3 of the

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89 installation in progress of a sound isolation layer for a drywall in a construction project. The physical object is placed in a space region, and the temporal description -in progressis assigned in the time dimension. In Figure 4-3 the space is domain defined at a particular location in the construction project, and the event in progress is a time dimension. The construction participants share the same space-time region in a social context, and the photograph is a social form or representation. The actors then can perform interpretation of the situation of the shared social, space-time region in the construction project by employing a common convention form. In Figure 4-3 the image captured through the lens of a camera does not require translation, just interpretation by the construction participants. Figure 4-3. Image of a situation. Stability of Situations The common domain where the situations in construction project take place is the space-temporal region that has as components the space and time domain. By virtue of this domain, the described situations continuously change. The remained question is that of what changes can be

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90 considered significant in the situation and how these changes can be instilled in the representation that describes such situation. The space-time region is central for the description of situations on construction industry projects. This notion is aligned with the pragmatisms of James (1897; 1912) in his suggestion that a significant situation cannot be left in an arbitrary, space-time region without bounding it with other events and contexts. Our research addresses the characterization of situations and the necessary assumptions and conditions for the validity of these characterizations. The first approach that should be taken to address the aforementioned questions is one that explains the concept which is extended and applied to the situations described in the representations. In order to define this notion, the role of semantics within the representation must be taken into account. The role of semantics within representation was clarified in the previous sections of this chapter. Stability of situation determines the permanency of the conditions and constraints that are instilled in the representation by the actors who generate and describe them. The intended semantics of a situation must be valid when the interpreters perceive the explicit set of conditions and constraints of such representation. The permanency of the conditions and constraints defines the validity of the representation when actors of the community perform the interpretations on this representation. In other words, the stability of situations affirms that the primary set of conditions and constraints, which contain the intended meanings or semantics, is not lost. It can be noticed that describing a situation requires a continuing subsequent set of descriptions; its nature implicates the time domain. Then, the primary set of conditions naturally changes. The description of this situation should be continuously updated in order to reflect the corresponding changes. The described intent can be lost by virtue of the nature of the temporal domain. If the

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91 explicit semantics, through conditions and constraints within the primary description of a situation, is not lost when other actors perform interpretation on that representation, then the situation is considered as stable. Furthermore, if the semantics contained in the primary set of description is not lost with the added, subsequent set of descriptions to the representation, the represented situation is also stable. The specifications about how to place concrete type K in a particular project, at certain time during a scheduled construction process, are elaborated by natural language. This natural language is a form of representation which describes a situation, and it is composed of a collection of signs described by axiomatic propositions, as follows: Concrete temperature at placement must not exceed 90F; concrete over 60 minutes old must not have a temperature greater than 80F; no concrete shall be placed that is more the 90 minutes old measured from the time of batching; concrete temperature at placement must not be less than 55F and concrete shall be protected from freezing temperatures for 7 days after placement, and the ambient conditions must be 40F and rising at time of placement. In the preceding example, the description of a situation through natural language representation is stable if the primary purpose of the semantics, definitions of physical conditions for concrete-placement type K, does not change. It is valid to notice that the purpose of the semantics is originated from the actor that generates the primary description of the situation. Thus, if the conditions are interpreted by other actors as describing concrete-placement situation of concrete type V, the indented description is not stable anymore. The fact that other actors misinterpret the situations can have multiple causes, which are not further scrutinized within this investigation. Roughly, within the characterization-interpretation cycle, this analysis recognizes the cause of change motivated by the temporal dimension of the situation. Concrete type K, for instance, was replaced with concrete type II,

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92 which adds admixtures to high-strength concrete such as fly ash and silica fume, under new regulations. For the discernment of the characterization of situations, our research does not inquire after the causes of their change, after the truth of their change or after any other inquiry derived from their nature. The focus of this investigation is aimed at understanding the concepts in the characterization-interpretation cycle. Situations are descriptions of some instances derived from these concepts through representations such as metaphors, sings, or formal methods. As situations are complementary to the understanding of the characterization-interpretation cycle of concepts, this research analyzes the influence of situations as well as contexts within the conceptualizations that take place in the construction domain. Stable Situations and Evolution of Concepts The acknowledgment of the temporal region is central in order to make the distinctions of the situations continuous evolution of concepts within construction projects. These distinctions are necessary to identify the difference between stable concepts and stable situations. In the same way as situations, concepts are stable when the primary description, generated by a cognitive agent, retains its meaning to an interpreter. The evolution of a described concept consists of the addition of conditions or of constraints to complement an intended description. These are natural additions to the representation of described concept and they are driven by the situations concern the explicit and detailed description of the instances of the concept where the primary purpose of such description is conserved. The instances involve propositions, through constraints and relations, with or without other concepts. One characteristic of the stability of situations is that of these propositions, which contain intended semantics generated by agents concerning concepts described by the representations, do not significantly change over time.

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93 It can be noticed that the nature of stability of concepts or of situations depends of the primary semantics. The actors who generate the description of the concept of situations expect that their description conserves such semantics during their interpretation. The subsequent identification over a period of time of the attempted semantics relations on the representation by interpreters suggests stability of concepts or of situations. A drawing of a set of squares constrained into two dimensions is placed in an architectural drawing pad as shown in Figure 4-4 The description as a set of squares is a primitive description of a concept that the author translated to the visual representation shown in Figure 4-4 Suppose that the primary semantics of the set of the squares is concept. Thus, the actor that generates the description expects that further interpretation of the concept. In this sense, if these further interpretations take place as shaped, squared windows, then the representation holds stability. Figure 4-4 Following the same example, suppose that additional constraints are added to the description of shaped, squared windows, which in turn are additional semantic relations to the

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94 concept. As was mentioned, the constraints help describe a concept and give additional meanings. In the case of Figure 4-4 these constraints indicate a situation or an instance of the concept squared, shaped windows. Adding the constraints through adjacent lines and numbers represents this situation of the architectural drawing concept. The constraints include numbers on the set of small squares and distances from one face to the other face to each square on the set of the bigger squares. In the visual representation shown in Figure 4-5 these lines are constraints of size and give semantics about the dimension of those representations. The constraints are instantiated with the inclusion of a value shown by the added numbers on the lines. The example of Figure 4-5 illustrates the evolution of a concept and its instantiation. The addition of conditions and of constraints opens the represented concept to generate new situations. If the inclusion of this constraint preserves the primary description of the representation, then the represented concept is considered as stable. Figure 4-5. Constraints that indicate a situation of the concept squared, shaped windows. The evolution of concepts corresponds to the natural change of the conceived concepts. The actor that generates the representation translates it from his/her mind to the representation and in turn adds constraints and conditions to simplify or diminish the universe of possible

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95 interpretation by other cognitive agents. The new constraints are mapped and added to the representation through the use of metaphors, signs, or formal representations. The evolution should be perceived through new distinctions. An example that illustrates this point is the addition of another dimension than constraints the representation of Figure 4-6 The assumption of the evolution example is that the actor starts the conception with the most primitive metaphors or signs of the square, shaped window concept. Although these distinctions are shown as obvious in this example, they could be very complex in other cases. The example also shows that the primary, attempted semantics is preserved during the evolution of the concept. Figure 4-6. Evolution of concept representation which keep initial semantics. Contexts Context is a multidimensional notion that is used in diverse disciplines. This notion draws a sense of ambiguity when it is not distinguished from other fields. In the information systems context, it is related to metalevels that separates related, extrinsic information from the intrinsic information, and they are used as a method of reasoning. In artificial intelligence the context is used to separate syntax expressions that operates on certain rules elaborated for certain purposes. In linguistics the context defines the relevant dimensions of the communicative situation that are

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96 relevant for the generation and interpretation of the discourse by employing additional surrounding natural language from the represented syntax or conversation. In this investigation, the notion of context is close to the focus of the definition stated in the semantics field. Context in semantics, which has its roots in linguistics, philosophy, and communications, is related to the method for finding relations to situations. In this area of knowledge, context is a method in which actors map elements of situations to other elements within the same or other domain with the purpose of semantically enriching the definition or assertion. This enrichment is performed with the intent of communicating a description of a concept or situation through a form of representation such as texts, oral discourse, images or visual representations, among other forms. A visual representation that resembles a concept doors screen can be further be described by semantically enriching it with other situations such as adding other relations to the components of this visual representation. These relations can be of different sort such as the assignment of size constraints to the on a computer screen. The purpose of semantically enriching a concept or a situation with additional relations is pivotal to the definition of context. Purpose can be thought of as a pragmatic function to help communicate a situation or a concept through representations. Thus, the process of communication by using representations also adopts intentionality aspects from the intervening actors. The situation or concepts that the actors communicate are embraced within a social context. Thus, any additional relation that is added to describe the context of a concept or situation should follow social conventions. The context of a concept or of a situation translated w social

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97 conventions which are interpreted by other social actors. Also, intentionality aspects help address the definition of the context relation added to the description of concepts. ess-steel framed -can be embedded. In Figure 4-7 -t in Figure 4-7 (b) follow the same type of social convention about the -steel framed window. These conventions are the result of some a priori experience with the description or the concept, i-steel aforementioned principle of conceptual similarity, even if they have social conventions. In Figure 4-7 (a) and (b), this situation is represented through the conservation of the same shape and dimension constraints, but the internal components of the concepts vary. The convention that these actors share can be enough to communicate the purpose of the concept or of a situation. In this case, the purpose is to make the contractor adopt a variety of bricks in order to consider them -The architect has a purpose for communicating additional context relations so as to describe the situation where these brick variations, or context relations, are involved. The architect aids the description of the situation with additional context relations. In Figure 4-7 (a) and (b), these context relations are represented by the arrows.

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98 (a) As a glass Window (b) As a sketch of a window to other wall materials Figure 4-7. Context relations. The selection of a context relation that expresses semantics has to be associated with the purposes of communicating the situation. The interpreter actors have to acknowledge the conditions and constraints of the communicated situation. The explicitly expressed purpose through social conventions, which both parties understand, is a catalyst for the interpretation of a situation. Concepts and situations are embodied, and they are constituted a priori by experience. Actors can have countless semantic relations for interpreting the concepts or situations due to the principle of conceptual similarity. The interpreters simplify the possible context relations through the identification of the purpose. The distinction of purpose, which is a pragmatic function for accompanying the notion of context, is central within this investigation. This pragmatic function includes the definition of intentions, purposes, and reasons of a concept or situation. This function determines a layer of information that should be explicitly communicated to concepts or situations, and its components or characterisituation or concept. In this research, intention indicates one set of possible semantic relations that the cognitive agent has with the object in order to assert an interpretation, e.g. the Project

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99 consolidated estimate. Purposes connote an interpretation of a cognitive agent of the interaction of some represented entity with other represented entity, e.g. the purpose of the glass in window is to aisle two environments, but keeping the environments visually connected. Reason suggests an entity, e.g. the knob of a window would explain that it has the close-open capability, however the architect interprets the knob in its decorative role. Communicating concepts or situations by using representations embraces the use not only of the semantic relations of such representation but also intentionality aspects from the actors. The intentionally aspects were proposed by Peirce (1991) within the thirdness category. Our research embraces the embody theory of concepts and the thirdness category as a form or layer for reasoning is also recognized. It can be noticed that the use of the word category implicates the use of a system for classifying genera or kinds, in the widest sense of this term. Thus if the spirit of the definitions is taken as a system, it will obligate or commit the actors or interpreters to ontologies by answering the metaphysical question: what is there? Thus, the layer of intention should be understood as a layer for reasoning. In the same sense, the expression of concepts or interpretation of the representations are the subject matter of the coThus, the thirdness category or intentionality layer is complementary to the semantic relations defined within the contexts. Context and Granularity Concepts and situations are embodied, and they are constituted a priori by experience. The identification of the concepts through sings, metaphors, or through formal representations

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100 interpreters observe the expressed context relations, which express semantics and the associated purposes of communicating a concept, at certain level of granularity according to their capacity and experience. If the interpreters do not find similarities of the expressed concept in the body of knowledge for the associated purposes, the granularity representation is deficient for the a priori experience does not match any similarity, according to conceptual similarity. Thus, the granularity expressed in the representation is deficient to acknowledge the conditions and constraints of the communicated concept or situation. If the purpose of a representation is explicitly expressed through social conventions, it aids the interpretation of the concept or situation and it complements the granularity of this representation. In an elemental case example, suppose an interpreter attempts to match a visual representation, shown in the right hand side of Figure 4-7 to a similar form in his body of knowledge. The first reaction of the interpreter is to focus on the primary semantic description of the right hand side representation, set of squares printed on the architectural drawings. The adjacent, but separated by blank representation on the same piece of paper, is initially ignored. If the granularity of the representation is not sufficient to identify the semantics, then the interpreter needs additional context relations to aid the interpretation. This case is represented with the addition of an external visual representation on the left side of the Figure 4-8. This additional representation can be linked as a context relation that complements the granularity of the expressed concept. The interpreter focuses the attention on these two representations and he or she attempts to find semantics through a context relation. If the context relation is identified as

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101 part ofelement of the set of squares and that they are metaphors of Figure 4-8. Focus on a context relation for complementing the granularity level to interpret a Characterization of Situations and Contexts The process to translate a situation or context to a form of representation is complex. These characterizations can be done through metaphors, sings, or any formal form. The characterization implies the assumption that the generators and interpreters recognize the same modal status of the representation. The status indicates the existing state of concept or situation such as possible or as imaginary. An imaginary situation should be assumed as a mind creation for the interpreters, and not a representation that can be mapped to the domains that the agents share. If is considered as possible to be describe a situation into a representation, then it is possible for its interpretation to be performed by another actor. The undertaken assumption is that actors a priori recognize the conditions that define this status. It is not possible to generate representations if the interpreters do not assume a status. A representation whose status has not been defined has the complexity of an infinite reasoning about what it is trying to represent. Safety concepts are represented by possible situations, and they should be recognized by the actors in a construction

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102 project. If the status of possibility is not a priori recognized the reasoning about the representations is infinite or not feasible. Top Ontological Distinctions The representations need to be classified into ontological distinctions. The classification classifications are abstractions of conceptual interpretation by perception, and they are combined to generate categoriesare combined to generate study of the existence of entities, events, and their relationships, as well as it is the resource used in formalizing categories, i.e. ontology categories. This research recognizes top ontological distinctions as the fundamental resource for relating a concept, a representation in the space-time region, and an actor or interpreter. This distinctions are based on the trichotomy of ontological categories proposed by Pierce(1991): Firstness, Secondness and Thirdness. Pierce explained that the first ontological category of any concept is the existence that is independent of anything else, the second is the conception of being relative to, and the third is the conception of mediation where the first or the second are brought to a sition by using an example from the construction domain, observe Figure 4-9 Each layer of Figure 4-9 represents an ontological category. In the independent category, an architectural drawing of the doors concept is specified in the drawings. It exists by itself. The drawings without any interpreter are simply an entity of papers and ink. The relative category that the pattern of drawings reflects is a shape of doors. Thus, there is relation between the drawings and the patterns of drawings, which take the shape of doors. The relative category is possible under the abstractions of the interpreter who performs the relations. The mediating category describes the purpose of the pattern of the shapes, which is to construct a

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103 mediate, through the intentions of the interpreter, the absrepresentations such as image schemas of doors are metaphors, which are subject to interpretation by the cognitive agent. The reader must be intrigued as to why this approach bases the interpretation of concepts on ontology categories. This approach claims that there exists a strong link between cognition and concept, the former represented by a human being (how the world is interpreted) and the latter by the representation of reality or the real world (how the real world is represented). An ontology, which reflects this link, should be elaborated in a way that reflects the generalization of specific concepts of the real worparadigm (George Lakoff and Johnson 1999; Gibson 1977), which is a good compromise Figure 4-9. Conceptualization on a domain.

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104 xt-oriented semiotics (Gangemi et al. 2001). What is most important within the introduction of Pierce categories into an ontology is that this research recognizes the importance of the intentionality of the cognitive agent. The cognitive es capture the reasoning of a concept and classify it into categories of existence. These categories indicate a common denominator of the concepts of the domain, for a more redefined domain. The agent must recognize what he or she needs from the representation of the concept and contextual relations included in speech act are (Searle 1995).

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105 CHAPTER 5 A DISJUNCTIVE OF THE MODEL PARADIGM The description of concepts into some form of representation does not guarantee the understanding by other members of the community of what is described. The choice of representation implicates different kinds of problems primarily influenced by the purposes of the actors in a domain. In a brief examination, consider aspects of representations such as logic and ontology (Sowa 1999). The choice of representing a concept in formal logic involves the lack of a subset of logic expressions to determine meaning of what is intended. The choice of representing a concept through an ontology implicates multiple problems, briefly: different choices to categorize concepts, different forms to name the same concepts, and different approaches for axiomatization, among others. In addition, the choice of employing the symbolic approach in order to characterize concepts can be seen as complementarily driven for some purposes, but for other purposes, the same characterization can be seen as contradictory. An ontology that describes the sets of pipes and water pumps for buildings can be complemented as much as possible with more axiomatization. The result might be more accurate for modeling pipes in buildings for the hydraulic engineering, but might be seen contradictory if the electrical engineer attempts to reconcile his model with the hydraulics ontology on the specifications on electrical, local regulations. A description of a concept in an ontology rests in the mechanisms of categorizations. The mechanisms are methods for considering only what the significant parts of a concept are from ontology of a modeler in Europe about construction materials for sewerage cannot reflect the same categorizations that are made by another ontology developed in Canada or in Texas about

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106 Ontological distinctions target the structure and the nature of some entities in the domain, but they do not target distinctions that include the role of the entities, which, in fact, is cognitive dependent. That is why we need other approaches that handle the mediation of the cognitive agent, the characterization of concepts through roles, and the characterization of concepts that includes context relations. Our investigation directs the attention towards the process of interpreting a concept from a representing concepts. The scrutiny on interpreting concepts results in the study of the conception of truth by cognitive agents on entities, states of affairs, and events in the world. There are differences in the notion of concepts, which rest where the concept was originated and was formed, between the analytical philosophical traditions, and within the cognitive and pragmatic traditions. This chapter illustrates the assumptions of this research concerning the dependency of the characterization of concepts with its purpose and the influence of a purpose when an actor performs an interpretation of a representation. This assumption is based upon the hypothesis that an entity, event, or relationships that are perceived in the space-time region has no intrinsic meaning The identification of meaning of entities, events, or relationships in a domain depends mind to define concepts. The meanings of entities, events, or relationships are not intrinsic per se but are dependent on cognitive aspects. The notion of concepts as abstract, mental structures of entities, events, or relationships from a domain is a generalization of a more comprehensive notion that goes along with the philosophical approach of this research, which is based more on a compromise between

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107 cognitive and pragmatic approaches rather than on analytical, Western, philosophical traditions. The aim of the analytic tradition is to clarify philosophical problems by examining the language that employs symbols to express it. This tradition privileges the use of sense and reference in the formation of meaning (Gottlob Frege (Appiah 2003), Kurt Gdel (Nagel and Newman 2002), Alfred Tarski's (Tarski 1944), among others). The differences in the notions of concepts between the analytical traditions and the compromise of cognitive and pragmatic traditions rest in the origination and the formation of such concepts. The cognitive notion of concepts is contingent on the human mind, while the analytic tradition notion considers concepts as extractions from the world, as if they were the world itself, which constitutes a characterization of an objective reality. In the cognitive and pragmatic perspectives, the notion of a concept as an abstract mental structure takes place in the human mind and serves to designate reasoning on categories of entities, events, and relations. Categories are the basic distinctions generated by the senses, and they are refined by experience in a learning, cognitive process. The cognitive process serves as a medium for judgments not only about what is captured by the senses but also about what abstract entities are identified by distinctions. Distinctions are comparisons to other primary mental structures learned a priori. The distinctions categories that conform to Distinctions are based on comparisons that employ contrasts with the purpose of finding relations to a primary, mental structure. Reasoning, a basic mechanism of inference that uses these distinctions, is an abstract and mental process that seeks the identification of those primary,

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108 Johnson 2003), and they are successively and continuously complemented and modified The influence of the pragmatic perspective in the notion of a concept, particularly on the explained definition of category, is the addition of a function upon the distinctions and the reasoning mechanisms. The function is framed within the role of intentionality. Intentionality mediates between the mental structure and the entity. The mediation is aimed to shape the meaning mental construct that conserve the notion of a particular concept and the distinctions, such as those instilled by stimuli from an entity in the world, constitutes semantics or meanings. The mental constructs are consciously complemented and constitute a continuous learning process he mental constructs are needed. From the pragmatic perspective, an immediate consequence of the notion of concepts is the rejection of the definition of concepts as derivations from properties of entities, of events, and of relationships inherited from the physical world. The result is an additional function upon the distinctions and upon the reasoning mechanisms that shape meanings is that the actor clarifies what the de facto concept represents. The meaning or semantics of a concept is established a priori, it is clarified with this additional function, and it is framed within one feature: intentionality. Although the clarification about de facto role of a conce level of understanding concerning that concept. The shaping, meaning procedure can be apprehended as a mental process to find additional acknowledgement by stimuli of an object or of a symbol in the external world. The agent

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109 recognizes meanings because of the distinctions and of the reasoning mechanisms. This recognition is performed through the reasoning process and it is made possible through the The level of understanding about a concept involves dependence of the agent who finds semantics concerning the concept and, at the same time, concerning an interpretation that is a believed to be shared with other members of a community. These beliefs are considered social facts (Searle 1995) and they are exclusively related to a social understanding of the concepts. on of truth about the interpretation of concepts in the world. The alignment is revealed on a common shared structure of knowledge on domains. Agents share a common understanding that implies semantic relations with the purpose of communicating concepts. The so-institutional factscollective intentions as a distinct form of intentionality Searle proposes a set of rules that are essential for collective intentionality. The Limitation of the Modeling Paradigm As was mentioned earlier, the divergence on the understanding of a concept among actors takes place when actors generate representations of concepts in order to communicate and when actors perceive the representations in the interpretation of those concepts. The generation of concepts from the analytical traditions compromises the understanding by the interpreter of the evidence of some phenomena in the world. The phenomena are syntactically defined in symbolic notations such as logic, frames, and semantic networks, among others, and are deliberately organized to define concepts. The characterization of symbols and the manipulation of them is a mechanical reasoning process similar to a mathematical manipulation. A group of a community

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110 addresses the understanding and characterization of the world into symbols and other forms of representations; in other words, the representations are aimed to be universally understood. Models involve grouping a set of relations and symbols with the purpose of characterizing some phenomena of the world and of being shared and understood by a community. Symbols refer to some entities of the world with properties and relations apprehended within them. Models hold a symbol characterization of the world that should satisfy particular world-states. Generally, those satisfactions are defined by the inclusion within a category. If a frame has aluminum as the main component, it holds a piece of glass, it is joined in a whole piece, and it separates two environments, it belongs to the glass-window category. Models assert truth if the satisfactions of their characterization are met. From this analytical tradition, then, the identification of meanings of each particular symbol in a model can be distinguished in the relations with other symbols that are included within the same model. Models are a family of propositions that constitute approximations that resemble instances or events of the world in order to be applied when pre-established conditions are satisfied. In this definition, propositions are correspondences that presuppose and assume truth of some phenomena of the world, and approximations are simplifications of a complex nature of the phenomena that are applicable when the same cases occur or, in other words, when the identification that satisfies the conditions are met. The simplifications are abstractions that neglect the influx of other factors in the phenomena. Correspondence For better understanding to the notion of models and their limitations, an analysis of the correspondence implications is necessary. Correspondence is bonded to the theory of reference that stems from the work of Gottlob Frege (Appiah 2003). Fregean theory considers senses as referents that link a symbol in the proposition to the world correctly. The distinction of senses

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111 expressions refer to the entity Venus, but they have different senses. The referent in this expression is the mode of prreferent determines how it is picked out or associated from the world in the mind. Frege stated that referents hold truth-value, which is either True or False, in virtue of the conditions that hold properties. Senses are abstract objects that exists in mind and that do not interact in the physical world. Frege also used analytic distinctions in proposition to identify the parts that inform about a sense and the parts that are referents within contexts in expressions. The sense of a whole proposition is determined by the senses of the parts, and, in the same way, referents of the whole proposition are determined by the parts. Then, an expression has true value or false value when the reference saw a professor of Referents are supposed to indicate truth in the correspondence between the symbol and the world. Correspondence is a metaphysical notion that ss that the description of the world is truth by the existence of some observation with corresponding elements and a similar structure; metaphysics is concerned with the explanation of the nature of the world. Correspondence refers propositions in a model become false if the correspondence does not adequately fit and they become truth if the opposite case occurs. One of the implications of considering the

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112 correspondence theory, which is an assumption in the modeling paradigm, is that the absence or failure to formulate a proposition in the model, which in turn constrains the model, regards false instances of the world that should be included in the model. A failure in a model is considered a false fact Willard Van Ormand Quine, one of the most influential American philosophers, contradicts the idea of referents and correspondence (Quine 2006) To be is the value of a variablechoice of a form of logic is the choice to commit to a certain arrangement of the world. From this, Quine accepts the existence of entities of the world when they are described by variables, but neglects the commitments of properties or other abstract entities, by assigning values to variables. Commitment is what an actor or agent considers real in a situation in the world. A commitment is an assertion of truth, which is termed ontological commitment. Quine recognizes an ontological commitment created by variables that describe objects or entities, but does not recognize other commitments such as properties of the objects. In other words, Quine expresses explicitly a commitment to the relation of the entity and symbols as variables. The choices of existence of those entities. Variables are symbols employed in logic, and entities are the conjunction of properties of things in the world. For example, if an actor selects the variable, in for all aluminum_windows, the entities that can vary over aluminum_window are the entities whose existence is assumed. is that an actor does not embrace truth when the actor assigns an interpretation of the world to a variable. An actor bounds the interpretation to a variable, but that variable does not contain any

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113 implicit contents of properties or abstract entities. The properties and other entities might be implicit in the first description of the entity or object, but they cannot be described explicitly by employing variables. In this research view, this point underlines the failures of modelers of domains in attempting to communicate their interpretation to a model of the description of the phenomena, which is expressed axiomatically through models. Our investigation claims that commitments are interpretations by the modeler of the observed entity. Our investigation also rejects the notion that these interpretations are tantamount to truth. As models are based on propositions, they suffer the limitations that logic and the symbolic notations convey. Models cannot capture the richness of the phenomena of the world in their syntactic notation. Furthermore, the continuous change of the physical world makes it impossible to set stable propositions. These particular propositions are mappings from the instances of the an objective relation between any symbol aassumption is that the propositions are a set of necessary and sufficient conditions that describe the phenomena. The complexities of the world cannot be accommodated in the limited resources of symbols and propositions. Embodied Concepts The inclusion of the word embody within the notion of concept implies that the sensory-motor systems are main characters in the definition. Concepts are created and shaped by employing inferences that take place in brain as a result of the way the brain and body are structured and in the way they function with other cognitive agents and in the physical world (Lakoff and Johnson 2003). Under this perspective, the actors depend strongly on the concepts and on the form of reasoning.

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114 The claim of this line of thought is that concepts are created through the sensory-motor systems independently from the categories of reality. Concepts are products of a continuous adjustment through a learning process of the cognitive agent, but the mechanisms for perception and object manipulation are responsible for conceptualization and reasoning. Concepts are represented as mental structures that are continuously adjusted by learning experience. The mental structures can be encountered in basic levels, and they are used for reasoning. These basic structures can be used as metaphors for inference and reasoning. The actor takes the understanding of the phenomena by perceiving it as truth. This is embodied truth, not objective or absolute. However, it is not subjective (Lakoff and Johnson Cognitive scientists had proposed a spatial relation as a common domain from which to derive truth, and, from this domain subsequent relations to derive semantics are determined (Grdenfors 2000). From a cognitive science perspective, truth is gradually adjusted with the interaction of the agents in the world, while within phenomenology, truth is perceived and discovered from experience in the world. The embodied concepts are further explored through our survey on semiotics in Chapter 7 as well as through the characterization of concepts in the following sections. Semantic Holism The mapping of symbols to entities in the world through referents is not objective. The mappings are products of an interpretation made through the senses, and therefore cannot support a determinative truth. The understanding from the cognitive line of thought concerning the foundations of meanings of representations and, from the analytic perspective, its contrast to symbols and language assigned in logic and their connections to entities in the world, is a central component to enlighten the problem of interpretation in interoperability.

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115 Within the analytic tradition, all forms of representations that are used for communication, such as natural language, formal languages, and models, can be framed by expressing them as symbols in a form of logical language. The examination of the relations of symbols to the world for identifying meaning started with Quine (1952), who scrutinized symbols from logic, axioms, and their connection to the entities in the world. Quine stated that symbols could not have meaning by themselves without being linked to a set of symbols or to the abstract structure of a model. In other words, the meanings of symbols cannot be derived until all of symbols in the set or in the model are interpreted. An interpretation, under this tradition, means the association made with symbols within a set of symbols or within a model. According to Quine, one symbol is not enough to guarantee the intended interpretation. This doctrine is known as semantic holism. Semantic holism or meaning holism is the idea that the meaning of an expression, which is composed by symbols or set of symbols, depends on its relations to many or all other expressions within the same totality (Pagin 2006). For clarity, holism entails the view that no complex entity can be considered to be only the sum of its parts. Semantic holism claims that arbitrary formal symbols can only have consistent meaning if they are interpreted all at once, as the whole set of symbols. Meaning holism was formulated for linguistic expressions, but Quine extended it to formal syntactic expressions. Meaning holism articulates the idea that expressions or symbols can be interpreted all at once, not in a separate, was attempted by the sum of its parts. The meaning of an expression depends on the totality of the whole set of expressions. The meaning holism theory contrasts with atomistic theories that state that each simple expression can have a meaning independent of all other expressions. It also contrasts with molecular theories, where the meaning dependencies in an expression are

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116 restricted to smaller parts or subsets of expressions, and with compositionality principles that state that the meaning of a complex expression depends on the meaning of its parts and on its mode of composition. This analytic distinction is not a matter of problem solving strategies. In fact, it is a paradigm that has intrigued philosophers for centuries. of a fixed truth when one, unique expression refers to one entity in the world via objective senses. Frege stated that the logical axioms are true because they express true thoughts through references to entities in the real world. For clarity, sense is the mode of presentation of the reference. Therefore, a unique expression cannot hold truths about an entity in the world through references. The expressions that embrace symbols cannot claim truth that characterizes an objective reality in the world. Ontologies that assign variables in order to describe some phenomena in a domain cannot hold truth characterizations. In the same way, models cannot hold truth characterizations; they state axiomatic relations under a set of assumptions. Within the perspective of this investigation, this is a significant problem for communicating meanings of concepts in any domain, such as in the case of the construction industry. Since members of the construction industry share space-time regions, commonalities about entities, events, and relations arise. There are no unique classifications of categories of the entities in the world that pervade for all members of a community. The only general acceptance them by legalization. The enforcement does not indicate an objective characterization nor a universal truth for the members of community. Accordingly, if members of the community recognize that one person has the authority to enforce a classification, then the members of a community should exclusively understand the classification, axioms, and rules as assumed truth about the characterizations.

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117 These enforced rules, classifications, and axioms, which are supposed to describe concepts, are es that employ taxonomical classifications experience an analytical problem when the modeler restricts the categories to what has been inherited. The current investigation proposes that there is no single correct classification, axioms, or rules that define concepts for the construction community. The meaning of a fixed set of axioms time, meanings depend on the level of understanding of the interpreter. The creation of nature of the observed physical world. Granularity Our research proposes the use of a concept of granularity to manage the problem of semantic holism within interoperability practices. We propose here that the way to overcome the problem of semantic holism is through granularity and the way to acquire concepts. This investigation focuses on new levels of representations such as intentionality. The purpose is to address in a different way the characterization of concepts by considering the notion of granularity of the concept representations. The introduction of the granularity notion is explained intention for the interpretation of concepts. This intention makes the agent contrast the intended semantics of the representation with the observed concept representation. This contrasting is a simple cognitive process that makes the agent select the relevant details and situational conditions of the representation of the concept and then perform an abstraction. An actor perceives observational factors that are noticeable. Gibson (1977) stated that what the agents perceive are affordances, not qualities of the object. Affordances are invariant combinations of variables of what the cognitive agents notice. In this fashion, if a cognitive agent perceives affordances and performs a reasoning

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118 process with them, the agent can perform plausible interpretations by using nonobservational factors such as experience. Granularity refers to what the agent notices. The cognitive agent looks at the world granularities as needs dictate (Hobbs 2002). As mentioned before, the relation one agent has with powered by the intention of the actor. Thus, interpretations are cognitively associated with a certain level of granularity by the agent. As was stated before, representations themselves do not have intrinsic meaning. The semantics of agent select relevant details and situational conditions in order to perform the interpretations. relevanceent or deficient in articulating interpretations. It is clear that details and situational conditions are the descriptions of a concept into a representation. Conspicuously, granularity states that the sufficiency of details and situational conditions contributes to performing accurate interpretations. An important definition proposed by our research is that of granularity level. The granularity level details and situational conditions or irrelevant details and situational conditions interpretations. For example, in a text-based representation of a concept the correct level of the details and situational conditions will be reached when the observer can find the set of descriptions of the details and situational conditions with which to interpret the construction concept.

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119 The actor that generates the representation adopts this boundary in order to describe the representation of the concept with sufficient levels of details from which the observer could elaborate an accurate interpretation. Then, the right level of details and situational conditions occurs when the observer finds all significant details and situational conditions in the representation. The right level of details and situational conditions are the right level of descriptions of a concept into a representation. Thus, when an actor in a construction project performs an accurate interpretation of a representation, a boundary of sufficiency is reached, and when it is asserted incorrectly, a boundary of deficiency From the above analysis, there are two cases concerning the boundary of sufficiency. First, the actor does not have the a-priori relation (e.g. experience) with the representation. In this case, the actor is not able to notice any significant semantic relation between the details and situational conditions. Second, the actor is not able to map any semantic association or notice any significant details and situational conditions because the representation has poor descriptions. This is the case when the explicit information consigned as the description of a representation of a concept is not enough for performing an interpretation. Then the representation is semantically poor and the description of its representation is deficient and accurate interpretations cannot be performed. Thus the representation is not a recreation of the Our investigation proposes the recognition of a triadic relation: representation, relation, and purpose. Granularity levels express and support this triadic relation: the signs, which are representations, are independent from other factors; the relation indicates the relationship between the cognitive agent the representation. If the cognitive agent performs an accurate interpretation, the boundary of

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120 sufficiency indicates that the agent selected relevant or discarded irrelevant details or situational conditionsboundary of sufficiency also indicates that the details and situation conditions that were used, also called explicit information, were enough to perform the interpretation. The information that is explicit is that which has been articulated in a representation. The boundary of sufficiency performing an interpretation of the articulated information of the representation. For clarity, articulated information refers to the associations of the symbols or signs made by the actor that were perceived with the purposed of finding semantics. Figure 5-1 articulates the granularity of the representation and the response of the cognitive agent in a qualitative graph. The boundary of sufficiency is the peak of details and situational conditions where the observer can derive an interpretation. The observer discards other details that are irrelevant while taking into account the interpretationitself does not have intrinsic meaning. The actor identifies the information consigned in the representation that corresponds to the explicit information for the representation. Figure 5-1 illustrates that the granularity knowledge were not enough to perform an assertion on the interpretation. This follows with the recognition of the current investigation that there should be an a-priori existing relation of the mentioned, interpretations depend on non-observational factors such as the level of knowledge of th the intended concepts among others.

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121 Figure 5-1. Qualitative relationship between quantity of explicitly given information and accuracy of its interpretation. Figure 5-1 was developed to exhibit this level of knowledge factor, when the characterization of the representation intersects the boundary of sufficiency. Thus, if the level of knowledge is not enough to perform a plausible assertion concerning the concept representation, the observer reaches the ignorance zone. However, if the case is that the description of the information of the representation is poor and the observer has a proper level of knowledge to boundary of deficiencyboundary in the graph indicates that the characterization of the concept in a representation is

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122 interpretation is a plausible assertion, and it is contingent on the cognitive agent. The word contingent is used to refer to things that are true in only some possible worlds (Appiah 2003) In summary, the boundary of sufficiency that accounts for the details and situational conditions of the represepast experiences in order to fully interpret that representation. If the boundary of sufficiency of the details and situational conditions are not satisfactory for inferring the meaning of the boundary of deficiencysituational conditions boundary of deficiencydepends ces. Our study advocates that any representation of the concept should be consistent and coherent at the boundary of sufficiency of the details and situational conditions from which the observer can find semantics of the intended meaning and from which the observer can derive plausible interpretations. Conceptualization A conceptualization accounts for all intended meanings of a representations used in order to denote relevant relations (Guarino 1997). This means that a conceptualization is a set of informal rules that constraint a piece of an observed physical construct or of an abstraction. An actor or observer uses a set of rules to isolate and organize relevant relations. These are the rules that tell us if a piece of such a concept remains the same independently of the states of affairs. One particular set of rules, which describes an interpretation of the domain, is called the intended model. A conceptualization of any physical construct or abstract concept in the construction domain must include details that will independently describe the construction concept from its states of affairs. Situational conditions will describe the concepts by reflecting common situations or relevant relations to the states of affairs.

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123 Guarino (1998) further clarifies the conceptualization notion, which refers to a set of conceptual relations defined on domain space that describe a set of state of affairs, by making a clear a distinction between a set of state of affairs or possible worlds and intended models. For better illustration of conceptualization, consider Figure 5-2 which schematically depicts a conceptualization into a specific domain, and indicates components that help define a conceptualization. The components are minimal ontological definitions of the entity, logical axioms that use the syntax and vocabulary of a language, and additional semantic relations, which help describe several states of affairs. Figure 5-2. Conceptualization on a domain. The conceptualization r relations (e.g. has hinges, opening or fixed components). Additional description of the concept specifications, which comprehend context relations and other constraints that do not change with the states of

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124 affairs interpretation. In order to clarify the conceptualization notion in the construction domain, the reader has to keep in mind that a concept in this domain can be described by its details and situational condition relations. Construction concept details comprise their geometric features, their components or parts, additional or assembled items, and their functional characteristics. The concept conditions are the situational conditions or state of affairs, which embrace the concept location, position, site, place, and settings; the status condition, which is the stage of the concept (e.g. completed, installed, delayed), and its relations with other products or context descriptions (e.g. set by, part of). The details and situational conditions then are minimal ontological definitions of the concept that can be formalized by including logical axioms that use the syntax and vocabulary of a language, and additional semantic relations, which help describe several states of affairs. A construction domain example is shown in Figure 5-3 The conceptualization of this of their relations. Additional description of the concept intension, which comprehend context relations and other constraints that do not change with the states of affairs of the concept (e.g. the interpretation. Thus, conceptualization involves the explanation of relevant details and unintended relations from the situational conditions of the concept of the construction domain. Note that

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125 conceptualizations are described by a set of informal rules used to express the intended meaning through a set of domain relations and that these meanings are supposed to remain the same even if some of the situational conditions change. Figure 5-3. Context relations and details for conceptualization. As shown in Figure 5-2 conceptualizations become extractions of the domain knowledge and are specified by ontological categories, relations, and constraints or axioms. Categories are forms of classifications of the ways cognitive agents see the world. Conceptualizations, through views or their perception of the world according to the nature of the concepts themselves and the categories cognitive agents use. In summary, conceptualizations become extractions of the domain knowledge and are specified by ontological categories, relations, and constraints or axioms. Categories are distinction or forms of classifications of the ways cognitive agents or actors see the world. The ontological refinement processes are explicit formalizations of the concept conditions and the concept details. Conceptualizations, through the use of relations and constraints or axioms,

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126 attempt to foto the nature of the concepts themselves and the categories that the cognitive agents use. Summary Our study addresses the understanding of interpretations of concepts in the construction domain that express explicit forms by transforming concepts into models, schemas, or conceptual models. It also suggests that expressions that embrace symbols cannot claim truth that characterizes an objective reality in the world. For example, the ontologies for information systems as knowledge representation structures assign variables in order to describe some phenomena in a domain. These structures cannot hold true characterizations. Similarly models cannot hold true characterizations; they state axiomatic relations under a set of assumptions. Our investigation also claims that assignation of variables are interpretations by the modeler of the observed entity. Our investigation also rejects the notion that these interpretations are tantamount to truth. Within the perspective of this investigation, this is a significant problem in communicating meanings of concepts in any domain, as well as modus operandi for the representation of these concepts. An example of this complexity is the need for human intervention for interoperability. The reconciliation problem is a manifestation of this significant communication problem. The current investigation advocates that there is no exact classification, axioms, or rules that define concepts for the construction community. The meaning of a fixed set of axioms conceptualizations contrarily to the dynamic nature of the observed physical world. The dynamic nature should be understood as evolutionary. Therefore, the conceptualization of construction concepts should follow the same evolutionary line. At the same time, meanings depend on the level of understanding of the interpreter. In addition, the meanings of what is represented are

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127 granularity for the interpretation of concepts. The resulting granularity indicates that the construction actor contrasts his or her intention for interpreting concepts with his or her own level of understanding of the real world. Consequently, there is a strong relation between by the intention of the actor. Therefore, interpretations are cognitively associated with a certain level of granularity by the agent.

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128 CHAPTER 6 NATURAL MODUS OPERANDI OF CONCEPTS An analysis of the natural forms of concept representations, typically employed in the construction community, gives a sense of perspective for their modus operandi. Our research studies the characterization and definition of concepts by the construction industry (see Chapter 3 for further details). The result reveals that the industry is aligned on a consensus on employing and developing standards, common conceptual frameworks, and ad-hoc schemes. These are conceptual structures and artificial formalizations, dictated by a small group of the construction community, and they are used to communicate and represent construction concepts with the purpose of interoperating. The sine qua non of the modus operandi of concepts in the construction domain is mainly cognitive. This cognitive function is considered natural and its dynamics do not involve artificial processes, such as the use of algorithms for efficiency. This modus operandi is used to formulate a framework for the characterization of concepts in the construction domain. This illustration contributes to the understanding of the use and nature of the representations employed in this domain. The purpose of this presentation is to clarify fundamentals of the relation between the representations and the construction project participants as cognitive agents. This relation is central to the understanding of problems of representations generated from multiple sources within interoperability. One paradigm example is the reconciliation problem for integrating, mapping or merging sources of information, which was introduced in Chapter 3. This analysis facilitates the introduction of the additional levels of knowledge representation proposed within this approach based on semantics, intentionality, and granularity. The examination of the modus operandi particularly addresses the perception, and interpretations of the representations and their components that hold concepts from the domain.

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129 The aligned with the methods to communicate construction concepts among the community. Sensory Experience and its Role on Concept Interpretation The perception and interpretations of modus operandi are in the simplest form a sensory experience and a cognitive process. The general aspects of the sensory experience and cognitive-y commonsensical perspective that ignores the fundamental nature of representations and the complexity of cognitive processes. The current analysis is supported by concepts derived from the areas of the philosophy of language and the cognitive sciences. The perception is an approximation of one or of a set of isolated physical entities in the world through the senses. It is the response of the mind to elemental uses of knowledge. The uses become more complex when the agents adjust their goals for perception. This process is internal or embodied, which entails that concept structures and linguistic structures are shaped by the peculiarities of our perceptual structures (Lakoff and Johnson 1999). Meanings or semantics are embodied and, consequently, entirely internal. The truth conditions of the isolated physical entities are provided by thought and perceived by the senses. The semantics are rendered by the interpretations performed on the conditions of the stimuli. The actor performs an internal representation of external stimuli through the set or inter-related concepts learned by experience. The internal representations resemble other representations that the actor already knows. This reasoning is performed by employing metaphors (Lakoff and Johnson 2003). The internal structure that forms a concept is complex and intricate and whenever the actor must work with such a concept, the actor interprets the concept in terms of an easier or simpler part of the whole concept (Minsky 1986). The easiest and simplest form is the primitive construct of that concept.

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130 The reasoning over the primitive construct is a form of the particular skeletal method of understanding about a concept that is central whenever the agents need to communicate a concept. The level of granularity of a concept representation is critical for interpretation, as was parts of that representation. The isolation allows mapping an internal, skeletal or primitive construct. It can be observed that if a representation describes a primitive form of a concept, it is explicitly expressed in the primitive form, and at the same time, it can be communicated easily. The actor in this case will barely need or not need to isolate the concept to perform internal mappings. Figure 6-1 illustrates an interpretation of a visual representation by two actors that belong to a construction project. Each one of the actors performs interpretations of the available explicit information of the drawings. They map their perception into an internal skeletal or primitive construct that constitutes a form that gives the semantics to complete the interpretation. The mapping is the reasoning mechanism that each agent uses. It can be noticed that a representation Figure 6-1

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131 accomplishes two functions: inference of thoughts for (1) interpretation and (2) communication. The the accurate level of granularity to generate a representation in order to communicate its meanings. Representations and Interpretations Representations attempt to describe an extension of a concept in the real world. The representations themselves are simple metaphors that give meaning to some concept. Concept representations are not merely elaborations of signs in the mind, but are extended to something physical, such as the context space, in order to be realized or instantiated (Emmeche 2004). This means that representations of concepts cannot fully describe the meaning of the concepts if the relations to the other concepts are not taken into account. These relations are termed contextual relations. Contextual relations the current concept interpretation, and to link such relation to other concepts. This line of characterization of the interpretation has roots in the semiotic tradition (Luger 2002). The contextual relations takes into account contextual relations in the consideration of a valid construction participainterpretation. Observational and Non-Observational Factors for Interpretations There are observational and non-observational factors that allow the observer to perform assertions for interpretations of representations. An example of an observational factor is the semantic relations that the observer is able to find in the details or in the situational conditions of a construction concept in order to apply a reasoning process. An example of a non-observational

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132 xperiences with a construction concept or its representation. Another non-find suitable semantic relationships when the interpretation is performed (Sowa 1999; Thagard details and situational conditions. This abstraction is a simple re-creation of the representation a representation of a construction process. Consequently, it is clear that not only observational factors but also non-observational factors affect the interpretation of the representations. A good balance of these two factors will aid in performing better interpretations. Interpretation as a Cognitive Process Interpretation is a cognitive process that involves mappings of the representations from several sources. Although a mapping of several sources is not essential when performing an interpretation, a mapping from more than two sources produces more certain assertions than those that are derived from only one source. In construction projects, mappings are critical in performing accurate assertions. As was previously mentioned, when the intension or the sufficiency of the set of properties, details, and conditions, that give and apply meaning to a concept are not enough to elaborate a correct interpretation, the construction participant is forced to find other sources of information that complement the set of properties of that concept. In other words, construction participants map various representations that aid them in the understanding of representations of construction concepts. Mappings are matches of abstractions of a construction concept that has several

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133 representations, or that is described by more than one representation. Figure 6-2 shows the mapping representations described within three layers: regulations, drawings, and document specifications. In Figure 6-2 the mappings are performed by an observer of any construction concept; for example, a constructidesigner (e.g. architect) and that is interpreted by an observer (e.g. contractor) by mapping the the local regulations about ladders (e.g. safety details). The mappings are not simple connections of concepts; they are links that find semantic relations among concept representations. The relations are not only found among the details, but also with situational conditions which help interpret the representations by examining states of affairs and context relations. For example, Figure 6-3 ext representation components of the construction documents. They map the visual representation (Wood Frame, Double Hung Figure 6-2. Mapping representations (layers) that describe the same concept.

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134 Figure 6-3. Relations between visual and text-based symbol representations. --addition to the visual representation symbol details (e.g. geometrical properties in the visual symbol such as frame size, or glass size) and details description of the text representation (e.g. silicon on glass-wood junctions), actors identify additional situational relations such as set on (e.g. set on a wall), or split by (e.g. split by internal and external environments). These mappings according to the intentions that they have with the representations. As the reader can infer from the above explanation, mappings or semantic relations include a reasoning process. This reasoning process will be illustrated in the next section. Reasoning on Interpretations Interpretation is a cognitive process that reifies a concept. These concepts are abstract universal notions, of an entity of a domain that serves to designate a category of entities, events or relations Construction participants find semantics of the concepts of their body of knowledge.

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135 The goal is to reify concepts on their extensions or possible instances the cognitive process, the actor maps observational representations, non-observational concepts (conextension of that concept. Figure 6-4 illustrates the relations of the abstractions among physical constructs, concepts, and representations in the popular Meaning triangle (Ogden and Richards 1989). In Figure 6-4 the image of the wood window is the physical construct, the cloud wood windowt-based representation and the picture of the wood window surrounded by the frame represents the visual representation. The meaning triangle shows the relations that help identify a concept in order to reify the construction concept. This is a simple way to describe semantic relations of the representations As was introduced in Chapter 1, the reasoning process for interpretation can be described by the following steps: Figure 6-4. The meaning triangle.

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136 identify the concepts of the observable source by finding details and conditions of the representation; perform concept abs map the abstractions to other observable sources which describe the concept but employ different representations; evaluate the mappings and assert the semantics of the concepts according to the Mappings of representations, which are separate representations that describe the same concept, rest on the purpose of the cognitive agent (refer to the mapping of text-base representation and visual representation example). These mappings attempt to reduce the risk of misinterpretations that can occur when an actor derives the meaning of a representation from only one source. Figure 6-5 illustrates the steps involved in a reasoning process: wi finds representations that contains the same referent in order to map those representations evaluates the mapping by finding semantics (e.g. only to a catalog). In summary, when an actor reifies a construction concept, he/she performs an interpretation of unprintable mental representations concerning a particular construction concept. At the same time, the representation can further be analyzed by its details and situational

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137 conditions. In fact, multiple representations that have the same referent can be mapped among them in order to find semantic relations. The purpose of this mapping or of these semantic links is to assert the original concept intention(s). For example, the visual and text concept representations are mapped and analyzed in order to obtain an interpretation of the representation actors use non-observational factors to interpret the concept such as experience and body of knowledge that they may possess of that construction concept. Concept Generation: A Translation The internal thoughts are correlated and translated to an external representation, at least in the primitive form. The process of translating a concept into a representation is called concept generation. Figure 6-6 shows the generation of a concept by an actor on a construction project and its communication to another actor. The assumption in Figure 6-6 is that the representation is the only means for sharing information between the actors. Figure 6-5. Proposed reasoning process for interpretations

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138 The actor correlates that is visually represented. Then, the actor translates these associations into the drawings, a visual representationconcept to other construction project actors. about a concrepresentations. The beliefs are not intended to create senses of ambiguity on the assertions, but to underline that any assertion does not convey truth or logical necessity. In its capacity, the virtue of the differences of the mental constructs from the other actor. Even if two actors perceive the same representation, as illustrated in Figure 6-6 the semantics of the representation for each actor is different. If two actors share the same concept, the role of the concept is not concept network (Rapaport 2002). In Figure 6-6 the resulting differences in the internal, conceptual roles are represented through the semantics differences, by color of the components of the mental constructs from concept. The semantics relationships are consigned and are part of the large network of the correspondence of the perceived phenomenon, i.e. entity, event, or relations, in the domain to the

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139 concept in the mind. In addition, this experience establishes the method of how semantics should be understood in order to give interpretations of concepts. The assertion action can be included into the interpretation action. Assertions are believes from the interpreters. The assertions cannot be taken for granted as truth. They are approximations that express the set descriptions that communicate meanings to the community. They reflect how the agent understands the concepts. Then, representations implies translated Figure 6-6 These ons with ambiguity senses. Any assertion does not granularity level or in the representation capacity. Figure 6-6. Generation and interpretation of the translated concept. Social, Context Character of the Concepts As the representations of concepts cannot be understood as literal, by virtue of the uniquetween any

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140 symbols or representations and its semantics, which fixes the meanings for a social network or for a community. The semantics of the representation cannot be fixed. The representation generated from other sources play a role that gives a social, context dynamic to the semantics of the representations. The semantics of the representation that is attempted to be communicated cannot be de-contextualized from the associations that involve social, human activities. This social role of a representation is analogous to the spirit of the idea of Wittgenstein (1973) that of the semantics of a word lies in its use. The semantics does not lie in fixed learned meanings for the future uses of a word. It can be noticed that the possible actors of a social network are not possible to a priori be defined in their totality. In consequence, the context, social dynamic of the semantics of a representation involves indetermination. This dynamic leads to an infinite level of granularity for defining meanings. New approaches should focus on the social, contextual role in the representation to slender the infinite definitions of meanings. Current representation in the construction industry ignores the contextual, social dynamics. To follow the spirit of this idea, this research suggests a new layer for the social role. This layer function of delivering and capturing the social interaction. As a preliminary exploration for this social, contextual dynamic, a framework for construction organizations is suggested by the author (Mutis et al. 2006). Following the spirit of this proposition, this research states that the meanings for communication are based on social conventions. The reprconsidering social practices along with social conventions. If the signs are not aligned with these conventions, the representations have solipsistic character. Actors must be involved in a network

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141 where a social interaction to communicate meanings takes place. The suggested layer for the social role should contain the elemental joints to the future counterpart interpreters. Concept Communication The social, contextual role of the concept embraces a mutual understanding of its notion for effective communication among a network. The mutual understanding is similar to finding a common ground or a same, combined situation. When communicating, actors within a network almost always fail, yet the actors almost always succeed, in explaining the paradox of communication (Rapaport 2003). As was explained, actors intend to communicate concepts through representations, either in natural or artificial language, or by employing signs. The role of representations is to serve as connectors for the actors in the network. Actors respond at the representations through their senses, and their responses depend on each particular cognitive agent. The experience at interpreting the signs and the accuracy or sharpness in their interpretation i Our research rejects the idea of having a literal meaning on concepts to succeed in communicating them, which is the basic tenet of enforcing standards within a network. There are only needed skeletal and primitive conventions. It can be noticed that the translated concept into a skeletal form in a representation is a belief in the simplest form or in a form with the fewest, possible constraints. This primitive form is further shared within a social context with the purpose of creating conventions. From here for successful communication, the level of sharpness representation. If the primitive form suffices to communicate the intention, then the sharpness of the communication is more adequate to represent the concept. The societal, contextual role for communication of the representations can be seen as analogous to the role of joint actions carried out by coordination and participation of actors in

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142 order to communicate in natural languages. In using languages to communicate, it is the joint action that emerges when speakers and listeners assemble actions such as communicative acts and signals in order to indicate anotheconcepts, it is the learning experience from each of the other actors that guarantees the assembled actions, allowing communication. In Figure 10-6 ao a visual representation to communicate it to other members of the community. In the example, a more developed primitive form is consigned within the representation. The product of this a particular aluminum constraint values such as the concept dimensions. If the representation as well as its conventionalities or its social usage are socially understood, the counterpart actor-interpreter should be able to recognize the representation. The visual representation showed as drawings hold semantics from the perspective of the actor who generates it. If this visual representation is launched to communicate its meaning, the counterpart should find a common ground or a same, combined situation to understand it. Although by nature, the learning of concepts is different for each one of the actors that participate in the action, the commonalties of the representation should suffice for understanding it. The identification of the concept takes place when the interpreter recognizes the set of signs, metaphors, and constraints thaluminum window

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143 to. Under this assumption if the other agent does not understand the set of signs, metaphors, and constraints, the translated representation has a solipsistic character. The meanings or semantics of representations are provided by thoughts, not by truth drawings of aluminium windowsconcept translation, not by truth conditions. The representations are skeletal forms of understandings and, in the basic form, are primitive metaphors. If there is only one source of the translated concept, the counterpart interpreter only has this representation to identify with certainty. However, the physical, perceived, material entity or qualia also influences the identification process. By nature, the material entity is the source of the stimuli. Some distinctions produced by the material entity can be identified by the interpreters, but others cannot. Thus, the translated concept cannot be conclusively known from its representation. Discussion Misinterpretations, errors, rework among other typical construction problems are the resulting, roadblocks that affect the effectiveness of sharing, exchanging, and integrating of information in construction projects. The effective communication of information is the goal during the modus operandi of the actors on the construction projects. Our research significantly advances the understanding of the role of the actors and of the concepts embedded within the representations. The nature and character of the forms of representations and the difference between symbol manipulation and semantic operations form the basis for the understanding of complex practical problems in establishing interoperability on construction projects. Our research explores the nature of signs and intentionality through a semiotic experience with the purpose of finding answers concerning the perception and interpretations of the representations that hold concepts from the domain. The approach emphasizes the relations among concept

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144 methods to communicate construction concepts among the community. Examples from the construction domain are used to illustrate the concepts and to show the promise of this approach in facilitating interoperability on construction projects.

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145 CHAPTER 7 A SEMIOTIC PROPOSTION This work quests for the understanding of the forms of representation in their prima naturae and in their prima character states. The objective is to comprehend the role of their eter, and the extent of their ability to capture the richness of the construction domain. A clear distinction has been made in Chapters 4-6 between (1) the nature of representations, (2) their semantics, and (3) the role of their interpreters. A close analysis of these elements has indicated a missed stratum where the semiotic experience is an approach that embraces these three suggested aspects. The semiotic experience studies the fundamentals of the features that are related to any forms of representations. This chapter approximates semiotics as an experience that illustrates the reasoning process from external representations and the role of intentionality in employing external representations. This experience inquires about the form of the correspondence of the perceived, entity, event, and relations, or, in other words, a correspondence of a phenomenon in the world with the concept in the construction particprovide direction to the method of how semantics aspects should be understood to give interpretations for concepts employed in the construction industry. This chapter extends semiotic analysis to a construction industry case. Semiotic Analysis The best way for explaining a semiotic analysis for representations is through examples derived from its corresponding theory. The principal purpose is to set up a framework for the nature of the interpretation of concepts and, for the purposes of this research a framework for

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146 interpreting the nature of the construction domain concept representations. Accordingly the y: independence, relative, and mediating. Peirce was a logician who challenged the tradition of understanding thoughts not as ideas but as signs. The signs are external to the agent, who is responsible for the thoughts and actions of an individual to which they are ascribed, and they do not have meaning unless interpreted by a subsequent thought. Signs, under the semiotic experience, are representations that contain meanings and purposes, which are prescribed by independence, relative, and mediating. The representations take the form of a visual representation, of a set of markers that describe a formal language, and of markers that are used to represent natural language, among other possible representations, such as a collection of hexadecimal numbers. In this analysis, the language that previously was used to describe symbols is replaced by the terms used in semiotics for signs. This semiotic analysis is an examination of the compromise between the meanings of a representation per se and the concept associated with the understanding of such representation. The semiotic analysis gives a perspective from the nature of understanding of the concept from firstness, secondness, and thirdness Firstness is the conception of being or existing independent of anything else. Secondness is the conception o being relative to, the conception of reaction with, something else. Thirdness is the conception of mediation, whereby a first and a second are to Material, Relational, and Formal aspects of the signs organized within the trichotomies. The first and Material trichotomy consists of Qualisign, Sinsign, Legisign; the second trichotomy

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147 consists of Icon, Index, and Symbol, and the third includes the Rheme, Dicent Sign, and Argument. Qualisign Qualisign is a sensory experience originated due to stimuli of some material on the actsenses. It has not reference or any additional indication to identify a meaning on it, but it has a character of being qualiaqualia Figure 71 shows a representation, which in this case should be perceived by visual senses. Any actor can perceive it through visual stimuli. The source of this stimulus contrastrepresentation is a sensory experience. Qualisign is simply the sensory experience and, as an experience itself, it is independent of the source. It has the same quality as an appearance. Qualisign firstness category, which is independent of anything else. In the example, the visual-representation contrasts are themselves independent from the source. They could have originated from printed drawings on paper, or from a computer screen. When the agent perceives the representation, here by visually contrasting dark and light, a set of relationships originating from what is perceived are internally created within the agents mind. Figure 7-1

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148 Sinsign This category is named material indexicality and relates qualisign, or the perception due to stimuli, to an internal concept that resembles an entity or an event. Sinsign is the result of the recognition of the simple material quality or qualisign. The recognition assigns meaning or semantics to the qualisign. The assignment of relations to the perceptual experience is the identification of semantics. According to this tradition, it takes place in secondness. The fact that sinsign has been identified implies the recognition of a particular mental recognized by perception and it is related to a specific source that has previously been understood by experience. Figure 7-2 shows a section of drawings that are chunks of traces of ink on paper and are recognized as a source that allows assigning meaning to the traces of ink on paper as drawings. In other words, this recognition identifies the concept drawings by visual perception. In the Figure 7-2 example, the recognition of this visual perception implies a match a priori, learned, piece of drawings concept. However, the recognition of pieces of drawings does not imply the definition of the convention or a consensual semantics of the sinsign. Figure 7-2. Sinsign.

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149 Legisign main feature is the essential character of obeying a social consensus about the semantics of a particular concept. Legisign has a force of convention or a social understanding of the sort of recognized sinsigns. Legisign is under a mediation category, which indicates that the not add additional semantics to the interpreted sign. Legisign identifies the convention or social understanding of such a particular concept. If the representations correspond to legisign, the actor's reasoning about the meaning of the perceptions identifies that the representations or signs have relations to the learned and socially agreed upon concept, and performs assertions about these relations. These relations are inferences from previously learned The lack of social consensus about a concept, an agreement, or an enforced legislation negates the possibility of considering a representation as legisign. The meaning of a concept is shared in commonality within a network. The understanding of the signs is based on a common set of constructs that constitute a concept. The interpretation of sinsigns can be a positive reaction towards an association of a previous, social consensus. If this reaction is performed, the interpreted sign are consider legisigns. In the example, the visual distinctions of a group of parallel and perpendicular lines grouped in a certain layout infer a form of a window in the Figure 7-3 the distinction implies the identification of an arrangemarrangementcorresponds to sinsign, which corresponds to the schema shown in Figure 7-3 (a). The result of arrangement that legisigna priori and corresponds to a socially agreed upon concept that is supposed to have a definition that stands for: a physical device that isolates two environments by keeping a visual contact between them. The convention of the window

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150 definition should resemble multiple a priori mental constructs that meet the description of this definition. Figure 7-3 (b) illustrates the hypothetical internal representations for a certain agent that stands for the concept that resembles the a priori learned concept of windows. (a) Arrangements of signs in a schema (b) Hypotetical internal representations. Figure 7-3. Legisign. Icon This category is part of the relational trichotomy, which is determined between a representation and an entity. A sign is a representation when it is recognized per se as a representation for the cognitive agent. To define an icon is to define a resemblance to a concept representation that resembles a specific entity. The distinctions The cognitive agent interprets it by establishing relations or finding semantics. The representation is not interpreted as qualia or as pure material, but the nature of the material has the quality to be recognized as a representation by the actor. The relations that the actor identifies are apprehensions based on similarity. The similarity is a property of the perceived phenomena and it is employed to find relations to the mental construct of the actor. Similarity does not

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151 designate the characteristics of a concept. It establishes general indications of what a representation of a concept refers to. An icon through the effect of the similarity distinctions does not implicate true existence of that entity. An icon makes clear the resemblances to a concept that has been a priori elaborated. The primary further semantics to the icon. The similarity is a contrasting reasoning that formulates indication to a concept. Figure 7-4 (a) shows an example of a representation that it is visual. The form of the representation resembles a concept that the actor is already familiarized with and which is depicted in Figure 7-4 (b). This a priori, primary, distinction is derived from similarity contrasts, resemble the habitat of insects or the design of a marine, emergency flag. (a) A visual representation Figure 7-4. Icons. Index The constituents of index are markers or icons whose semantics exclusively indicate a relation to a specific concept. An index loses its semantics if it does not react upon a concept, i.e declares is to afford the existence of a concept. An interpretation of the concept can be guided by the index, although the index may

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152 not be necessary for its interpretation. The index serves to make connections to a concept in the indication to the concept does not imply the distinction of the Indexes provide nothing other than the indexical relation. The nature of the index can be of any type such as a physical or material entity, relations or events, or even an imaginary thought. A cognitive agent does not need a physical or material connection in order to get an indexical serves to identify a concept on the photograph and it is not physically connected. In the same way, a set of markers that form the student ID number, which possesses semantics and constitutes a social concept for identification purposes, provides for indexical functions and is not physically connected. Physical connection means a direct contact that produces a stimulus to ation with a concept, index is part of the relational trichotomy that establishes a relation between a sign and an entity. The connection, expressed through the indexical relation, is independent of any similarity relation to the entity. The indexical function is an internal inference that generates distinctions to a particular concept Index mind. If an index is learned by experience and it is identified through social conventions or network. An index that possesses a social role has non-solipsistic character and its nature is not imaginary. Although, Peirce suggested that indexes point to objects or facts, this study treats objects or facts as concepts that actors identify by stimuli. The concepts must be commonly recognized by social actors, i.e they are common, shared concepts. This particular, social, inclusion feature of

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153 index implies a purpose of sharing concepts among the community. This purpose, then, should make any index, by virtue of its semantics, be an artificial signal to point to a concept. The pointed or mapped concept, by virtue of the indexical relation, must be the same, independently from which actor performs the interpretation. A photograph is an index that can be read by any other actor, and the indexical relation always maps to the photographed entity. Under this social dimension, indexes map to a unique entity and they serve as an identification of that entity. However it is important to note that indexes that, under a social consensus, afford the indexical relation. The set of markers that compose a social security number can indicate identity or ownership of a boat. Index just points to a concept and social conventions convey the semantics of what is pointed at. Within the social, convention role, index has the character of being dependent on the mapped object although it is an artificial representation that can exist by itself. The reasoning process consists of performing inferences with the purpose of finding matching to the identified entity. The social security number is an index that serves as a means of matching other sets of numbers in a knowledge base of social security numbers. The inference for a search of matches of social security numbers is based on similarity relations. In Figure 7-5 the set of markers index consists of performing searches for matches to other representations that contain the set of knowledge base can be construction specifications, schedules or any documents that contains the representation, index

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154 the same way, the inference that acts on other sets of markers, such as the social-security-number index, searches for matches that are based on the similarity relation. Figure 7-5. Index. Symbol Symbols are the result of a rule or association for a sign by virtue of the experience or of the learning ability of the cognitive agent. This rule governs the representation of signs or indexes. Symbols are the outcomes of the learning process that has shaped the concept for a particular meaning. The actor establishes the semantics of a concept by learning. When an actor recognizes a symbol, it is simply associated to a concept, i.e. the actor understands the semantics of that symbol with no additional inferences or aids from other sources for its comprehension. respunderstanding addition of semantics to other representations and rules, such as syntax rules, can be a very complex process. This semantics addition should respond to any perceived sign during its interpretation. This suggests that there exists symbols only under interpretation, and that their

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155 symbol interpretation is the result of a distinction of an a priori, learned conce Figure 7-6 illustrates a symbol on a computer screen. The symbol is an instance of some printed drawings. The actor associates the perceived signs with the concept drawings. At the same time, the actor identifies further semantics in each one of the distinctions performed and perceived from the provided signs on the computer screen. The role of the computer screen is to serve as a means of replicating the signs that represent the computer screen mediates the representation of the concept drawings through the symbols on the screen. Clearly, the symbols are presented in visual representation form. The agent can find additional associations for additional semantics during the resulting reasoning concerning the symbols on the computer screen in Figure 7-6. The additional associations are mediated through the signs shown on the screen. The screen mediates for additional associations or additional semantics in order to be distinguished by the actor. The lines on the top and the left side of the scheme on the computer screen are signs that add semantics to this visual scheme. The actor might read these signs as symbols for defining and delineating mediated concept. Clearly, the screen serves as a device that mediates for a representation, which in this case is a visual representation, screen afford information that the actor has a priori learned and defined by experience. The employing a mechanism of reasoning such as additional inferences or the use of rules or

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156 propositions. A cognitive agent elaborates a mental image from the symbol that mediates a representation of an entity. The entity, in this case, is represented in the drawings. Figure 7-6 on a computer screen. Rheme This category represents a set of markers that afford a proposition or relation to some concept. Rheme are the makers that have been identified by the actor as signs that have a form of representation and that hold information of a concept. Rheme essentially represents the signs that belong to a formal language and that can be either natural or artificial. For example, the word -making device or a percussion instrument that has a form of open-ended hollow drum and that perform the perception of the markers have learned the concept and they imply a consensus or a social concept description, which is part of the features of a formal language. Rhemethe quality of quilisign and they can be identified as signs or markers; they can be recognized as representations. The resulting identification of the primary information of the markers is their recognition as a representation. Rheme affords some

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157 information that holds meaning to the cognitive agent. The information does not have any additional indication than the possible identification of a concept. The series of markers that resembles the role, the form, and the properties of a window, which is made of aluminum material. This example takes an ontological account by naming properties and forms, with the purpose of explaining the possible concept characterization that an actor might possess. Then, example. Although Peirce (Peirce 1991) defines Rheme as terms that have the ability to conserve a blank in a set of a proposition, Rhdefinition can be extended to signs to be used in formal languages in general. Dicent Sign Dicent sign, also expressed as dicisign or dicent, represents a formal category of indici. Dicent sign is the assertion of a concept, which, in turn, is the result of identifying the semantics of the concept. The actor reasons on the perceived sign, shapes its semantic, and expresses an assertion. Dicent sign can be interpreted as true or false, but this interpretation is embodied. Then a truth or false character rests on the semantics that are refined through the distinctions made on the sets of markers that compile the representation and constitute dicent sign have the capability of being true or false. The result is an assertion produced when the actor assigns semantics. Dicent sign affords grounds for interpretation and its purpose is to perform an assertion about what is perceived by the actor. Dicent sign can adopt indexation signs due to its nature. An example of dicent sign is as s of

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158 words that in turn are a set of markers that afford information and that assert the existence of an entity or event. In the example, the cognitive agent, who perceives the set of markers that form the phrase, might take for granted the truth or might reject the assertion. This means that the phrase still affords grounds for interpretation. Argument Argument is a sign that involves formality in the interpretation of a dicent sign and it falls under the formal mediation category. It is the reaction to the perception of a learned concept without further reasoning for finding additional semantics on the perceived sign. Argument has the form of law to the actor and does not give grounds for interpretations other than that intended. Although argument suggests an intended interpretation, the cognitive agent processes it as a beliefmurepresent a constraint in the type of metal of a window. The interpreter or cognitive agent might vary the interpretation according to his or her belief concerning the meaning of aluminum metal. The mediation level of argument represents a further result than the addition of semantics to the signs. The derived result of the sign perception and interpretation reflects intentionality. With argument, the intentionality reaches a level of formality, which does not require additional reasoning for assigning semantics for the actor. Clearly, the basic reasoning of argument consists of the identification that is learned and refined a priory. The basic argument for interpretation is regarded as previous knowledge. Summary The purpose of introducing the semiotics theory through this investigation is to analyze the role of the construction-

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159 includes aspects ointerpretation. Current efforts that quest for efficiency in interoperability fail to notice the dynamic of signs and the use of natural language within any activities on construction projects. Errors, misinterpretations, and rework with the employed representations in their modus operandi are common problems found during current construction practices. This analysis suggest an opportunity to understand the nature of the multiple practical problems with the representation of concepts in interoperability. Interpretations involve the observation and distinction of syntactically defined symbolic notations and of other visual representation forms. These notations are deliberately organized to define concepts. The understanding and characterization of concepts into symbols and other forms of representations can be addressed in the semiotic framework. From this framework, the analysis of the systematic, common forms of symbols questions the current employed forms of representation in their ability to express meanings in interoperability. The following example illustrates how the semiotics experience is part of any interoperability activity in the construction industry when the relationship between and actor and a representation takes place, as well as the implications. From the aforementioned semiotic framework, consider the following interoperability situation. Suppose that one actor shares information with other actor in a construction project. One actor generates the information and the other receives it. They do not previously arrange meetings, nor do they work in collaboration for generating the information. The recipient obtains the information in tables as well as their corresponding meta-model which it is shown in Figure 7-7

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160 The meta-model and the tables are forms of representation that are intended and structured to d-model. From the semiotics standpoint, the meta-model satisfies the definition of sinsign, since it represents the recognition of the internal understanding of the diagram as a meta-model as well as the syntax of meaning of the words. However, the interpreter does not recognize the meaning of the relationships of these words within the meta-model. The metalevel does not have the character of a symbol for the interpreter. Thus, the metalevel does not embrace a mediation stratum where the social understanding of the arrangement of the shown entities has a social meaning. Therefore, in order to determine semantics on the metalevel, the interpreter will demand additional information from the source, which is an activity that requires multiple resources. Figure 7-7. Meta-level representation. Sharing concepts among the construction industry community is limited to the captured content in the representations producing errors and misinterpretations in these operations. A further analysis of the relationship between concepts and their associations to a more primitive sense of signs as well as a strategy needs to be considered for advancing semantics in

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161 interoperability. The analysis should include the relationship between concepts and the systematic, common forms of symbols that can be embedded in models or in computers, as well as the role of the agents with the representations of concepts and the domain.

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162 CHAPTER 8 CONCEPTUAL ROLE SEMANTICS FOR INTERPRETATION Currently the construction industry interoperates by transforming concepts into models, schemas, or conceptual models. An interoperating approach addresses efforts on mapping, harmonizing, integrating, and aligning, among other methods. However, they do not direct the fundamental problem of understanding the information that is generated by different sources. Evidence of this problem in the construction industry is found in the difference between the semantics contained in conceptual models such as standards (Mutis et al. 2005). The manifestation of this divergence takes place when actors perceive representations generated from different sources. This situation is found in interpreting representations of concepts that were generated with the purpose of communicating them. Actors in this domain continuously generate representations to communicate concepts, which are further interpreted and perceived by other actors within the community. This investigation explores valid reasons for the divergence of The purpose of this chapter is to introduce a concept that helps advance the understanding of the nature of the current methods to represent concepts within the construction industry in order to identify the deficiencies that inhibit sharing of information among actors. These deficiencies cause difficulty in creating efficient methods of exchanging, sharing, transferring, and integrating information from distributed sources. Conceptual Role Semantics and the External World Truth concerning a description of a phenomenon in the world is not fully established by observation due to the different cognitive levels of understanding. The levels depend on the exposition for interpretation of the phenomenon and the experience of the cognitive agent. The concepts that a society manages or that a community understands are the common and shared

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163 situations with which they have been involved. The meanings or semantics of concepts are absorbed by the daily experience and by the learning processes that shape the concepts in the mind. Thus explicit and direct correspondences from one concept to another concept, and then in turn, from concepts to the world, cannot possibly be established with certainty. semantics in order to assert an understanding concerning its form. The internal role of a form of representation is recognized and reasoned. Concepts are abstract, mental structures of an entity, events, or relations of a domain and the internal role of these abstract, mental structures for conclusive semantics is called conceptual role semantics. Conceptual role semantics is a framework rather than a theory concerning the roles of representations, their reasoning of thoughts or caused inferences, and their contribution of cognitive abstractions to meanings (Block 2006). Although theories of roles of meanings go back as far as Kant (Whiting 2006), this framework has recently been scrutinized within the area of philosophy of the mind and has been extended in linguistics, especially in formulating theories of meanings processed by natural language expressions. Cognitive science, computer sciences, and other sciences broaden the framework of conceptual role semantics in seeking the semantics of the use the actors put on such representations. In philosophy and linguistics, the famous dictum influenced major well known advocates of theories, such as Wilfred meaning distinguished the use of inference that discriminates between various meanings such as:

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164 conceptual role semantic is on meaning as translation (Rapaport 2003). Theories of truth and reference can be seen as contenders to conceptual role semantics in defining the source of meanings for any symbols, signs, or syntactic systems. Referents are supposed to indicate truth in the correspondence between the symbol and the world. The theory of reference stems from the work of Gottlob Frege. Fregean theory considers senses as referents that link a symbol in the proposition to the world correctly. Correspondence is a metaphysical notion that claims that the description of the world is truth by the existence of some observation with corresponding elements and a similar structure; metaphysics is concerned with the explanation of the nature of the world (Appiah 2003). However, conceptual role semantics put the cognitive role as central to defining meaning instead of a reference in the external world. Understanding a meaning consists of having symbols with relevant conceptual roles and not having an understanding of truth conditions. Conceptual role semantics holds that meaning and content of syntactic forms and other forms of representations arise from and are explained by the role of these syntactic and of other forms of representation (Greenberg and Harman 2006). Conceptual role semantic theories explain how the roles determine the meaning and content in thinking or internal thought. The use of forms of representation is the means for reasoning. The use of these forms includes perceptual representation, recognition of implications, labeling, categorization, theorizing, planning, and control of action (Greenberg and Harman aluminium windowmade of aluminiumied as a metal window element. Conceptual role semantics suggest the way in which the label is semantically distinguished from

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165 metal-aluminium windowsconsists of the way they were assigned to be used within the external world. The content of the aluminium windowopenings category or as in the metals additional functional aspects, although not essential or unique, are relevant to the use of the aluminium window Harman brought forward the account of whether an external or referential or truth-conditional theory plays a role, or if the conceptual role semantic framework embraces a theory that is internally based for recognizing semantics. Thus, meanings of natural language expressions are determined by the thoughts, with which the expression is correlated, and not by true conditions. The contents of the expressions are determined by their functional role in the conceptual role semantic framework, the meaning of syntactic expressions is determined by the role of the conceptual scheme of the thoughts. The other words, the symbolic expressions play a functional role in thoughts for meaning or content. An expression is perceived, internally processed, and expressed through an action. According to use the expression. Representation Forms and Significance of Conceptual Role Semantics role semantics is extended to other forms of representations used in the construction domain. The possible forms of representations are not listed in this study, but their forms of expressions such as visual, syntactic, or formal are recognized as expressions of construction concepts. The characterization of the concept notion involves the description of abstract, mental structures, of entities, of events, or of relationships

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166 from a domain performed by an actor as cognitive agent in the construction domain. The description is the translation of the concept into syntactic or natural languages, visual representations, or formal structures such as models with the purpose of sharing or communicating the concepts to other actors of the construction community. As an example consider Figure 8-1 which shows a visual form and a syntactic form of representation respectively. One can notice that construction project participants continually employ these types of forms. The act of describing concepts into some form of representation does not guarantee the understanding by other members of the community of what is described. The choice of a form or representation does not guarantee the understanding of the meaning or content of the representation. Current forms of representations implicate different kinds of problems primarily influenced by the purposes and the uses in the external world or environment. No form of representation can be deemed the right choice to represent concepts. A syntactic form of representation does not guarantee the understanding of the expression by other actors in the community. A visual form of representation does not guarantee the assimilation of the indexical contents by other actors in the domain. Deficiencies of Forms of Representation The choice of representing a concept in a model through formal logic involves the lack of a subset of logic expressions to determine meaning of what is intended (Sowa 1999), and for what it is used. In the construction industry for example, the choice of representing concepts through standards and taxonomies implicates different choices to categorize concepts, and different forms to name the same concepts. New forms of representations such as ontologies in the construction industry suffer the same type of problems, especially within different approaches for axiomatization.

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167 This choice of employing models, which are symbolic approaches for characterizing concepts, can be seen as complementarily driven for some purposes, but for other purposes, the same characterization can be seen as contradictory. An ontology that describes the sets of pipes and water pumps for buildings can be complemented as much as possible with more axiomatization. The result might be more accurate for modeling pipes in buildings for the hydraulic engineering, but might be seen contradictory if the electrical engineer attempts to reconcile his model with the hydraulics ontology on the specifications on electrical, local regulations. (a) Visual. ( b) Syntactic Figure 8-1. Visual and syntactic forms of representation. investigation attempts to direct attention toward the process of interpreting a concept from a provides the framework. The functionalist approach within the interpretations of concepts scrutinizes the role that is played in throles give meaning to the interpreted concept. The central issue is to illustrate that the forms of

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168 representation do not guarantee the communication of the semantics of the attempted interpretation. Examples with Some Forms of Representations In interpreting forms of representation, conceptual role semantics plausibly set the account on the element that plays the role of finding semantics under the psychology of an interpreter or actor. In order to clarify the significance of the framework of conceptual role semantics within the construction industry, consider the following examples. The examples illustrate the conceptual role semantic plausibility. Although the examples are obvious cases, the purpose is to employs a visual and a syntactic representation, while the second example employs a symbolic, formal representation. Under the view of conceptual role semantics, the later shows a case of divergence on finding relationships by similarity as the main form of reasoning for finding semantics among representations. Visual and Syntactic Forms Example Conceptual role semantics should indicate how actors react against the perceived representation. An actor finds the content and semantics of a concept in order to assert an interpretation from representations generated from other sources. This is the case of many operations and processes in the construction industry. Actors frequently perceive visual representations such as sketches, drawings, schedules, etc., and react by asserting interpretations. Consider, then, the case of Figure 8-2 (a) where a visual representation is to be interpreted by an

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169 they are only shown here for illustration purposes. In this research, other forms of reasoning are also considered as valid, such as metaphorical reasoning (Lakoff and Johnson 2003). It is central to emphasize that the representations under the conceptual role semantics are means for reasoning for the interpreters or actors. Thus, the relations from a representation such as syntactic markers or symbols serve and aid the thinking to establish semantic relations. In the case of the visual representation of Figure 8-2 the interpreter searches for these relations through resemblances that are made by setting similarity relations. The actor finds resemblances of the visual representation or sign shown in their body of knowledge by employing similarities. This reasoning includes the uses of this sign. The findings are the semantics relations that must identified relations are apprehensions based on similarity. The similarity is a property of the perceived phenomena and it is employed to find relations to the mental construct of the actor. Similarity does not designate the characteristics of a concept. It establishes general indications of what a representation of a concept refers to. The designation of the characteristics of a concept suggests its content, which must conform to its role. The reasoning illustrated in Figure 8-2 (a) shows that the relations for semantics were not found. The sign as visual representation is not recognized for performing interpretation. This is the case that the actor does not have a relevant conceptual role for distinguishing semantics. In continuing with this example, the actor needs to find additional sources of information to aid finding the semantics relation. For this purpose consider Figure 8-2 (b), where the form of representation is syntactic. In the left part of Figure 8-2 (b), there is a set of markers that, by some method, the actor reasons like the ones that contain and indicate the semantic content of the sign of Figure 8-2 (b). For clarity, the set of makers is a syntactic form that for a more primitive,

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170 cognitive expression are signs. The markers of Figure 8-2 (b) conform to a natural language expression that states the semantics of the visual representation. The resulting path for reasoning concerning the representations of Figure 8-2 (a) and (b), is the one played by the semantic role. This path for reasoning implies the description of how to use these representations. The reasoning should indicate the content of the concept. The uses are features learned a priori by the actor. It can be noticed from the example that the designation of the characteristics of a concept or content anticipates the reaction or the reasoning of the actor. This designation should make the actor produce accurate assertions of the expected results. (a) Visual (signs or symbols) (b) Syntactic or text Figure 8-2. Reasoning forms of representation. Formal Form Example Consider a taxonomical form of representing concepts, which can be employed for certain actives, such as estimating or planning. Under the conceptual role semantic view, the assumption is that the actors translate into representations their knowledge that corresponds to certain this example, these thoughts are formally represented as a formal form.

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171 The resulting concepts represented by this form of representation must bear some relationship to properties, objects, or situations in the external world by virtue of that domain nature, in this case, construction industry concepts. These relationships do not imply correspondences of the concept to the physical world as true conditions. The relationships are from common set of properties, objects, or situations to that are shared and, in turn, perceived by a group of actors, such as a construction industry network. The resulted representation is not grounded to the external world; instead, it is the outcome of the translation to a formal form from For clarity, a taxonomical form breaks down a particular area of knowledge that shares certain features by classifying it into categories or items. The relationships between the items have automatic inheritance features, which can be interpreted as free path for inferences among the related items. The resulting items from the breakdown are actorassertions generated from this form of representation. According to the selected features of the knowledge domain, a criterion is used to evaluate the multiple sorts of properties of functional aspects, among others, in order to assert the items and relationships for building the taxonomy. Thus, this taxonomical form can represent objects, properties, relations, situations etc., and the represented forms are the nodes that shape the taxonomical structure. Figure 8-2 (a) and (b), shows two sections from two different taxonomies, which are formal forms of representation. The sections shown in the example of Figure 8-2 are parts of two taxonomies that characterize elements of hydraulic components used in buildings. The assumption for this example is that the sources from two different sources or actors translate their thoughts or knowledge concerning the hydraulic components into representations according rion. Under the view, the judgment that aids the

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172 breaking down process into classification, should take into account the role semantics. The role enables these items to relate and constructs a relationship between them. For example, suppose that an actor wants to relate two concepts from these two sections of the taxonomies. This can be the case for any operation where an actor needs to share information concerning building components with another construction project participant. The actor, who generated the taxonomy in Figure 8-3 (b), needs to share information with the other participant who elaborated the taxonomy of Figure 8-3 (a) by querying information from the taxonomy of Figure 8-3 (a). For this purpose, the actor accesses the taxonomy of the other participant by some method. As the main form of reasoning for finding their semantics, construction participants base their reasoning on contrasting the similarities of the items, which represent the concepts of hydraulic components used in buildings. As shown in Figure 8-3 finding similarities is possible through contrasting syntactic expressions with the purpose of establishing syntactic relations among the compared items. However, if a syntactic relation is established, it does not give consistent results on equating the semantics of the compared items. The semantics of the represented concepts from the taxonomy structure cannot be equated, they can be associated. The roles of each one of the structures for the compared items differ. The semantics is given by the role that the compared item plays in the -3, the actor contrasts the form of representations, expressed as a similarity relation. Contrasting is performed between node 9 of Figure 8-3 Figure 8-3 (b) whose

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173 (a) Taxonomy with syntactic content (b) Taxonomy with syntactic content Figure 8-3. Example of formal forms of representations. Figure 8-3 (b). The content of node 9 of Figure 8-3 (a) has a conceptual role in the system of Figure 8-3 (b). Note that if the correspondence between of node 9, in Figure 8-3 Figure 8-3 (b). It consists Figure 8-3 (b), and it must describe the semantic role of that system. There is no implication that two nodes similarly marked have the same semantics. The syntactic forms are not used to name them as similar. Under conceptual role semantics, example, if a correspondence is made between the content of Figure 8-3 (a) and (b) respectively, the correspondence conveys information about the semantic role of node 10, but the semantics has to be given in terms of the role it plays within the language games, the correspondence should be given in terms of position and move.

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174 For further illustration of the plausibility of conceptual role semantics within formal forms of representation, consider other highlighted components or nodes in Figure 8-3 Under conceptual role semantics, a consistent result on the semantic of a representation is definable, if the set of the terms are taking into consideration. There is not a consistent semantic definition if the terms or components of the representation are considered in isolation. The role of using the components of the representation is not clearly defined if the set is not considered. In Figure 8-3 the semantics content of node 9 of Figure 8-3 Figure 8-3 (b), 6 and 9 play in Figure 8-3 Figure 8-3 Figure 8-3 Figure 8-3 (b)). The definition of the semantics of the shown set of nodes has to be taken into consideration for understanding their functional uses. Summary Conceptual role semantics open new perspectives to understand the modus operandi of sharing and communicating concepts in the construction industry. This research rejects the idea of having a literal meaning for concepts in order to succeed in communicating them, which is the basic tenet of enforcing standards within the construction community. The meanings or semantics of representations are provided by thoughts, not by truth conditions. Conceptual role semantics serve as the framework to find semantics based on the role and the concept of the forms of representation used.

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175 CHAPTER 9 A FRAMEWORK FOR ANALYSIS OF CONSTRUCTION CONCEPT Analysis of Construction Concepts and a Methodology for Aiding Their Interpretations In this research, a conceptual framework for interpretation of construction concepts has been generated from the analysis of the (1) forms of representation of construction concepts, the (2) the modus operandi of the representations and of the concepts, the (3) the proposed disjunctive of the modeling paradigm, the (4) the granularity and its relevance for interpretation, the (5) the analysis of the semiotic framework, and (6) the inclusion of the role concepts for semantic interpretation. The framework is presented in this chapter. This conceptual framework articulates the theoretical propositions that this investigation advocates. The purpose is to develop a methodology that supports a novel way for interoperating semantically within the interpretation step. The understanding of the role of semantics through representations of construction concepts contributes to the illustration of the semantic interoperation. The framework is a mechanism that articulates this understanding through the propositions stated in the previous chapters. The framework explains how the articulation of the theory propositions takes place. The conceptual framework has the following components (1) knowledge acquisition, (2) knowledge organization, and (3) querying. One of the major differences of these components is that the actors who participate or use the framework do not necessarily work in each component. The actors do not participate in each component or their roles in each component are different. Within the knowledge acquisition component domain experts who can essentially perform interpretation of the domain concepts are involved. Other actors participate in the knowledge organization component by using the resulting product from the knowledge acquisition one. Finally, the users are actors in a construction product that query the concepts that have been

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176 organized. The users are the direct actors who participate in this component. Figure 91 illustrates the dynamic of the different actors that intervene in the framework. Figure 9-1. Intervening actors and subsequent components of the conceptual framework. Knowledge acquisition is a methodology employed to capture domain concepts from experts. It explains the systematic procedure for analysis of construction concepts in a formal representation, named conceptualization. For the knowledge acquisition component, a scheme is formulated for conceptualizing a phenomenon or an activity, a process, a resource, or an actor that intervenes in an interoperability activity in a construction project. The scheme articulates the theory that connects the relationships of the phenomenon defined in the theoretical propositions. For example, the characterization of concepts can be articulated by employing a scheme through the influence of situations and of contexts in representing them,

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177 role, as well as the boundaries of sufficiency and deficiency. The scheme describes the relationships of contexts and of situations for interpreting a social, domain concept. The knowledge organization component stipulates the method used for storing the information which has the ability to provide semantic associations of concepts. The organization can be specified through a knowledge representation structure named in this research as This knowledge base has the ability to store and to provide the semantic associations of the concepts. It semantically organizes concepts to facilitate the storing and retrieving queries about a concept in construction. The mechanism used as a knowledge structure is the ontology for computer systems. The querying component illustrates the competency of the approach for aiding the framework users in interpreting a concept. The queries are elaborated in a GUI (Graphical User Interface) for a clear understanding of the dynamics between the knowledge-bases, the interpreter and a concept. The interface facilitates the comprehension of the components of the proposed, semantic interpreter tool. The explanation and description of the components of this framework is the objective of this chapter. In the first segment of this chapter, the mechanism for characterizing concepts and the scheme is illustrated; the second segment shows the approach for knowledge organization, and the third, the querying method of information. Knowledge Acquisition The mechanism for acquiring knowledge consists of translating a concept that is represented in a human readable form into other knowledge representation form by using a judgment and the input of an expert. Thus, observable elements and non-observable elements are included in the translation. The main reason to develop other knowledge representation forms is to facilitate its manipulation, storage, and querying through the use of computer systems. This

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178 knowledge representation form is expressed as semantic networks. A semantic network is a declarative graphic notation for representing knowledge in patterns of interconnected nodes and arcs, and for using reasoning on the representation (Sowa 2006). These semantic networks can further be transformed into a logic based language for computer implementations. The translation is performed through interpretation of the observed representations. The observable elements of the translation correspond to what the interpreter perceives in the human readable form. The reader can notice that the human readable forms correspond to the quality of material and to the character of symbol from the semiotic framework. Also the reader can notice that what the interpreter is able to observe in the representation corresponds to the relevant elements or details of the concept. These elements are the explicit information located within the boundary of sufficiency in order to be interpreted by that particular observer. The non-observable elements correspond to the added details, categories, properties, and semantic relationship to informal form. The resulting non-observable elements are generated from the interpretation of the observed or perceived representation. Chapter 6, which analyzes the modus operandi of representation of construction concepts, explores the procedure for the reasoning on the representations. The inclusion of all possible domain features and constraints in a knowledge representation form are required to conclude the knowledge acquisition process. A description of what is only wood interior doororder to be represented into other knowledge representation form, is an example of a translation of an observed representation. The inclusion in the formal form of additional domain features such as project name, location, environmental conditions, among others, are examples of non-observable elements and, therefore, there are not included in the visual representation. In this

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179 example, the purpose of topologies in construction drawings is to represent the concept visually as well as its associated details. The details that are usually indicated in the visual representations are the dimensions in the space domain. The dimension is an observable constrain feature that can be included in the other form of representation. However, the translation process from an observable representation to a knowledge representation form is complex. The mechanism for knowledge acquisition should be harmonized to the theoretical propositions of this research. It should be consistent and homogeneous for different interpreters. For this purpose, a scheme that serves as a mechanism and as a theory articulator is proposed. This scheme helps analyze consistently and homogenously any concept that it is perceived by the interpreter. The scheme is based on six basic questions which is similar to the analysis of language whatwherehowwhywheninterpreter to organize and to associate each aspect of the concept to the answer of each question. Thus, each question is in principle a course of action of the interpreter. This research proposes that each course of action, defined by each question, has to be related to an ontological analysis. Therefore, each course of action indicates a direction for defining the observed concept through ontological categories. An illustration of the scheme is shown in Figure 9-2 Figure 9-2 shows the scheme and the three levels that help differentiate the components of the scheme. The first level indicates the top ontological categories that are associated with the whathowwherewhowhenwhyscheme. Top ontological categories are basic distinctions that are neutral from any domain and on which basic relationships can be grounded. An analysis of a concept through the scheme must at least be defined by the categories showed. Although the purpose of our research is not to

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180 design a methodology for concept ontological analysis, our investigation does suggest that this framework must follow a systematic analysis of concepts. Other valid ontological analysis methods in the literature, which define top ontological categories (Guarino and Welty 2002; Sowa 1999), can be applied to the framework. Figure 9-2. Scheme for concept analysis and the associated top ontological categories. Figure 9-2 illustrates how top ontological categories act upon the proposed research scheme. For example, top ontological categories defined as continuant, which is the category that describe an object or abstract that has stable characteristics over a period of time, or occurrent top ontological category (Sowa 1999), that describes a concept that has enduring characteristics, can be set up by using the scheme. The scheme represents a methodology that classifies concepts ontologically. It is critical to highlight how ontological categories act upon the scheme. The third level of the scheme defines the relations that the cognitive agent or expert makes associations with based on the selected top ontological categories. For example, the expert recognizes the concept representation itself, finds role, in the scheme of Figure 9-2 ). The top ontological categories, such as abstract, physical, continuant, among others, capture the instances in which an agent reasons about a concept. Top ontological categories guide a classification of the concept into categories of existence. These

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181 categories identify a common denominator of the analyzed concept within a domain, which is by definition the ontological specification of the concept. by definition must be reflected in thdistinction of the relation of the cognitive-whoavailable conceptualization role in the organization of a construction project. The resulting analysis through the scheme is organized into a knowledge representation form in order to be manipulated, stored, and queried. This analysis is similar to the conceptualization process of information systems. However, in this approach the interpreter has to follow the course of actions of the scheme to ensure homogeneity and consistency in the analysis of the concepts. Taking this difference into consideration, the following is an explanation of the conceptualization and its dynamic within the proposed scheme. Conceptualizations A conceptualization is a set of informal rules that constrain a form of representation that describes a predefined social concept or concept of a domain. The meanings of those concepts are supposed to remain the same even if some of the situational conditions change (Guarino 1997). Conceptualizations are described by a set of informal rules used to express the meanings through a set of domain relations. Top ontological categories are employed as a mechanism for structuring the ground of the informal rules. The ontological distinctions support the domain conceptualizations, which in this case is the construction domain. This structure is a semantic network. Figure 9-3 shows an example. The top categories are the red boxes in the Figure. Figure 9-3 is a graphic notation of

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182 interconnected nodes and arcs. The nodes represent a declarative distinction and the arcs the relationships. Figure 9-3 As can be observed in Figure 9-3 there is the subtype or is-a relationship between declarative distinctions. This relationship is also called a generalization or subsumption hierarchy. It is employed with the purpose of supporting the rule of inheritance that replicate the properties defined for a super-type to all of its subtypes. Our research does not recognize that top ontological categories are unique or valid as a basic structure. Other top ontological categories could have also been employed to provide the distinctions in the framework or in the example. The employment of these ontological distinctions, however, has to be in a systematic method with the purpose of providing a conceptual analysis. Conceptual Analysis The second level of the scheme, shown in Figure 9-2 has the course of action expressed as

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183 interpreter, who is an expert as was mentioned to query and to address the description of the analyzed construction concept. As was explained previously, the first level indicates basic neutral distinctions through the top ontological categories. In addition, the boxes, which correspond to the third level of the scheme, have examples that help the readers analyze the concept in each course of action. In Figure 9-2 whatphysical object or as an abstract scheme. An abstract scheme is a pattern (e.g. geometrical forms, topology, or as textwhatcontrasts of the analyzed concept to in defining what a concept is. A metaphorical reasoning takes place and the interpreter faces the boundary of sufficiency or deficiency in identifying the concepts. In other words, the observer is able to identify a concept based on their own experience or own knowledge by contrasting the relationships between them. The relationships are essential for further analysis in the framework in order to non-observable elements that are not included in the representation of the concept. The boxes below on the third level of the scheme contain the possible form in which the concept is represented. The forms also facilitate further analysis about the strategy for the manipulation and the computation of the translated concepts. If the concept is represented as a function, for example, then procedural aspects are needed for describing the concept. If the concept is represented as an object, declarative relationships that describe the concepts such as the relationship of containment are needed.

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184 Figure 9-3 course of action within a semantic network. The examples illustrate an ontological definition from a top-down approach by employing top ontological categories from the first level of the scheme. In Figure 9-3 the left semantic links portion corresAluminium WindowsAluminium WindowsAluminium WindowsAddAluminium WindowsAluminium WindowsAluminium Windowsipulating the description of this concept within construction documents or within speech acts. The syntax Aluminium Windowsof specialization or explicit ontological representations are not used for the concept manipulation and for the concept computation. Aluminium WindowssWood-Window howanalyzed concept. If the concept has components or parts, the description includes how the parts are organized for a given function. When the concept contains parts, the distinctions made in the semantic network can define one or more functional relations among them. As was described in the modus operandi of concepts, the concepts encompass roles within the space-time dimensions.

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185 The functional relations describe this role as well as the role of the concept to others within space-time region. As it shown in Figure 9-4 in red boxes, the role of the concept is described Aluminum Windowsfunctionality. The concept should contain components that have properties and attributes. In Figure 9-4 the components meet certain properties specified in the regulations. whererelationship in the space time domain in which the analyzed concept is perceived. In addition, the Figure 9-4. Top ontological category analysis

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186 space time domain in which the analyzed concept is perceived. In addition, the analysis must settings as well as situational conditions concerning context relations. Further explanation concerning the relationships between the concept and space domain are described in Chapter 6 (modus operandi) and in Chapter 4 (concept in the construction domain). Since concepts can be asswherewhen the relation about a specific place or location is instantiated. For example, the concept platform in UF building 272. Figure 9-5 whereAluminum Windows Figure 9-5 context relationships are explicitly described. Although the Aluminum Windowsontological distinction are neutral for other concepts in the domain. In other words, the ontological distinctions, which are the red boxes on the right side of the Figure 9-5 can be used with other concepts in the domain. concept during its life in the time-space region. This is a specification of the stage of the concept (e.g. completed, installed, delayed) during its lifetime. It describes its process through the occurrent or continuant to specify the status of the concept within its lifetime. The reader can notice that the description of a concept depends on the characterization of its time scale. The concept can be considered as a process, as a part of a process, or as a stable entity. Thus, the concept status is a description of a view of the interpreter or of the expert by identifying this concept. The interpreter perceives the entity in an unstable or stable state at a given period of a

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187 Figure 9-5. Top ontolo time scale. This situation is labeled by this research as situational conditions or status conditions. Chapter 4 fully explains the research behind the situational condition notion and its relation to the stability of situations. Figure 9-6 Aluminium Windowswhen whyintention behind the interaction of the concept whoplayed within a social context, such as an organization, with the observed concept. The role is exclusive and it is the one played based on the course of action that the user has with the whoconceptualization

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188 with the analyzed concept. This research recognizes that each construction participant plays a role within a social context such as the construction project organization. Figure 9-6 As the intention is the explicit association of the observed concept to other concepts, the expert identifies the intention of the observed concept to others. This identification is performed exclusively for each one of the roles played by users within the observed concept. For example, why

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189 visual representation in the drawings, with the role of whyintention defines why these two concepts are related (e.g. the minimum distance specified by the local fire regulations) under the actor role. A careful analysis on associating two concepts is that this action is a semantic enrichment act. The risk of a combinational explosion on associating denominator which factors any association among concepts. In other words, the relevant The intention and the role have to be considered by the expert in analyzing an observed concept in the knowledge acquisition stage. The expert has to identify the actions played by the the purpose of one concept is described by an expert, the relationships between two or more concepts needs tpurpose is a dichotomy of the As Figure 9-7 whyfirst association of the intention of the cognitive agent within an ontological distinction. In Chapter 6 (modus operandi), Chapter 5 (granularity), and Chapter 8 (the semiotic proposition section), clearly the role of the user for interpreting a concept, as well as the intentionality within the concept, are recognized. The identification of the relationship between the observed concept and t

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190 form of the question is illustrated in Figure 9-7 Figure 9-7 whybasic form of inquiry helps the expert find the intentions of employing a concept by the actions of the role of a particular actor who belongs to a social organization. The expert actions in manipulating the representation of a specific concept. Thus, the role of the expert in the knowled

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191 with the observed concept. how the concept is represented and on how it is conceptualized. The granularity level of the observed entity is participant observes the layout of Porcelain-enameled reflector with 30CW x 30LW shielding. participants. The granularity level of the representation of this electrical concept is relevant only to the electrical subcontractor. In the case that a subcontractor attempts to perform an be performed. Knowledge Organization As it was explained, the conceptual framework is aimed at associating the orelationships between the agent and the observed concept. The framework guides this analysis and helps to define semantic associations to the concepts. Once the analysis of the observed concepts has been made through the scheme, the resulting knowledge has to be organized in a form of representation. Although the semantic network is a form of representation that was used in the knowledge acquisition component, this form is more useful for facilitating the visualization of the semantic associations of the concepts. The semantic networks, however, express semantic associations that can be transformed into a logic based language for computer implementations. An arrangement of the concepts and of their semantic associations through other forms is required to perform effective manipulation and computations. These forms are

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192 based on levels of representation that assure a systematic and harmonious re-use of the concepts by other actors in the community. They are also required to facilitate computational applications of the acquired knowledge. The knowledge organization within the framework is based on the distinction made by Brachman ( 1979) concerning the different levels of knowledge representation formalisms from forms of knowledge representation. The epistemological levels define how knowledge of the physical constructs or abstract notions can be represented (Kronfled 1990). For clarity, an analogy on these levels of representation can illustrate the knowledge organization. Suppose that some experts in the biology domain introduce a new concept by observation of some phenomenon. Initially the experts describe this new concept through visual representations and define it within biology taxonomies. However, even though the visual representations and taxonomies are forms of representations that hold semantics for these new concepts, additional levels for representing this concept are required for its manipulation and for its computation. This new concept, for example, was related to existing ontologies within the biology domain, which are semantically richer forms of representation than that of the taxonomies. Also, pragmatic aspects of this new concept are required to be associated within its definition as well as the definition of variables and quantifiers for computing. For example, the property oduced two times in two week of incubation. Therefore, if actors query any system on the number of biology concepts that can be reproduced two times in two weeks of incubation, the semantic associations to this new concept will be queried.

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193 The following levels incorporate the strategy for representing knowledge and the input from the cognitive agent. The levels are based on the distinction made by Brachman (1979), which differentiates knowledge representation formalisms from the epistemological point of view. The epistemological point of view is concerned to the nature of the forms and method for acquisition of knowledge of the physical constructs or abstract notion (Kronfled 1990). The levels of Brachman are complemented with the levels of representing knowledge from Guarino (1993), who emphasized that the intended meaning of the concepts must be performed a-priori in knowledge representation formalisms. As was introduced in Chapter 5, the conceptualization method is an a priori strategy for analyzing concepts. Logical. Symbol logics, predicates, and quantifiers, among others, that give formal semantics in terms of relations among entities within the real world. These relations are non-aligned concerning the intended meaning of concepts. Epistemological. Structures of concepts, objects, frames, inheritance, among others. -se involves or takes on meaning by capturing semantic relations. Pragmatics. All the arbitrary syntax and functions other than those specified in the epistemological level. Ontological. The use of ontological relations to define a-priori formalism in a structure. The fact of being a-priori facilitates the definition of the concept intention into the formalism. These formalisms are defined from top ontological distinctions to more refined ontological ones. In other words, the formalisms at this level can define general meanings of the concepts for the cognitive agents, or they can define a concept with a higher level of accuracy of the meaning by making additional ontological commitments. Conceptual. Conceptual relations, primitive objects and actions, linguistics roles, among others. These are the connections that infer particular meanings. However the meanings are subjective and, do not reflect any ontological commitments (Guarino 1995). The levels of representation define what is needed for representing a concept, by taking into account the primitives (e.g. predicates, structure relations) and the characteristics of each level (e.g. define concepts, meaning, forms etc.), as well as societal agreements on forms, on symbols and among other commitments. These aspects are used in the conceptual framework to

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194 s and additional semantic relations construction concepts, and the method that should be used to represent the knowledge as well as presentation. Organization in Clusters This research uses an abstract structure to organize knowledge in clusters. This structure is named Concept Cluster. Concept cluster is analogous to a metaclass of an ontology for information systems. This structure includes the aforementioned levels of representations and the semantic relationships of the semantic networks derived from the scheme within the knowledge acquisition stage. This structure gives a discriminate description of the components and relations of a concept. Concept cluster provides links to clusters with the purpose of organizing knowledge. Figure 9-8 illustrates the categories of the proposed concept cluster. The cluster groups are specified by (1) pragmatics, contain semantics only inferred from the pragmatic actions; (2) contextual relations, holds strictly locative relationships with other concepts; (3) intention, specify the purposes that define the relationships of the analyzed concept to other concepts; (4) part whole-relation, makes explicit relationships of containment and of the composite; (5) topology, describe the metaphors and symbols used for reasoning about the concept; and (6) cognitive agent role, explicitly states the social role of the actor within the concept. The cluster groups are specified by pragmatics, contextual relations, intention, part whole-relation, topology, cognitive agent role, and possible metaphors that represent that concept. The organization of the concept through the concept clusters structure is the subsequent analysis step from the one performed within the knowledge acquisition stage. It explicitly defines

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195 according to the categories of the metaclass. Experts or other actors perform this analysis and These links are formal inferences made by the actors about a relationship between one concept and other defined concept (Woods 1975). These links are inferred by the actors. In this case, the links connect the analyzed concept from the semantic network to the clusters. The clusters per se have a category, a distinction. This distinction is an additional semantic specification, which gives additional semantics to the concept. Figure 9-8. Concept Cluster structure. The following is an example that illustrates the course of action of the knowledge organization component, subsequent to the knowledge acquisition analysis step of the conceptual framework. An expert assumes the role as a contractor for analyzing the concep

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196 for a natural language form of a concept. must be on the border of sufficiency to derive the analysis of the fundamental questions of Figure 9-2 The starting point in the scheme of Figure 9-9 whatphysical object (physical category), and that the current representation is an abstract schem Figure 9-10 does not have the expertise to assert an interpretation about the role or functionality of the concept, as well as its status or stage of life in the time region (e.g. completed, installed, and delayed). Thus, the expert approaches the boundary of deficiency to interpret the functionality and the status of the provided text-based form representation, the expert is not to recognize the concept as a process, part of a process, or a stable entity. This portion of the howwhenme of Figure 9-9 For clarity within the example, these entries are shadowed in Figure 9-9 Figure 9-9. Scheme for concept analysis and the associated top ontological categories.

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197 The expert, then, is able to perform an analysis of two additional entries. Assume that this actor, in this example a contractor is aware of the situational conditions (e.g. location, position, w here why why the concept why situations, such as the need that made the contractor interpret that concept. For this particular example, suppose that the intention of the contractor is the installation of the metal curtain doors intention explicit. The reader is reminded that the explicit definition of the intention is central as a factor for finding semantic associations in the scheme. who conceptualization of the social role. as well as the manipulation of any concept representation within each role. The interpretation of a representation depends on the role played or associates the information to the concept clusters. This is the knowledge organization step. So far the information obtained from the scheme concerning the representrepresentation stands for a natural language form; the reference to physical object; the identification as an abstract scheme in natural language, the situational conditions (e.g. location, position, site, place), and the intention towards the representation concerning why the concept

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198 project). Concept cluster provides the expert additional semantic associations to analyzed information. In other words, the metaclass suggests additional semantic specifications that should be associated with the information extracted from the scheme. The sources of this additional information are other actors or experts, as was previously explained and illustrated in Figure 910. Figure 9-10 shows the structure and the links to each of the clusters. It is easy to observe that the concept-cluster associations constrain the formal meaning through ontological commitments in order to facilitate computation implementations. Figure 9-10 In relation, intention, part-whole relations, topology, and cognitive agent cluster. The result is that concept-rolling door is semantically associated to the following clusters: Representation. This cluster holds other type of representation such as the section of the Figure 9-10 the representation in the cluster is constructed in natural language. Pragmatics. Pragmatics includes the semantics upon pragmatic levels of a concept. The example shows two syntactic forms service doors and coiling doors that are other type of ontological concept. Contextual relation. This cluster holds possible and strictly locative relations with other objects. These relations indicate the state of affairs of the concept. Their property is that they do not change with the states of affairs of the concept. Figure 9-10 shows the Intention. The intention cluster contains purposes that the cognitive agents have with the concept and reasons for the interaction of the concepts with others. The purposes make lling doors in a specific construction project.

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199 Figure 9-10 Part-whole relations. This cluster supports relations that the analyzed concept bears as composite or as components of other objects. For simplification purposes, it contains only the significant composites, which are independent of the concept, as well as components, which hasrelationship of containment of the components rubber hood baffle, seals, and slats. Also, the electrical motor composite is shown. Topology. Topology contains image or visual schema representations, which are metaphors that transfer information from the author domain to the cognitive agent domain. From these representations, the cognitive agent can induce the relation to the analyzed concept. Figure 9-10 shows two visual representations, which illustrate an

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200 role in the organization. The assumption is that different roles in the organization make With the information obtained from the previous analysis, a group of experts or actors are able to build a structure This form of conceptualization resembles a systematic method to construct domain ontology. The resemblance is on the logic level and in the conceptual level of representations. The dconcept and the pragmatic aspects of the analyzed concept. Querying Querying consists of requesting information from the concept cluster or domain ontology. As illustrated in Figure 9-11, querying information from the concept cluster depends on the details or the sufficiency levels needed for the representation by the interpreter. The query process starts when the user or interpreter reasons on concepts in harmony with his or her needs during certain activities on a construction project. As was stated in this research, additional semantics on other representation are searched by the construction participant. For clarity, the actors who participate in this component are the users or construction project actors who perform representation of a concept. Chapter 1 explained these needs in an interoperability scenario. The focus of the querying component is to develop a strategy for information systems applications. The design of the component is adjusted to build a structure for which computation is possible. The strategy privileges the employment of symbols in order to make the computation possible. The employment of visual representations and reasoning forms such as topologies are not directly addressed for querying. The information systems are based on the computation on

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201 symbols. The use of other forms involves complex transformations in order to be computed through current technologies. Therefore, symbolic representations such as natural language are the representations employed for directly querying the concept cluster or ontology domain component. The query component is based on a process for searching the ontology for information systems or the knowledge bases that contain the information which has been conceptualized from the concept cluster. Figure 9-11 shows the workflow for querying additional information from the concept cluster or ontology domain, which constitutes the main mechanism for querying the component. The workflow describes the steps of this mechanism which consists of a series of searches for matches. The search will provide semantic associations to the user. These associations will grant explicit semantics to the interpreter. The associations offer explicit information by aiding the user to perform interpretations on the boundary of sufficiency. Once the user has identified the representation to be interpreted, or at least the unknown syntactic form, the user has to input this syntactic form into the querying process for searching. intention with the observed representation is taken into consideration. This is a fundamental assumption of the framework. The objective is to reduce the computational complexity of the semantic association search on the queried concept. Additional information, if possible, is valuable for narrowing the search space. For this purpose, the example of Figure 9-11 shows that the user knows the project location. Then, the user is able to input this additional information. This input is subjected to the intention and to the interoperability activity requirements. As shown in Figure 9-11 the input information is parsed and processed in the search engine. A search algorithm matches the syntax

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202 Figure 9-11. Query workflow. in the ontology or clusters or repositories. This information is parsed into a module that evaluates and weighs the multiple results. The evaluation results consist of a list of alternatives that semantically enrich the queried concept. This information is displayed for the interpreter who examines if the displayed information suggests additional semantic associations for his or her interpretation. If the provided or displayed options do not reach the level of sufficiency for interpreting the concept, additional information is needed. The additional information, which consists of the additional semantics for aiding the interpretation of the concept in the observed representation, will be determined through the query workflow mechanism of Figure 9-11.

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203 A visualization of the query through a GUI (Graphical User Interface) facilitates the understanding of the aforementioned workflow. Figure 9-13 illustrate a GUI that displays the query for interpreting a concept. The interpreter inputs the concept by using natural language. Thus, the first entrance will query the corresponding syntax representation of the concept. In order to avoid multiple outputs, or a combinatorial explosion, additional inputs are requested for the search. Therefore, the additional information for the initial input constrains multiple results by refining the search and by improving (O) complexity times. The rest of the inputs will constrain the search. In Figure 9-12 input. In Figure 9-12 corresponds to the social role of the actor who requests additional information to interpret the concept. The option specifies the main intentionality about the queried concept, which in this labor of a construction organization. The intention is associated with the social role that was input by the user. Obviously, the intention is previously defined by a conceptualization process of the social role of the construction participant. The social role description in Figure 9-12 d purposes for the interpreter. Figure 9-12 will help the interpreter in finding regulations for such an Educational Building Type in Alachua County from the queried concept.

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204 The left part of the GUI corresponds to an organized set of results of the queried concept. The results are symbolized by the tabs Dictionary, Context, Purposes, Parts, and Symbology. Thus, the results of the query will be shown within one of the tabs by querying the concept cluster knowledge bases. For example, Figure 9-13 this The purpose is to semantically enrich the description of the concept. Figure 9-12. Graphical user interface of a query. As a further illustration of the query, Figure 9-13 sSymbologycorresponds to the visual representation of the concept and the visual representation of its parts

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205 actor to visually identify aspects of the concept that are difficult to describe by employing natural e that the drawings, which are saved in graphic files. Symbols are not part of a mapping result between the topology and the drawings of the construction participants. The topologies are visual extensions of conceptualizations which are participant components of the drawings can match a typical, visual representation stored in the Figure 9-13. A graphical user interface that queries the topology clusters.

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206 Summary In summary, when any interoperability activity during a construction processes triggers the need to interpret a concept, the use of the framework scheme will aid the cognitive agent in analyzing the concept, and the concept clusters will assist the interpretation through the application of the structure that links the analyzed concept to other semantic specifications.

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207 CHAPTER 10 RESEARCH VALIDATION The validation of this research demonstrates the theoretical propositions for semantic interpretation through the use of examples which illustrate the relationships and the actions that take place between the actors or cognitive agents and the representation of concepts. The examples contain information used in past construction projects. The scenarios were recreated where typical situations of semantic interoperability activities are executed. The validation uses the conceptual framework for interpretation of construction concepts as a vehicle for searching relevant evidence, within the recreated situations and contexts. This chapter illustrates the examples in a case study format. The set of case studies were deliberately developed for testing the theoretical propositions as well as for illustrating the dynamic in construction project scenarios. The theoretical propositions serve as a template to compare the resulting construction project information of the case study. Case Study as a Strategy for Validation The philosophy of this research validation is aligned with the theory constructions of Weick, who suggests that the validation process should guarantee the usefulness of judging the plausibility of the theory proposition in a conceptual framework (Weick 1989). The nature of this research inquiry, which contains abstract speculations that fall under semantic interoperability scenarios, compels the use of validation methodologies other than the traditional data-recollection-testing methods. This research validation method is not based on previous literature and empirical observations, but is based upon the evaluation of the proposed conceptual framework through the simulation of scenarios. By definition, a conceptual framework contains an evolutionary process of theory propositions wrapped in the logic of constructs.

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208 This research is explanatory. Its nature exhibits an inquiry to unveil an epitomized phenomenon under the semantic interoperability paradigm. Therefore the validation will be restricted within the evaluation of the following factors: the plausibility of the theoretical constructs, and the effectiveness conceptual framework of interpretation activities. Validation Mechanisms The validation method consists of a recreation of scenarios in which an interpretation of a construction concept will be performed by a construction participant. The simulation is used as a mechanism that explains the sets of steps and logical propositions in interpreting the construction concept in order to explain an empirical event. The proposed conceptual framework contains these steps and logic propositions and support theoretical discussions. Therefore, the proposed mechanism validates the conceptual framework by circumscribing the simulation in the scientific methodology. This simulation of the interpretation will employ a set of construction concept representations and will be executed in two ways: first, the interpretation will be performed as a regular procedure of a construction activity; and second, the interpretation will be performed by using the conceptual framework proposed in this research. The following are the actors and resources that will be employed in simulating the interpretations: Cognitive agents. Actors will perform the interpretation of the construction concepts. The experts must play a role as a member from different areas of a construction project organization (e.g. PM, electrical contractor). Construction concept. Sets of concepts from each of the specialized construction areas will be selected. The concepts must be represented in natural language and visual or image schemas. The main objective is that the representation must be as close as possible to the common representation that construction participants find in a construction project.

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209 Conceptual framework tool. The strategy will employ a simulation of the queries where the conceptual framework is assembled, in order to facilitate the analysis of the concepts by the cognitive agents. Evaluation of the Validation These judgments must take into account the units of analysis, the plausibility of the theoretical constructs and the effectiveness of conceptual framework factors. In addition, the judgments must be observed through ideal scenarios of semantic interoperability activities. Ideal scenarios are those in which an ideal exchanging, sharing, transferring, and integrating of information from distributed sources such as customers, contractors, and owners is effectively performed. Ideal scenarios are those cases where construction participants manage to effectively communicate the content of information such as products, processes, and documents. Ideal scenarios also enable exchanging, sharing, transferring, and integrating of information with the purpose of helping construction participants make decisions or work on concurrent engineering. The selection of these scenarios will be made based upon the most pressing research needs. The needs account for the social, technical, and economic impact in the construction project. Therefore, it is anticipated that the most significant scenarios occur within reported results, quantity takeoffs, submittals, online purchasing of materials, and notification of design modifications, among others. Unit of analysis: Construction Concepts Actor(s): Estimator Secondary Actor(s): Architect and Specialty Engineer Roles: Estimator: Perform a quantity take off in order to generate an estimate of a construction project.

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210 Architect and Specialty Engineer: Architectural designs of a construction document. They are the authors of the construction documents that accompany the architectural design. Action: Interpretation of construction documents within an information sharing activity. Context The objective of the estimator in this case study is the prediction of the cost of performing construction documents and predictconstruction documents are elaborated, the project progress is on the final cost estimate stage. The overall design, then, is complete and the technical specifications are finalized, including the finishes. In the case study, an estimating activity takes place between the architect, the engineering an it be constructed within a certain budget. For this purpose, a quantity take-assumption is that the estimator possesses the skills and experience to identify the costs and the scope of work for iinterpretations of the construction documents that were elaborated and generated from other construction participants. During an estimating activity, the estimator reads the construction documents and continually searches for additional information concerning the components of the item to be estimated. The estimators interpret items on construction documents that where elaborated by other actors such as the architects or the specialty engineers in the design department. The estimators identify the items to be estimated in the construction documents. The items are concepts in the construction domain represented in these documents. Thus, a selected

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211 representation corresponds to the observed item. The observed concept was generated as well as was intended to be communicated to other actors on the construction project. The concept identification is followed by the full interpretation of the concept. The interpretation also implies the association to other project resources and the prediction of problems related to the interpreted as the required equipment for its installation or the mandatory care for storing in order to determine the associated costs. Note that these are additional interpretations of the concept Given the information in the construction documents, the estimator needs to possess the knowledge and skills for understanding the conditions and the related amount of work for -questions are how the interpretation process works and what strategy can be used to aid the dy The Sharing Information Case for Interoperability Sharing information means the distribution or the contribution for a particular purpose of a resource by a project actor to others within a construction project. This resource is obtained by other actors who belong to an internal or an external organization and who participate in a construction project. The objective is the completion of an activity by the other actors during a construction process. This resource is a form of representation of information that is either elaborated by any actor or just manipulated. An architect elaborates a wall design for a building project that is represented on the drawings, and a contractor interprets and manipulates the wall design.

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212 There is a relationship between the resources and actors of an organization. The actors play a specific role on an activity in a project. However, even if the roles are different within a project, the actors can have a joint purpose with the resources that are taken into consideration. The purpose is to define the relationship between the actor and the resources. An architect has the role of is the resource that it is shared with other members of the project network. This resource is represented through drawings and specifications. Another actor, the design engineer, has the role of reviewing these shared resources by providing observations to the drawings in order to meet local standards. The design is corrected and complemented by the architect according to the tors have a joint purpose with the shared resource. Alternatively, construction project participants can individually perform a role and convey an individual purpose by sharing a resource. An architect and a contractor can share the same resource such as tindividually and they also share the same resource. The reason for outlining the relationship actor-resources is to identify the nature of interoperability in a construction project, by recognizing the actions, the actors, and resources. -windows case The estimator is an actor of a construction project as well as a recipient of construction documents from other actors such as the architect and the design engineers, which is a sharing information case for interoperability. The employed documents are the shared resources mentioned in the above paragraph. These documents resources are the drawings and the

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213 specifications, which are human, readable forms of information. The drawings are visual typologies, i.e. visual representations, and the specifications are text based representations. The documents were created and elaborated by the architects and by the design engineers. These documents are employed or manipulated in order to be interpreted by the estimator. The shared information, then, is generated by the architects and is received by the estimator. These actors perform a different role but share the same representation. Their purpose with the representation is also different. The estimator has the purpose of executing quantity take offs over the documents while the architect has the purpose of elaborating a creative and functional design over the same set of documents. Clearly these actors do not work on collaboration for generating these documents. The architect or design engineer distributes packets of their work as a product among the construction project network. These packets are arranged for their distribution in a computer or human readable forms. The purpose is that other actors, such as an architect or a contractor, are able to manipulate these forms in the workflow. Semantic Interoperability Step The semantic interoperability paradigm stands for the understanding of what is represented exchanging, sharing, transferring, and integrating the meanings of information are the quest of ability to understand the meaning of the shared information from other actors. A contractor, for example, shares information or resources by obtaining construction documents from the architect and performs interpretations on these documents. The estimator also requests information from the architect and performs interpretation of representations in the construction documents. Figure 10-1 illustrates the continuous sharing, requesting, and exchanging of information. Figure 10-1

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214 also shows the flow of the construction documents, which are human readable forms of representation of information, from the architect or specialty engineer to the estimator. Figure 10-1. Continuous sharing information among construction actors. In Figure 10-1 the architect or design engineer generates information by translating and an interpretation of the observed representations of the construction documents. The requesting, sharing, and exchanging information between these two actors are manual operations. Typically, there are no networking technologies that facilitate the request for information operations among architects, design engineers, and estimators. In addition, the estimating of the architectconcepts represented in the construction documents are performed manually. The estimator manipulates the construction concept for interpretation. If the architect translates the concepts into a computerized form of representation, such as Computer Aided Design (CAD) formats, the estimator has to interpret the translated concept from the CAD format in order to perform any estimating activity. The CAD files are in human readable forms that make the interpretation possible. Subsequently, the estimator manually observes a representation from CAD format with

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215 the purpose of reasoning and finds meanings of the represented concept. The strategies for understanding of what has been represented within the shared information or shared construction documents and the methodology as a framework for interpretation are explained later on in the illustrative case. A function of the estimator is deciphering what has been represented on the shared construction documents in order to prepare the estimate. The estimators have the ability to execute quantity takeoffs from the construction documents. The elaboration of the estimate is an nstruction documents generated by other construction project actors is a step towards the developing of the estimate. The assumption is that the estimator has developed the experience and judgment to perform the interpretations on the documents. By visualizing construction processes, this ability should facilitate the estimator in the understanding not only of the explicit information represented in the documents, but also of the implicit information concerning the project, such as job conditions, material storage, and productivity rates. However, the elaboration of the construction documents implies the generation of details and conditions that cannot be fully recognized by the and conditions of past experiences. These past experiences aid the estimator in identifying errors or problems, but not all the details, conditions or construction process out of the level of expertise or even pragmatic aspects such as the terminology used to name construction resources in the documents in a particular local area. readable forms of representations without the aid of computation for examination or for interpretation. Thus the examination takes places by observing the form that describes the

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216 construction concepts. In other words, the estimator observes the construction documents and analyzes a form of knowledge representation for characterizing the construction concepts found in the documents. Identification of the concept from the representations As was explained, construction participants are committed to building projects based on the drawings and specifications they have been furnished as part of the construction documents. The documentation will help them in understanding the scope of the specific activities of the project. Designers rely on this documentation to communicate the design intent and contractors rely on the documentation to interpret this intent. This is a case of sharing information within interoperability. In this step, there is also an interpretation by observing and analyzing a specific representation in the documents. For this analysis, the actor observes the representation and identifies a concept. During this observation, as was mentioned, the actor identifies a concept depends on the purpose of analyzing the representation. How do these representations describe a concept and how do the actors identify the concept in the documents? As the specifications and the drawings describe a collection of construction concepts through their form of representing information, the specification describes the concepts through text-based representation and the drawings, through topological or geometrical forms. These representations themselves are simple metaphors that give meaning to some concept. Thus the method to obtain meanings of concepts from the documents is through their forms, either from text based or from topological forms. These forms express the characterization of the concepts employed within the documents.

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217 Figure 10-2 shows the metaphor of a concept. This metaphor is a visual representation that was generated for facilitating the reasoning to the interpreter. The visual representation in Figure 10-2 consists of a set of symmetrical lines. This visual representation is an image that has been selected from specific architectural drawings. The interpreter or estimator observes the set of lines on this construction document and reasons about the concept and its meaning. expressions for defining characteristics in a project, as opposed to complex and formal forms of any construction concept. The details and conditions are common words for defining the characteristics of the resources that play a particular role in a construction project. Typically what is considered a description of a concept is a poor characterization through description of concepts comprises geometric features, components or parts, additional or assembled items, and functional characteristics. For example, the description of a visual representation of can be extended through other topologies that describe the same concept. Figure 10-3 shows these topologies. The topologies are constrained by other dimensions and by text-constraints are concept Figure 10-2. A metaphor represented within the construction documents.

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218 (a) Visual representation of a section (b) Details of the visual representation. Figure 10-3The interpreter is able to not only reason through the topologies or metaphors but also through the syntax that are symbols that aid the definition of the concept. The sections in Figure 10-3 show additional geometric features, components or parts and assembled items of the topologies shows in Figure 10-3. This additional information is an explicitation of the information for describing the concept represented in the Figures. The interpreter or estimator has more elements for reasoning about the observed concept. Figure 10-4 shows additional metaphors or visual representation of the same concept. These representations show functionality features as well as other components of the concept for facilitating the reasoning. The topologies of Figure 10-4 are CAD images represented by a computer in a human readable form. The visual representation illustrates the concept from bottom and top sections. As in shown in Figure 10-4, text based representations or syntactical symbols aid the reasoning of the metaphor shown in Figure 10-2.

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219 (a) Bottom Section. (b) Top section. Figure 10-4An additional form for characterizing concepts is the explanation of the conditions of the concept. In the construction industry, the conditions are commonly bounded in the space time dimensions, and they are named as situational conditions. The description of situational conditions includes the states of affairs, the status condition, and contexts relations of the represented concept in the construction documents. The states of affairs includes the location position, site place, and settings of the concept; the status conditions comprises the stage of the concept life cycle (e.g. completed, installed), and context relations embraces the description of the associations to other concepts within space dimension. These situational conditions are described through the text-based forms of representation in the construction documents. The situational conditions are expressed through general example of the text-based form of representation. Figure 10-5 shows the same concept as Figures 10-3 and 10-4, except its descriptions are in text-based format.

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220 Figure 10-5Figure 10-5 describes the situational conditions of the concept components of Figures 10-3 and 10-4, a Section 1.6 A of the text based representation. This is an explanation of a contextual relation of glasson project. An action is suggested to protect the component glassconcept performed by the architect or design engineering who generated the representation of Figure 10-5. In Section 1.6 A, the level of specifications of the environmental conditions can be glassis described in more details by considering the condensation, temperature changes, and direct exposure to the sun which are constituents of the environmental condition concept.

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221 The text-based representation can also describe properties of the concept of Figures 10-3 and 10-glasshas to comply with certain properties for serving particular purposes. Figures 10-6 shows a section of construction documents that describes the properties of the concept of Figures 10-3 and 10-4. The description of the properties shown in Figure 10-6 is done by the text-based -aluminum is required to resists wind loads, then the description of Figure 10-6. Text--concept.

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222 is instantiated by including the number of the regulations that define the ability of the glass How is a concept identified by the estimator? The estimator should locate the object or item in the documents by observation. However, the reasoning and interpretations of the representations. The actions are procedural operations which are not analyzed in the interpretation of the observed concept. However the intentionality of the actor is a basic tenet for interpreting the representation. This intentionality describes why the estimator performs the interpretation. As intentionality is the explicit association of the observed concept to others concepts, the estimator has to identify the tion is to verify minimum thickness of the glass-3 and 10-4 to estimate the component cost, then the estimator needs to search for the description of thickness in the construction documents. The thickness could have been described as a constraint of size in Figures 10-3 and 10-4 As it is shown, these Figures do not contain the constraint thickness to search for the thickness description in other construction documents. Figure 10-6, which is a text based representation, has a description of the thickness concept constraint. Note that the thicknessg syntax in the construction document of Figure 10-6. In this case, the similarity relationships are semantic associations established only for the purpose of costing the thickness of the glass component. The intention defines why the

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223 This identification of a concept within the construction documents is performed by searching similarity relationships. The estimator matches the possessed notion of the concept and the observed description in the documents. Thus, if the estimator first searches a concept through the syntax form of representation, then this actor looks for the similarity relationship between the possessed notion and the observed representation in the documents. A typical search for similarity relationships is when the actor focuses their searches on the indexes of the representations. Figures 10The estimator uses similarity relationships to perform the identification of a concept within possessed notion of this concept with the representation within the construction document, then the estimator affords the existence of a concept. Indexes are markers or icons whose semantics exclusively indicate a relationship to a specific concept. (a) (b) Figure 10-7fixed-aluminum windowsA802

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224 -semantics function is to documents. Note thaadditional semantics. Indexes provide no other than the indexical relation. An interpretation of the concept can be guided by the index, although the index may not be necessary for its In the same way, the estimator searches for other syntax representations, such as the window concept in the Figure 10-7 (b) that can be located within any construction specifications, Figure 10-7 (b), the -the displayed values of the concept in the Figure 10-7 (b), and the spatial arrangement of the fixedaluminum windowfixedaluminum windowdocuments. fixedaluminum windowlocated through similarity relationships either by matching syntactic expressions such as fixedaluminum windowservation additional features

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225 fixedaluminum windowexplained, the activity is defined by thThese role activities are human manipulations of the representation which are expressed in human readable forms. There is not a computational device that helps to identify the concepts on the drawings for executing the quantity take offs. The concepts must be commonly recognized by social actors, they are common, shared concepts. In interoperability, the assumption is that architect, design engineering, and the estimator are social actors that commonly recognize the concepts they interoperate on. The fixedaluminum windowHowever, its recognition does not indicate that their interpretation of a concept is the same with the exact and same concept features. The particular, social, inclusion feature of index implies a purpose of sharing concepts among the community. This purpose, then, should make any index, by virtue of its semantics, be an artificial signal to point to a concept. The pointed or mapped concept, by virtue of the indexical relation, must be the same independently from which actor performs the interpretation. Within the social, convention role, index has the character of being dependent on the mapped representation although it is an artificial representation that can exist A802-7 (a) has the character of being dependent on the exterior windowdoes not have semantic meaning by itself. In summary, index is an artificial representation that facilitates the identification of a socially recognized concept within the construction documents.

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226 Are the representations within the construction documents accurate to perform interpretations? The representations on the construction documents are poor translations made by the actor that generates them. The architect or design engineering describes a concept through topologies, text-based representations and other forms of representation at certain levels of granularity which limit the interpretations to the intended purposes. The committed level of granularity of the representation is semantically poor for other purposes. The architectural drawings are generated for general purposes to be integrated by the general contractor, the electrical contractor, or the municipal council. The architectural drawings are complemented with the specifications to have better granularity level description. However, they do not fully describe the concepts at certain granularity level for other actors within interoperability activities. For example, the architectural drawings, as shown in Figure 10-8 do not describe information concerning finishes for the estimator. The estimator must include the cost of protection of the aluminum frame for estimating purposes. Figure 108-representation.

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227 fixed-aluminum windowsadditional cost. Not only the cost of the additional items has to be included in the project, but also their installation cost. The architectural drawings, shown in Figure 10-8 only provide information about the special distributi---construction progresses or they may be slipped into the opening when the building has been completed.

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228 CHAPTER 11 CONCLUSIONS AND CONTRIBUTIONS Since fully automatic interoperation is not feasible, human intervention is necessary to accomplish interoperability activities. The manipulations on any form of representation, which are based on human intervention, are part of the interoperability process. The manipulations involve an interpretation step performed by the actor or construction participant. Therefore, one or more components of the interoperability process demand human intervention. For this purpose, this investigation considers meditation as essential for interoperability. A mediation mechanism should be established to aid the interpretation of any form of representation of a concept generated from other sources. Automatic interoperability by employing approaches that transform concepts into models, schemas, or conceptual models, operated by computers, without any form of mediation is not possible. The use of computers should be understood as a mechanism for mediation and as a device that translates a construction concept into other forms of representation, such as the translation from human readable forms to a computer readable form, and as a mechanism that performs calculations on the translated representation. Note that the representations are forms of knowledge representation that describe construction concepts. The scrutiny of the interpretation action, which is performed by an actor as cognitive agent on the representations, indicates the quest for the understanding the involved, fundamental elements. The basic studied elements were the representation of construction concept in their prima naturae and in their prima character, and the relationship between the actor and the representations. The purpose is to bring into existence and to assemble a strategy that aids the actors reduce time, resources, and errors within their interpretation operations. The quest for efficiency as well as for economy of these operations is the motivation of the present research

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229 efforts. The purposes of these efforts are the reduction of time, resources, and errors within the interoperability activities. The interpretation step takes place when a relationship is established between a representations and an actor by observing the representation in sharing, exchanging, or integrating of information activities. Clearly, this research addresses a method to reduce the time and resources in this interpretation. As a result of the analysis of the fundamental elements within an interpretation, this research develops a conceptual framework for aiding the interpretation action of a concept from the construction domain. This framework describes a mechanism or process that serves for semantic interpretation. The framework mediates between the representation and the actor in order to perform interpretations. The mediation is an alternative approach from that of the modeling paradigm which forces the actor to follow a previously prescribed set of rules, syntax, vocabulary, and conceptual model in order to perform the interoperability activity. The process defined in the conceptual is addressed to aid the interpretation according to the level of sufficiency for interpretation of the concept representation. The framework also considers the concept. Then, the conceptual framework helps in the analysis of the interpretation process and takes into account the intentionality of the cognitive agent. One of the elements used by this framework is a knowledge representation structure named This knowledge base has the ability to store and to provide the semantic associations of the conc epts. It semantically organizes concepts to facilitate the storing and retrieving of queries about a concept in construction. This knowledge structure is a mechanism that can be implemented as a metaclass for ontologies for computer systems.

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230 The framework also recognizes the social role of the construction participant and additional relations such as the state of affairs and the physical location. For example, the estimator is mainly concerned with the quantification of products. Thus, the framework associate components that are being quantified. Our analysis of the fundamentals of sharing, exchanging and integrating information suggests that the concepts of This concept was taken under consideration for the framework design. Considering the case study, if the estimator receives pieces of lines from the designer in the drawings with poor d efinition of the concept on the drawings schedule, the framework provides a mechanism to aid observed and queried, and enriching the representation of such co ncept. Therefore, practical errors such as misinterpretations or a lack of understanding or familiarity with the components are reduced. The framework addresses the enrichment of the semantic deficiencies of the representations. It attempts to satisfy the concerning a construction concept in order to aid the actor in performing an accurate interpretation. As opposed to the current notion of concept within the construction industry, which implies the description of geometric features, components or parts, additional or assembled items, and functional characteristics, our research claims that concepts are manifestation of signs construction participant as a cognitive agent who uses his or her knowledge and experience for reasoning on any form of representation. In this study, the employment of metaphorical

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231 reasoning is a valid strategy for the identification of construction concepts by the cognitive agents. The concepts are represented through forms of knowledge representation that have the character of signs. The signs are described on paper, such as ink markers or topologies on the drawings, or on human readable electronic forms. From the aforementioned proposition, the interpretations of concepts. Thus, the role of an actor within a construction project delimits the scope and the complexity for interpreting an observed representation. Our research concludes that the ability to accurately interpret a concept by observing explicit forms depends on the granularity level of the representation. This dependency is a relationship that can be plotted into an artificial graph (see Figure 5-1), which shows the relationship between the quantity of explicitly given information and the accuracy of its interpretation. The explicit information is directly related to the interpretation of a concept if the interpreter unders tands what is explicitly described. In this way, a level of explicit details is necessary until the interpreter is able to interpret what is explicitly described. This is the case for defining the border of sufficiency to interpret a concept. However, if t he interpreter cannot reach a level for understanding what is explicitly represented, even though there are enough explicit details for such interpretation, then d by the boundary of deficiency. In summary, our research concludes that for understanding the information that is generated from other sources within a process of exchanging, sharing, and integrating information, a mediation mechanism should be included. The mechanism mediates through an ontological description of the information that is shared, exchanged, and integrated by the actors. In addition, our research claims that the information that is exchanged, shared, and integrated is

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232 based on representation of concepts. These tend to be poor semantic representations of concepts actors within the construction project. The accuracy for interpreting the representation depends Therefore, this claim contrasts to the modelling and to the standardization efforts on imposing er actors on a construction project. Contributions and Implications A major contribution to the construction scientific community is the systematic study of the fundamentals on the interpretation of explicit information, which were employed for constructing theoretical propositions assembled in a conceptual framework. The framework articulates a strategy based on theoretical propositions in order to interpret forms of representation of a concept. The employment of the method devised in this framework, as a reasoning concerning accurate interpretations of representations of construction concepts within an interoperability activity. Therefore, the first contribution is that this research furnishes a valid framework to manually interoperate with information provided from other sources. This framework provides assistance to the construction participant in interpreting an observed representation. The framework is based on operating and on working with concepts of the construction domain. In this framework, this research addresses fundamental aspects of the interpretation step of what is represented in paper-based or computer-readable forms. The exploration of these fundamentals significantly advances the understanding of the semantic interoperability paradigm, especially in the direction was made towards analysis of the relationship between the construction project

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233 actor as cognitive agent and explicit forms of representations. This framework is a contribution not only in the mechanisms for organizing construction domain concepts, but also on the proposed modus operandi for interoperability. The conceptual framework is an outcome of the explanatory approach within the semantic interoperability paradigm. An implication to the community is that the rethinking of the modus operandi of information through the employment of construction concepts is a revolutionary approach for manipulating information in construction projects. An increase in productivity and efficiency in interoperability is expected with the implementation of this approach in the projects. In other words, the construction project actor benefits from employing the strategy described in the framework by reaching efficiency as well as for economy of the interpretation operations. The implementation of this approach should result in a better use of the resources and to the reduction of time, errors, and misunderstandings on interpreting information provided from other sources in the project. In addition, this framework will offer any domain actor support on theoretical foundations to develop computer applications. Thus, the reasoning that the framework provides will help system designers of the construction domain to have a better basis to explicitly represent construction products. In addition, concept clusters should give better insights to the designer in order to identify the components of concepts and concept practical accounts. Accordingly, the implementation of the proposed strategy systematically will help construction participants in identifying the potential inconsistencies in their interpretations of the construction concept representations.

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234 Recommendations for Future Research Since construction manageme nt is a practical discipline, any future research has to be focused on applications to the current problems continuously challenge the construction industry. Our research envisions the communication of representations of concepts which are shared, exchange d, and integrated by multiple actors on construction projects as a practical area of research, which falls within the interoperability and collaboration paradigms. From the scientific point of view, our research envisions the u se of the semiotic framework as a promising field for understanding the relationship between actors and representations and the relationship between the actors and the world. The semiotic framework studies signs and their interpretations. The introduction of the semiotic framework is a new strategy to find approaches within the interoperability paradigm and it is also new research within the construction management field. The applicability of this effort requires the development of tools that employ signs as a vehicle for meaning that aids the communication between construction project actors of observable and not observable signs. The purpose of these practical implementations is to significantly reduce errors within the interpretations of representations of construction concepts. The scientific exploration of conceptual role semantics theory is a promising field for the understanding of meanings of representation of concepts which are generated from other sources. Future efforts should address the lack of methodologies to aid construction project actors in interpreting the representation of concepts. They will require the development of meta-ontologies to capture the meanings of representations generated from other sources. The practical purpose is to generate a new and innovative technique to communicate concepts that are translated into representation among construction project actors.

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242 BIOGRAPHICAL SKETCH Ivan Mutis earned his PhD degree in construction engineering and management from the University of Florida, Gainesville, Florida. Ivan was honored with the Rinker Scholar Fellowship, the highest merit-based award for PhD students in the department, to support his doctoral studies. While working towards his degree, he worked at the Computer Science Department at the University of Florida where he collaborated with computer science colleagues in research on interoperability in construction. Ivan holds a Master of Science in civil engineering from the University of Florida with an area of concentration in construction management. He also holds a Master of Science degree in Construction Engineering and Management from the Civil Engineering Department at Los Andes University, Bogota, Colombia, and a Bachelor of Science in Civil Engineering from the Pontificia Universidad Javeriana, Bogota, Colombia. Ivan worked as an instructor at Pontificia Universidad Javeriana, and held positions as a project manager and graduate assistant at Los Andes University. After graduation, Ivan will continue his academic career as an assistant professor at the University of Southern Mississippi, at Hattiesburg, MS.