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Future of Information Exchanges and Interoperability

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Future of Information Exchanges and Interoperability
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Workshop on Linked Building Data and Semantic Web Technologies (WLS2019) ( Conference )
Costin, Aaron ( Editor )
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Over the last few decades, the built environment and the Architecture, Engineering, Construction and Operation (AECO) Industry has seen an increase in the amount of computer software, technologies, and automation to help improve all facets of the industry. This new era of technologies is enabling transformative change in the way our communities are interacting among themselves and with the built environment. The Internet of Things (IoT), cyber infrastructure, Big Data, and Artificial Intelligence (AI) are among the new transformative changes that produce and share information from all the connected devices and technologies enabling Smart Cities and Intelligent Jobsites. With the increase of such innovations, seamless information exchange between the connected technologies within the different domain facets is a major need. The purpose of this workshop was to provide a focused overview on technical and applied research on the usage of semantic web, linked data, and web of data technologies for the AECO industry. The workshop aimed at gathering researchers, industry stakeholders, and standardization bodies of the broader Linked Building Data (LBD) community. This includes the buildingSMART Linked Data Working Group (LDWG) participants, the W3C Linked Building Data (LBD) Community Group participants, and others.
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Collected for University of Florida's Institutional Repository by the UFIR Self-Submittal tool. Submitted by Aaron Costin.
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Costin, A. M. (Ed.) (2020). Future of Information Exchanges and Interoperability. Gainesville, FL: SCI Publishing, ISBN: 978-1-7351595-0-8.

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Future of Information Exchanges and Interoperability Proceedings of the 2019 Workshop on Linked Building Data and Semantic Web Technologies (WLS2019) Editor: Aaron Costin, Ph.D.

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Future of Information Exchanges and Interoperability i September 29 October 1, 2019 Gainesville, Florida Infotech, Inc. 2970 SW 50 th Terrace Gainesville, FL 32608 S PONSORED B Y University of Florida College of Design, Construction and Planning and Infotech, Inc. E DITED B Y Aaron Cost in, Ph.D. Smart Construction Informatics (SCI) Lab oratory 304 Rinker Hall P.O. Box 115703 Gainesville, FL 32611 F UTURE OF I NFORMATION E XCHANGES AND I NTEROPERABILI TY P ROCEEDINGS OF THE 2019 W ORKSHOP ON L INKED B UILDING D ATA AND S EMANTIC W EB T ECHNOLOGIES (WLS2019)

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Future of Information Exchanges and Interoperability ii Published by Smart Construction Informatics (SCI) Laboratory 304 Rinker Hall P.O. Box 115703 Gainesville, FL 32611 Any statements expres sed in these materials are those of the individual authors and do not necessarily represent the views of SCI Lab and the sponsors Infotech, Inc., and the College of Design, Construction and Planning, which takes no responsibility for any statement made her ein. No reference made in this publicati on to any specific method, product, process, or service constitutes or implies an endorsement, recommendation, or warranty thereof by SCI Lab. The materials are for general information only and do not represent a sta ndard of SCI Lab, nor are they intended as a reference in purchase specifications, contracts, regulations, statutes, or any other legal document. SCI Lab makes no representation or warranty of any kind, whether express or implied, concerning the accuracy, completeness, suitability, or utility of any information, apparatus, product, or process discussed in this publication, and assumes no liability therefor. The information contained in these materials should not be used without first securing competent advi ce with respect to its suitabi lity for any general or specific application. Anyone utilizing such information assumes all liability arising from such use, including but not limited to infringement of any patent or patents. Photocopies and permissions. Per mission to photocopy or reprod uce material from this document can be requested by sending an e mail to wls2019@dcp.ufl.edu. Copyright © 2020 by the Smart Construction Informatics (SCI) Laboratory All Rights Reserved. ISBN : 978 1 7351595 0 8 Manufactured i n the United States of America .

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Future of Information Exchanges and Interoperability iii Acknowledgements The following members are recognized for their dedication, support, and contributions for the success of the 2019 Workshop on Linked Building Data and Semantic Web Technologies. Organizing Committee: Aaron Costin, University of Florida, USA R. Raymond Issa, University of Florida, USA Monelle McKay, Info tech , USA Pieter Pauwels, Eindhoven University of Technology, Netherlands Nora El Gohary, University of Illinois at Urbana Champaign, USA Technical Committe e : Mike Conlon, Univers ity of Florida Gonçal Costa, La Salle, Ramon Llull University, Spain Aaron Costin, University of Florida, United States Chuck Eastman, Georgia Institute of technology, United States Tamer El Diraby, University of Toronto, Canada Nora El Gohary, University of Illinois at Urbana Champaign, United States Masoud Gheisari, University of Florida, United States Raymond Issa, University of Florida, United States Saeed Karshenas, Marquette University, United States Yongcheol Lee, Louisiana Sta te University, United S tates Maxime Lefrançois, MINES Saint Étienne, France Kris McGlinn, Trinity College Dublin, Ireland Ivan Mutis, Illinois Institute of Technology, United States Nawari Nawari, University of Florida, United States Pieter Pauwels, Ghent University, Belgium Mar ía Poveda, Technical University of Madrid, Spain Ana Roxin, University of Burgundy, France Georg Ferdinand Schneider, Fraunhofer Institute for Building Physics, Germany Workshop Event Planning and Support : Student Volunte ers : Sara Ann Green Heather Rene Clayton Kjerstin Terry Jessica Berg Joshua Garland Lacey Jones Bob DeHoff Hector Del Valle Ron Perkins Doug Couto Darcy Herlihy Carmen Jeffcoat Travis Tooke Alireza Adibfar Bing Qi Grant Anderson Jimmy Sebesta

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Future of Information Exchanges and Interoperability ii Supporting Organizations Sponsors Supporting Organizations

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Future of Information Exchanges and Interoperability iii Contents ................................ ................................ ................................ ............................ 5 Sponsor Let ter ................................ ................................ ................................ ................................ 6 Program ................................ ................................ ................................ ................................ ......... 7 SESSION #1 DATA STRUCTURES, FORMATS, AND STANDARDS Keynote: The Future of Open Data for the Built Environment ................................ .......................... 9 Dennis Shelden, AIA Ph.D. Web Based Management of Building Data: An LBD Approach ................................ ........................ 10 Pieter Pauwels, Ph.D. Functional Modeling and Reasoning in Building Design ................................ ................................ . 10 Andres Cavieres, Ph.D. Semantic Interoperability and Semantic Technologies at a Crossroads. ................................ .......... 10 Jack Hodges, Ph.D Blockchain and the Built Environment: Automated Design Reviews ................................ ............... 11 Shriraam Ravindran Machine Readable Taxonomy Delivery: CSI Construction Information Exchange (CIE), A Sole Source of Truth for Software ................................ ................................ ................................ .................... 12 Greg Ceton SESSION #2 IND USTRY AND OWNER PERSPECTIVES Operational Technolo gy ................................ ................................ ................................ ............... 13 April Blackburn, PMP Capitalizing on Autonomy, Connectivity, and other Advanced Technologies to Enhance Mobility and Safety : The I STREET testbed ................................ ................................ ................................ ........ 14 Lily Elefteriadou, Ph.D. SunTrax: Accelerating the Future of Transportation ................................ ................................ ...... 14 Josh Pedersen, PE Self Driving Vehicles and Advanced Mobility Transportation Options ................................ ............ 14 Dea n Bushey, Ph.D., Col(r) US Air Force Migrating from 2D Plans to Digital Twins ................................ ................................ ...................... 15 Mark Lemieux, PE Life Cycle Information Models for Highway Infrastructure ................................ ............................. 15 Amlan Mukherjee, Ph.D., PE

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Future of Information Exchanges and Interoperability iv SESSION #3 DATA STRUCTURES, FORMATS, AND STANDARDS Keynote: AEC Tech Innovations: Technology | Implementation | Outlook for the Future ............... 16 Ron Perkins, PMP Digital Workflow in a Federated Model Environment ................................ ................................ .... 17 Leif Granholm BIM Framework for Sustainability in Saudi Arabia ................................ ................................ ......... 17 Fatma Hasanain Digital Twin s of Urban Buildings with a Data and Computing Web Platform ................................ ... 17 Xuan Luo Ontology Based Building Information Model Design Change Visualization ................................ ..... 18 Ning Wang Semantic Web for Knowledge Based Energy Management and User Engagement in Existing Buildings ................................ ................................ ................................ ................................ .................... 18 Hervé Pruvost PRO CEEDING S Functional Model ing and Reasoning in Building Design ................................ ................................ . 20 Andres Cavieres, Ph.D., Charles Eastman, and Russell Gentry, Ph.D. A Graph Database and Query Approach to IFC Data Management ................................ ................. 28 Zhengyang Chen , Yiying Pu , and Dennis R. Shelden Smart Grid/Building Semantic Integration for Interoperability ................................ ....................... 37 Jack Hodges, Ph.D. and Wei Xi Xia, MS Using Linked Data to facilitate smooth and effective workflow in a federated model environment 45 Leif Granholm, M.SC. (Eng) , and Seppo Törmä D.Sc. (Tech) Ontology Based Building Information Model Design Change Visualization ................................ ..... 53 Ning Wang, SM.ASCE , and Raja R.A. Issa, PhD, JD, PE, F.ASCE, API Blockchain and the Built Environment: Automated Design Review Process ................................ .... 62 Nawari. O Nawari, Ph.D., P.E., F.ASCE, and Shriraam Ravindran, M.Sc. BIM Framework for Sustainability in Saudi Arabia ................................ ................................ ......... 69 Fatma Hasanain MIA and Nawari O. Nawari , Ph.D., P.E., F.ASCE2 Digital Twins of Urban Buildings with a Data and Computing Web Platform ................................ ... 83 Xuan Luo and Tianzhen Hong Data Integration and Innovation: The Future of the Construction, Infrastructure, and Transportati on Industries ................................ ................................ ................................ ................................ ..... 85 Ron Perkins , C. Douglass Couto , and Aaron Costin, Ph.D.

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Future of Information Exchanges and Interoperability 5 The Workshop on Linked Building Data and Semantic Web Technolo gies 2019 (WLS2019) was hosted by the University of Florida with sponsorship from the College of Design, Construction and Planning. The Workshop was co hosted with Infotech, Inc, held in the ci ty of Gainesville, Florida from September 29 through October 1 , 2019. Over the last few decades, the built environment and the Architecture, Engineering, Construction and Operation (AECO) Industry has seen an increase in the amount of computer software, technologies, and automation to help improve all facets of the industry. This new era of technologies is enabling transformative change in the way our communities are interacting among themselves and with the built environment. The Internet of Things (IoT) , cyber infrastructure, Big Data , and Artificial Intelligence (AI) are among the new transformative changes that produce and share information from all the connected devices and technologies enabling Smart Cities and Intelligent Jobsites . With the increase of such innovations, seamless information exchange between th e connected technologies within the different domain facets is a major need. The purpose of this workshop was to provide a focused overview on technical and applied research on the usage of sema ntic web, linked data, and web of data technologies for the AE CO industry. The workshop aimed at gathering researchers, industry stakeholders, and standardization bodies of the broader Linked Building Data (LBD) community. This includes the buildingSMART L inked Data Working Group (LDWG) participants, the W3C Linked B uilding Data (LBD) Community Group participants, and others. The 2019 Workshop, as a standalone event, received 20 abstracts, 14 full papers, and 10 extended abstracts for the poster and demonstration sessions. A total of 8 full papers and 15 presentation from countries around the world were accepted and included in the proceedings. The final set of papers was selected through a rigorous peer review pr ocess, which involved the collection of at least two blinded reviews per paper. The review process was per formed for both abstracts and full papers, ensuring that only the best contributions were selected. Finally, the authors had the chance to incorporate We are very pleased with the high quality of selected papers, and we wish to thank both the authors and reviewers for their efforts. The success of organizing this workshop has only been made possible with the support of many. We are particularly grateful to the College of Design, Construction and Planning, the M. E. Rinker, Sr. School of Construction Management, and Infotech Inc. We hope that you enjoyed the workshop sessions, posters, demonstrations, and indus try panel discussion during the workshop and that the results disseminated from this can foster new partne rships to promote new research directions. Aaron Costin, Ph.D. Conference Chair, Organizing Committee, University of Florida

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Future of Information Exchanges and Interoperability 6 Innovation is a top priority at Infotech. The 2019 WLS Workshop was the first of its kind in the U.S., bringing national and international experts to gather in Gainesville, Fla., where we are headquartered, to discuss big ideas about linked building data. It was our honor and privilege to be the p rimary sponsor and host for this event that brought forth imp ortant conversations regarding the future of information exchange and interoperability. The highly interactive workshop and its diverse attendance brought academia, owners, and industry togethe r to discuss the future of information exchanges and interope rability. It was quite a success, with discussions on data and technology from our three keynotes, 15 additional speaker presentations, and conversations with local students about cutting edge to pics. Navigating the many disparate, fast emerging technolo gies is no easy feat, but when everyone speaks the same language the language of data integration the obstacle of creating a seamless process becomes an exciting challenge. The WLS workshop p artnership was born from the desire to create a space to conn ect key leaders and relationships in this niche field, to bring potential new opportunities to our city of Gainesville and to team up with academia and industry in gaining understanding about the excited to witness the results of this collabo ration and to see what possibilities are on the horizon.

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Future of Information Exchanges and Interoperability 7 Day 1 Sunday 29 September 12:00 PM Registration 12:30 PM | Pre Workshop Short Courses 6:00 PM | Opening Reception (Info Tech) 8:00 PM | End Day 2 Monday 30 September 7:00 AM | Regist ration 8:00 AM | Welcome and Opening Remarks o Aaron Costin, Workshop Chair o Chimay Anumba, Dean, College of Design, Construction and Planning 8:30 AM | Keynote #1: Dennis Shelden, Ph.D. Georgia Institute of Technology 9:05 AM | Plenary Session #1 Data stru ctures, formats, and standards 10:30 AM | Coffee Break 10:45 AM |Breakout Session 11:45 PM | Session Recap and Discussions 12:15 PM | Session End 12:2 0 PM | Lunch (Info Tech) 1:45 PM | Keynote #2: April Blackburn, PMP, FDOT 2:20 PM | Plenary Session #2: In dustry and owner perspectives 3:45 PM | Coffee Break 4:00 PM | Breakout Session 4:40 PM | Session Recap and Discussions 5:30 PM | Session End 6:00 PM | Networking Reception o Student Poster Session o Research Demonstrations o Software Demonstration o Industry Dem onstrations 8:00 PM | End Day 3 Tuesday 1 October 7:00 AM | Registration 8:00 AM | Opening Remarks o R. Raymond Issa, Director, M.E. Rinker, Sr. School of Construction Management 8:15 AM | Keynote #3 Ron Perkins, Jobsite Tech Group 8:50 AM | Plenary Sess ion #3: Technology, implementation, and outlook 10:15 AM | Coffee Break 10:30 AM |Breakout Session 11:05 PM | Session Recap and Discussions 12:00 PM | Workshop Conclusion and Closing 12:15 PM | Lunch (Info Tech) 1:30 | Mini Hackathon (Info Tech) 5:00 | Din ner 7:30 | Mini Hackathon Awarding and Closing Remarks 8:00 | End

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Future of Information Exchanges and Interoperability 8 Innovative Design for Sustainability: Integrating Embodied Impacts and Costs During Early Design Phase Ruochen Zeng Evaluating Transportation Services Based on Soc ial Media Data: A Case Study in Miami Dade County Bing Qi Fusing Bridge Information Mode ling (BrIM) and Intelligent Transportation Systems (ITS) Data into IFC Alireza Adibfar Safety Training using 360 Degree Panorama and Virtual Reality Techniques Ric ardo Eiris Energy Neutrality analysis for Occupancy Sensor integrated Smart Building: An L CA Study Tarun Kumar Factor analysis for emerging technology in industrialized construction: the USA v.s. China Shuyu Qian Improving Point Cloud Accuracy Using a Cu stomized Unmanned Aerial Vehicle with Dual Frequency GPS and Post Processing Kinematic Technology Gilles Albeaino Intelligibility in Transitional Spaces of Healthcare Facilities Mahshad Kazem Zadeh Ecological Performance Optimization of Green Building, Carbon and Water Footprint M aryam K ouhirostami Blockchain a nd the Built Environment: Automated Design Review Process Shriraam Ravindran Assessing the Challenges Faced with the Adoption to an Innovative Approach to Improve U.S. Residential Construction Humberto Cantu

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Future of Information Exchanges and Interoperability 9 Keynote : The Future of Open Data for the Built Environment Dennis Shelden, AIA Ph.D. Associate Professor at Rensselaer Polytechnic Institute Director of the Center for Architecture S cience and Ecology An expert in applications of digital technology to building design, construction and operations, he has worked in professional practice, technology entrepreneurship and academia across architectural, building engineering and computing di sciplines. He has lectured and w ritten widely on topics of computational applications to architecture and b uilding industry transformation. He was Associate Professor of Practice in Design Planning from 2005 2016, and has taught at IDEAS Studio and the Southern California Institute of Architecture. Dr. Shelden has been an entrepreneur and innovation leader in several professional organizations and capacities. He led the development of architect Frank tal practice as Director of R&D and Director of Computing. He then co founded Gehry Technologies, serving as Chief Technology Officer on the development of several software products and Project Executive on numerous groundbreaking building proj ects. He has previously worked with diverse architecture, engineering and technology firms including Arup, Computation Bureau. He holds a BS in Architectural Design, an MS in Civil and Environmental Engineering, and a PhD in Desi gn Computation from MIT, and is a licensed architect in the State of California . Abstract: After a lengthy period of slow adoption, open data standards are entering a period of increasingly accelerated development and application. New use case s integratin g cloud connected services are appearing in academia and industry. A steady influx of new startups is eclipsing the historical dominance of major software vendors as the exclusive purveyors and gatekeepers of information interoperability. These trends are occurring in parallel with a rapid expansion of interest and investment in the built environment by the tech and venture communities, as well as in house integrated system development initiatives by major architecture, engineering and construct ion firms. T his keynote presentation provides an overview of industry trends in information exchange, recent developments in the building information open standards communities, and work being conducted at in academia with the goal of establishing a vision for the tra jectory of open data platforms for the building industry and the their potential impact on the practices of building design, delivery and operations.

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Future of Information Exchanges and Interoperability 10 Web Based Management of Building Data: An LBD Approach Pieter Pauwels, Ph.D. Associate Profes sor, Department of the Built Environment at the Eindhoven University of Technology Abstract: Building Information Modelling (BIM) shifted construction industry to an era of digitization. With the Industry Foundation Classes (IFC), a strong standard has bee n put forward for interoperability, data exchange, and collaboration. Yet, as digital tools moved to the web, and changed into an environment with small data exchanges, fast web services, query engines, mobile devices, and distributed data management in th e cloud, construction industry needs to evolve even further into a web based industry (BIM L evel 3 and Digital Twins). Our main industry standard, IFC, needs to evolve into a modular and web native data standard that actively promotes and enables such dist ributed, community based, and web based data exchange. Linked (building) data makes that pos sible, yet a lot more other tooling is needed, including code libraries that bring building data directly in developer hands for creating a web based world of build ing data. 1. Can interoperability be enabled by changing technology? 2. Can we build a BIM a uthoring tool in a web browser? 3. Centralized storage or data distribution? Functional Modeling and Reasoning in Building Design Andres Cavieres, Ph.D. Assistant P rofessor, College of Architecture, University of Oklahoma Abstract: Contrary to some assumpt ions, BIM does not provide formalisms to represent functional aspects of design in a machine readable way. For instance, the description of functional requirements still follows a text based, document centric approach, despite progress in various database and semantic web implementations. This situation limits the scope of semantics required to support more effective interoperability and automation in building design . Part of the solution certainly involves the development of an ontology of functions, but t his problem is far from trivial. An entire line of research in Artificial Intelligence and Applied Ontology has been devoted to this issue for more than two decades . So, what are the most promising efforts made in allied fields, and what can we learn from them to improve our own models and standards? Semantic Interoperability and Semantic Technologies at a Crossroads. Jack Hodges, Ph.D. Siemens Corporate Technology, Artificial and Human Intelligence Group Abstract: We report on a project to develop round t rip interoperability between the grid utility and building management systems (BMS), and between buildings running heterogeneous management systems, which have trad itionally been information silos. The approach is based on the semantic integration of energ y and building information models with a common, or system -

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Future of Information Exchanges and Interoperability 11 agnostic, semantic layer. Standards tend to have a very narrow focus of applicability, so growing a syste m agnostic domain model involves the integration of several standards (in this case FSGIM, O penADR, IFC, SAREF, QUDT, SOSA, NIST Tariff, and BRICK) into a cohesive model. The resulting information layer provides a foundation for round trip translation, val idation, logic, and reasoning, and is part of a cloud based platform that provides a messagi ng hub. The approach is currently being tested in a pilot study with 23 buildings in the two primary California power utilities, PG&E and Southern California Edison . 1. The value of semantics has been demonstrated time and again but is nowhere near ready for widespread adoption, why? 2. Because the experts in the field are still developing ad hoc ontologies to solve niche problems => We need an approach, such as building s tandards as ontologies and integrating them into domain models, that will bring industry ado ption . 3. Because the experts in the field have no common best practices for either design or implementation that would allow even other ontologists to read, understan d, and appreciate an ontology => We need to develop best practices guidelines and make it easy to a dopt and enforce them . 4. support semantic application development/deployment by subject matter experts or lay de velopers => develop them and make them available . 5. Because after so many years we still have no trie d and true way of finding/discovering ontologies and knowing whether they are applicable to a particular application . 6. Because we still believe that we can, o r should, implement ontologies as blobs rather than in a layered manner that will produce the most reuse => adopt the OOP approach to encapsulation . B lockchain and the Built Environment: Automated Design Reviews Shriraam Ravindran PhD Student, School of Ar chitecture, University of Florida Abstract: Blockchain is a technology concept that originated from the first cryptocurrency known as Bitcoin and was soon noted to have a much wider range of applications beyond serving as the platform for digital cryptocur rency. A blockchain (BC) is essentially a decentralized and an immutable ledger that records every transaction made in the network. The implementation of decentralized technology in any industry would result in augmented security, enforce accountability, a nd could potentially accelerate a shift in workflow dynamics from the current hierarchical structur e to a decentralized, cooperative chain of command by encouraging trust and collaboration. This paper present examines the potential integration with the BIM process in advancing the automation of the design review process. Moreover, the study explores how employing distributed ledger technology (DLT) could be advantageous in the automating the design review process by reinforcing network security, providing m ore reliable data storage and management of permissions, ensuring change tracing and data ownership . The paper evaluates the potential application of blockchain technologies such as Smart Contracts in cybersecurity, data ownership, and other aspects, as we ll as enhancing the framework for automating the design review process with a demonstration using H yperledger Fabric.

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Future of Information Exchanges and Interoperability 12 1. Legal concerns: Could the efficacy and immutability of distributed ledgers warrant their implementation as binding legal documents? Are pr ivate keys satisfactory stand ins for statutory signatures? Can the elimination of the requirement and complexity of contract litigations, in fact, give rise to newer disputes? How will Smart Contracts be judicially enforced externally, and what other lega l implications/concerns would factor into implementation? 2. Implementation: For practical use in the industry, how does one address socio technological factors such as the requirement of new cyberinfrastructure installation, personnel training, existent work flow dynamics, and organizational culture, or skepticism towards blockchains? What degree of automa tion is tangible/practical as of now? 3. Scope: Which other auditing/permitting operations at present could most benefit from Smart Contract automation? What other BIM ICT applications can Smart Contracts lead to? Machine Readable Taxonomy Delivery: CSI Con struction Information Exchange (CIE), A Sole Source of Truth for Software Greg Ceton Director of Strategic Initiatives and Special Projects, Construction Spe cifications Institute 1. Construction taxonomies are present in many countries in Europe and North America and are an essential tool for project delivery and management. In the US and Canada. Delivery of information using taxonomies is nevertheless piecem eal, with variations from standard version differences, home brewed classifications, and other sour ces robbing the standard taxonomies of their advantages. 2. Delivery of information using web technologies has been available for decades, but the construct ion industry has tended to use these technologies in a product specific atomized fashion, maintaini ng the fragmentation and siloes that have been present for even longer. 3. Despite knowledge that BIM and related technologies can break down these siloes, m ost firms do not engage in regular sharing of information. There are a variety of reasons for this: standards to do so are not adopted uniformly, professional culture discourages sharing of IP, perceived cost and risk of sharing, and failure of codes and c ontracts to recognize models and structured information as deliverables, relying instead on old con tract document forms. Sharing information more freely and fully nevertheless seems like a necessary precursor to improving construction productivity. 4. Wil l a bottom up strategy, using tools already in place and used by firms, break d own one set of barriers to this change without action by government or standard contract providers? What additional functionality will help with the adoption of taxonomies and i mprovement of standard use of structured information on any given project?

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Future of Information Exchanges and Interoperability 13 Keynote: Aligning Information and Operational Technology April Blackburn, PMP Chief Technology Officer, Florida Department of Transportation April Blackburn is the Chief Technology Officer (CTO) at the Florida Department of Transportation (FDOT). FDOT is responsible for one of the largest and most extensive transportation syst ems in the nation. With 30 year s of experience, April specializes in developing and implementing technology. technology environment in direct support of the sion. She i s also responsible for the alignment of information and operational technologies within the agency. April has led the Plan, Information Technology/Operational Technology (IT/OT) Alignment, Civil Integr ated Manage ment and is the leader of the newly developed Transportation Technology Office . Abstract: journey. Not only what FDOT is doing to prepare for a mor e connected, technology rich future, but how to leverage that same technology and reap the benefits from the data. Our goal is to be a data driven organization and utilize fully the asset of data throughout our business. I plan to cover our organizational ch anges, culture changes and governance journey. Once I see the topics from the panel, I will adjust my remarks to provide a A couple of questions fo r consideration: 1. How do we harness the best of BIM for the transportation (horizontal) industry? 2. Is this really about modeling or is it more about information management? 3. Are the greater challenges with people or technology?

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Future of Information Exchanges and Interoperability 14 Capit alizing on Auton omy, Connectivity, and other Advanced Technologies to Enhance Mobility and Safety: The I STREET testbed Lily Elefteriadou, Ph.D. Barbara Goldsby Professor of Civil Engineering, UFTI Director Abstract: This presentation will discuss the I S TREET real world testbed which is being developed in Gainesville, FL in collaboration with the Florida Department of Transportation and the City of Gainesville. Several infrastructure projects are underway or planned for deployment, including an autonomous shuttle which w ill operate in the downtown Gainesville as part of the Regional Transit Service (RTS). There are also several research projects underway which develop and evaluate sensors, apps, and other tools to enhance traffic signal control, improve sa fety for pedestr ians, bicycles, and scooters using connectivity, and to develop a comprehensive data analytics platform, among others. 1. How do we maximize market penetration of connected vehicle technology, in order to maximize the benefits of connected vehicles? 2. How do we best inform transportation professionals and the general public about the (realistic) potential of advanced transportation technologies? 3. As a traveler/driver, what are your mobility/accessibility/safety needs which are not bei ng met now? SunTrax: Accelera ting the Future of Transportation Josh Pedersen, PE Senior Project Manager, HNTB Corporation Abstract: This presentation will provide an overview of the new SunTrax Connected/Automated Vehicle testing facility being developed b se. Topics covered will include the purpose and mission of the facility, the importance of testing overall and closed course testing in particular, the process of designing CAV focused testing infrastructure, and where SunTrax and the State of Florida fit in the landscape of CAV deployments to come. 1. Most of the major OEMs are headquartered in Michigan. Is SunTrax / Florida an attractive location for major auto manufacturers? 2. Connected and autonomous vehicles are already on publ ic roads both nationally and internationally, including here in Florida. Why then are proving grounds and test facilities like SunTrax still needed? 3. Considering how rapidly CAV technologies seem to be changing and evolving, how did you know what testing in frastructure to build? Self D riving Vehicles and Advanced Mobility Transportation Options Dean Bushey, Ph.D., Col(r) US Air Force Advanced Mobility Consultant, Dean Bushey Enterprises; General Manager, Voyage Auto Abstract: Self Driving vehicles offer the promise of safer roads, less congestion, environmentally friendly transportation, and mobility options for those who need it. What is the state of the industry?

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Future of Information Exchanges and Interoperability 15 What are the challenges? What is the timeline and how will this impact planning across multipl e industries? Migrating from 2D Plans to Digital Twins Mark Lemieux, PE Technologist, HNTB Corporation Abstract: Will provide a quick look at how 3D models are created and used through the various phases of horizontal (e.g. road/rail) construction project. Will discuss some challenge s and limitations of model development as we strive to leverage digital twins for managing assets. 1. How does the development of IFC schemas impact how 3D attributed model data is continually developed/updated through the design construction inspection > Operation lifecycle? Do we expect that subsequent teams will be able to update/embellish previous developed work? 2. How to influence the software vendors to fully embrace IFC? Concerned that some vendors will resist as the ta xonomy is still being develop ed? Is it "all or nothing"? 3. As model content is shared between different software systems, how to know that data is being exchanged correctly between software? For instance, even with simple data we use s where surfaces are triangul ated differently or where alignment stationing is calculated differently. Life Cycle Information Models for Highway Infrastructure Amlan Mukherjee, Ph.D., PE Associate Professor, Dept. of Civil and Env. Engineering, Michigan Technological University Abstra ct: In the field of pavement design and construction, significant progress has been made in the last decade through a participatory stakeholder driven technical working group led by the Federal Highways Sustainable P avements Program. A pavement life cycle assessment (LCA) framework (Harvey et al. 2016) has been developed, and the pavement materials industries have also developed Environmental Product Declaration (EPD) programs. This study reports the next step in this process: the development of standardize d data structures to reflect the unit and product system processes, and map them to consistent background databases for conducting pavement LCA. In addition, a pavement specific pedigree matrix based on Edelen and In gwersen (2016) was developed to characte rize data quality, and it was used to review if the background data quality was 'sufficient and appropriate'. Therefore, the goal of this research is to ensure consistency, transparency and reliability of the collect ion, reporting and use of datasets for p avement LCA. This research is timely given legislative mandates such as the Buy Clean California Act (2017) that requires eligible construction materials to produce an ISO 14025:2006/EN 15804:2012 compliant EPD at th e point of installation, for all publicl y procured projects. It is significant as it lays the foundation for the long term success of using EPDs to inform pavement design, procurement and construction decisions. 1. How do we integrate BIM information model s with LCA information models? 2. As LCA is becoming part of public procurement how can we learn from lessons in BIM implementation? 3. What standards can be applied besides the ISO 14000 series to integrate LCA with BIM?

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Future of Information Exchanges and Interoperability 16 Keynote : AEC Tech In novations: Technology | Implementation | Outlook for the Future Ron Perkins , PMP President, Jobsite Tech Group Ron Perkins is the president o f Jobsite Tech Group and has been an active member of the Associated General Contractors (AGC). His experience in the AEC industry goes back more than three decades , and has led sales and business development initiatives for firms such as Construction Market Data (CMD), Architects First Source and Autodesk; consulted for HP, SYNNEX, Infotech, Samsung, Dropbox, ARCO and spent many years in SaaS, EDM, BIM and VDC solutions. He has been a speaker or panelist at numerous indus try events including Autodesk University, ENR FutureTech, CMAA, FTBA, TRB, Meridian, Oracle, AIA, ABC, AGC IT Forum, AGC BIM For um, CSI, and others. He is an active member of several Transportation Research Board (TRB) committees and Advisory Board Member on National Science Foundation (NSF) funded technology research grants. He has been published in Construction Executive, Design Intelligence, Florida Transportation Builder, and a number of other industry publications. Ron co developed the Jobsite Tech University sales training program and authored The PULSE of Jobsite Tech for SYNNEX. Ron is also a former US Marine serving as an Assault Amphibian Crewchief of the LVTP 7 (YAT YAS). Abstract: The session will evaluate the current use of emerging technol ogies and explore research and statistics that point to the future trends of tech adoption across the AEC industry. Technology such as UAV, Laser Scanners, AR, VR and AI are at the forefront of the adoption curve. We will review real project scenarios an d discuss product development paths of some of the leading technology providers to the industry. Leveraging these technologies is critical because of the accuracy and efficiency they bring to the project. Incorporating this data in the project workflow w hile maintaining integrity is only the first step in the process. Maintaining the data and adding functionality to manipulate o r run analysis is the stage we will further explore during the session. 1. Identify data acquisition processes that will see the gr eatest benefit when embracing emerging technologies 2. Examine the most common use cases for technology adoption across various dev ices. 3. Suggest best path forward for organizations considering adopting new technology and best practices designed to streamline data acquisition .

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Future of Information Exchanges and Interoperability 17 Digital Workflow in a Federated Model Environment Leif Granholm Senior Vice President and BIM Ambassador Stru ctures Division, Trimble Solutions Corporation Abstract: The current BIM practice is based on a federated model where every discipline and often each phase within a discipline create their own self contained models that are then combined in different w ays together for coordination and other purposes. This c oncept can be successfully enhanced with linked data to provide a comprehensive workflow support with provenance and metadata management, natural data ownership and governance, and collaboration based on change propagation downstream and change requests up stream. This work is based on two research projects with Trimble, Aalto University and VTT as their main parties. In this paper we will present the main findings and concepts developed in those projec ts. Linked data is used to link object instances in diff erent models and the many of the links can be created automatically as byproduct of design progression using new paradigm for BIM software that will be presented in the paper. BIM Framework for Sustai nability in Saudi Arabia Fatma Hasanain Ph.D. Student, S chool of Architecture, University of Florida Abstract: This presentation will provide an functions of BIM could be utilized to implement sustainable des ign principles in new and existing structures in Saudi A rabia by exploring the nature of the relationship between BIM platforms and sustainability. Due to the lack of a national rating system a BIM framework will be used to achieve the envisioned sustainab ility goals and implement sustainable design principles in Saudi Arabia. Digital Twins of Urban Buildings with a Data and Computing Web Platform Xuan Luo Building Technology and Urban Systems Division, Lawrence Berkeley National Laboratory Abstract: This d emo will showcase an open and free data and computing we b platform CityBES, which uses CityGML based 3D city models, simulates building performance to identify retrofit measures that can cut building stock energy use by 50%, and evaluates city wide PV po tential. CityBES visualizes 3D GIS integrated building p erformance in dozens of metrics (e.g., energy, water, demand, cost, GHG, savings, and regulatory compliance status) for each building at urban scale. The demo intends to introduce some of the applicat ions and workflows of CityBES at the data level, regardi ng data integration, visualization, and utilization. Functionalities include integrating building data from different resources to compile and visualize building performance related database, and to c onstruct city scale building energy models. Utilizing th e models to link and interact with district utility data and sensor network data, the platform is able to simulate and predict the spatiotemporal energy fluctuations of cities.

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Future of Information Exchanges and Interoperability 18 Ontology Based Building Information Model Design Change Visualization Ning Wang Ph.D. Student, M.E. Rinker, Sr. School of Construction Management, University of Florida Abstract: The use of Building Information Modeling (BIM) has become popular in the architectural, engineering, construction and Operations (AECO) industry, and BIM ha s been used in the lifecycle of projects. As more data is added to a BIM model, the complexity and data volume of the model increases. Further, many design changes are made to a building information m odel during design and construction phases, and it is di fficult to extract and visualize the changed objects. Research on the use of ontology in BIM is also limited. The purpose of this study therefore is to use an ontology to visualize revised objects in BIM models. This research uses the Industry Foundation C lasses (IFC) format, a widely supported open standard for building information models. The changed objects in the BIM model are extracted by comparing the revised model to the original model, and a mo del report of the design change is provided. A prototype program using a sample IFC model is developed to validate the system. The results indicate that the proposed methodology is valid for the extraction and visualization of design changes in BIM models. Semantic Web for Knowledge Based Energy Management and User Engagement in Existing Buildings Hervé Pruvost Computational Analytics, Fraunhofer Institute for Integrated Circuits IIS Abstract: The purpose of the presented work is to propose a novel ICT met hod for supporting energy efficient operation of buildin gs by the means of semantic web technologies. So far, many developments and research have led to enhanced building automation systems embedding data analytics algorithms and performing energy optimize d building system control. The presented approach tries to bring a different and complementary added value to such systems through semantic modeling of building energy systems and knowledge reuse. It aims at providing an additional analysis layer compared to traditional algorithmic and model predictive approach es in which a semantic analysis and interpretation of the operational state of a building is executed. This is based for a part on building data gathered during its operation through a monitoring syst em. For another part, it relies on information contained in initial BIM compliant building design models. Moreover, in contrast to the classical goal of building automation which tends at achieving a fully automated and autonomous energy management, the me thod relies on the interactions between the building and its users. In particular, it aims at increasing the awareness and engagement of building users with regards to their habits about building energy use. For that purpose, it implements a knowledge base of energy conservation measures that prescribe building control actions and handlings that a building user or a facility manager may execute for saving energy .

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Future of Information Exchanges and Interoperability 20 Functional Modeling and Reasoning in Building Design Andres Cavieres , Ph.D ., 1 Charles Eastman , 2 and Russell Gentry , Ph.D. 3 1 College of Architecture , University of Oklahoma ; e mail: andres.cavieres@ou.edu 2 College of Design, Georgia Institute of Technology; e mail: eastman@design.gatech.edu 3 College of Design, Georgia Instit ute of Techn ology; e mail: russell.gentry@coa.gatech.edu ABSTRACT B uilding design requires different types of knowledge . However, only structural knowledge is explicitly represented in current Building Information models . Other types of knowledge , such as those related to functional and behavioral aspects of design, remain tacit or described in ad hoc terms by relying on structural properties as representati on al surrogates ( e.g. geometry). T h e lack of a formal, model based representation of functional know ledge limits the scope of semantics required to provide better computational support in performance based building design. To address this problem, the rese arch proposes the development of a representational framework for the functional and behavioral char acterization of building elements based on the Functional Representation (FR) schema , and its formalization under the DOLCE foundation ontology. Part of thi s formalization has been translated into the Web Ontology Language to explore capabilities of DL rea soners to support inference of functional interdependencies affecting performance . An overview of the main theoretical background adopted is provided. Preli minary results and future lines of research are also presented. INTRODUCTION Design, construction and operation of buildings are complex activities, often requiring the collaboration of experts from multiple disciplines, who must work together to ensure the satisfaction of different functional requirements, at specific levels of pe rformance. Developme nts in Computer aided Design, and more recently in Building Information Modeling have greatly facilitated these processes of collaboration, by allowing the creation and exchange of design information among different design and analysis applications with in creasing levels of automation. Although these developments have already provided major benefits to the AEC industry, some fundamental problems persist which limit the potential of BIM to better support interdisciplinary collaboration i n the delivery of hi gh performance buildings. In particular, the semantics of building information models currently available do not provide formal, machine readable characterization of functional and behavioral aspects that are the backbone of the collabo rative process. Inde ed, an explicit, shared understanding of these aspects namely, what a given building element does (i.e. its function), and how it is supposed to work (i.e. its behavior) is precisely what informs the process of collaboration, especi ally in the context of systems integration, when multiple and often competing sets of performance requirements have to be evaluated and satisfied concurrently. When such a shared understanding is lacking, evolving behavioral interactions between different building subsystems may go unnoticed, eventually leading to functional conflicts and poor levels of performance that are usually not caught until very late in the delivery process. From a representational perspective, part of the problem stems from how fu nctional and behavio ral aspects are defined within the conceptual ization of BIM applications, including IFC and associated standards and

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Future of Information Exchanges and Interoperability 21 classification systems (e.g. COBie, BPie, OminClass, etc.) . In general, functions and associated performance criteria are described in ad h oc, tacit fashion, by relying either on structural entities as representational surrogates (e.g. geometric properties), simple value types or text without formal semantics . Th is is problematic for several reasons, including the fact that traceability of fu nctional interdependencies needs to be performed without computational support (Kiviniemi 2005) . Besides being time consuming and prone to error, the use of informal, document centric representations le ads to different types of inconsistencies, especially when both functional requir ements and design alternatives change constantly, and the consequences need to be tracked down and propagated manually across various domain models (Kamara, Anumba et al. 2002) (Qamar, Paredis et al. 2012) . Furthermore, in order to capture the dynamic, cross cutting structure of behavio ral interactions and functional interdependencies, multiple functional viewpoints are required at different levels of abstraction (Eastman 1994) . Current BIM applications however lack the formal semantics needed to meet these modeling requirements. Among the main reasons, the following theor etical issues are worth mentioning: Partial ontological commitment: The lack of formal semantics is result of limited ontological commitments implicit in the conceptualization of building information models. This limitation restricts the set of ontologica l categories and relations available to formally describe phenomena of interest, particularly time dependent phenomena that need to be captured by different functional viewpoints (Smith 2012) . Reliance on extensional definitions: This problem was first analyzed by Borgo et al. (Borgo, Sanfilippo et al. 2015) . In this work, the ontological and computational implications of extensional definitions are discussed, especially in relation to the lack of consistent criteria for the classification of design entities based on prescription of normative property sets. To address these problems, a formal, explicit representation is proposed to enable a machine readable specification of functionality with associ ated performance criteria. This explicit representation should cover both the 'demand' side, concerned with the description of functional goals and requiremen ts, as well as the 'supply' side, concerned with the behavioral characterization of building eleme nts that may contribute in the satisfaction of such goals and requirements. In order to enable multiple functional viewpoints, and inference of cross cutting elements with participation in a given functional requirement, the definition of functional entiti es should be made intensionally , based on conjunction of constraints that need to apply under certain context of use. This would allow dynamic classification of elements playing a functional role in a requirement, rather than relying on normative model vie w definitions that may be too brittle or incomplete to deal with the iterative and often uncertain structure of design processes. SPECIFIC PROBLEM: INFERENCE OF ASPECT SYSTEM S The research proposes the development of a representational framework for the f unctional and behavioral characterization of building systems and components. A main goal of this framework is to support the incremental inference of buildin g elements (i.e. structural entities) that participate in the satisfaction of different functional requirements. In this research, the set of structural entities that participate in the satisfaction of a functional requirement is considered a special type of aggregation abstraction called the Aspect System of the functional requirement. This abstract ion has been originally proposed by Augenbroe in the context of performance based design, with the goal of providing a more robust system theoretical framewor k for the integration of design and analysis applications, particularly regarding the use of simul ation models for p erformance evaluation under

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Future of Information Exchanges and Interoperability 22 uncertainty (Augenbroe 2011) . The key idea behind the notion of Aspect System is th e fact that there is never a fixed, one to one mapping between a functional requirement and a building technical sub system. Instead, the satisfaction of any give functional requirement, specially at certain levels of performance, can only be achieved by t he participation of multiple elements , possibly from multiple technical sub systems, and from different levels of the compositional hierarchy. This implies no t only more complex mappings from requirements to technical sub systems, but also that such mappin gs change overtime as the design requirements and design alternatives co evolve. From a modeling perspective, this means that the specification of input mod els for performance evaluation need s to be richer and more flexible than usually assumed in the de finition of conventional model views . While the aggregation of building elements that are related by a common purpose or function is supported in in theory by IFC with entities such as IfcGroup , and its specialization IfcSystem , these modeling constructs a re more like general containers , la cking formal criteria for class membership. In particular, the ad hoc , extensional nature of these functional aggregations makes it difficult to implement automatic procedures for dynamic inference of Aspect Systems. A t a more fundamental level, the prob lem lies on the fact that reasoning capabilities required need to operate under conditions of model incompleteness, which are intrinsic to the very nature of the design process. For this reason, it is necessary for a fun ctional modeling framework as propos ed here to operate under an Open World Assumption (OWA) paradig m , as opposed to the Closed World Assumption (CWA) underlying relational models such as IFC. This condition is key to support the types of quer y required to capture the intensional semantic s u nderpinning the inference of Aspect Systems, along with the set of potential behavioral interactions and functional conflicts that can be derived from such inference. The first type of query can be exemplified by the fol lowing expression : Given a required function f and a design model a , return the set of building elements from a with functional participation in f . This is the most general form of the query, for which the Aspect System of function f is inferred based on the participation relation of its members that is not qualified in positive or negative terms (i.e. the required function is affected in a positive or negative way). The second query involves the inference of an inverse relationship . T hat is, to return th e set of functions a given building element participates in , either nominally or as result of a behavioral side effect. This can also be described as the set of functional roles played by a building element by virtue of one of its inten ded effects, or unin tended side effects : Given a building element a 0 , proper part of a design model a , return the set of functions F = {f 1 , f 2 f n } in which a 0 has some functional participation. From these two queries , more specialized forms can be d eveloped, by using a dditional constraints in the query expression. In any case, a building element inferred as member of several Aspect Systems, is deemed to co participate in the satisfaction of the different functional requirements (one for each Aspect S ystem). This inferen ce provides not only the basis for the identification of possible behavioral interactions and functional conflicts, but eventually more complete input models for performance evaluation, as well as trade off analysis for decision making among competing desi gn alternatives.

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Future of Information Exchanges and Interoperability 23 Currently, there is no means of formulating such type of quer ies in BIM applications , unless informal participation relations are hard wired into the models . As discussed previously , providing a timely answer for this type of query during different phases of the design process is relevant because it would allow to convey the rationale for previous design decisions, in such a way that potentially problematic design changes could be avoided or properly handled. Furthermor e, characterization of Aspect Systems by inference of implicit functional relationships would allow automatic generation and update of input models for analysis applications that otherwise would remain brittle or incomplete. THEORETICAL BACKGROUND AND PROTOTYPE IMPLEMENTATI ON The functional modeling framework proposed is grounded on the study of several theoretical models of functional representation and reasoning , developed in the area s of Artificial Intelligence and Engineering Design , as well as more recent efforts toward s the formalization of functional meaning in the field of Applied Ontology . Based on the analysis of theoretical models addressing specifically the representation of different functional viewpoints at different levels o f abstraction, two schemas have been identified as particularly relevant for this research. These include the Structure Behavior Function schema (Goel 1992) , and the Functional Representation (FR) schema (Chandrasekaran and Josephson 2000) . The latter has been formalized under the DOLCE foundation ontology using First order Logic (Borgo, Carrara et al. 2009) . This formalization, called in this research DOLCE FR, provides the foundation for the implementation of a proof of concept for the proposed functional modeling framework. Specifically , the implementation involved the tra nslation of a subset of DOLCE FR axioms from First order Logic into Description Logic using OWL DL, in order to take advantage of available DL reasoners. Moreover, this choice was made to support future integration with IfcOWL specification under developme nt (Pauwels, Törmä et al. 2015) . The following subsection outlines the ontological commitmen ts with main categories from DOLCE, a subset of DOLCE FR axioms and the formalization of the notion of Aspect System based on such axioms. DOLCE CATEGORIES AND DOLCE FR AXIOMS The adoption of DOLCE as ontological framework allows an extended set of ontol ogical commitments beyond those impli cit the conceptualization of BIM models. These commitments are grounded on a robust formalization of categories and relationships, along with constraints on how these relationships can be established. Specifically, DOLC E provides the category of perdurants , which allows explicit description of time dependent phenomena associated with functional and behavioral aspects of design. This in turn allows the specification of participation relations to be established between thi ngs such as physical or spatial eleme nts, with functional phenomena described by perduran s t . Moreover, specific relationships between perdurants are also supported, such as causality and composition relations. The former allows to describe notions of causa l pre conditions and post conditions, normally used in the specification of functions. Composition relations between perdurants in turn are useful to formally capture notions of functional decomposition. Figure X summarizes the ontological commitments in D OLCE, in comparison with the implicit commitments underlying conceptualization of BIM models (first in the left).

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Future of Information Exchanges and Interoperability 24 Figure 1 . Partial ontological commitments of BIM models (first on the left). Extended ontological commitments of proposed framework based on DOLCE (cen ter and right) . These additional ontological commitments, along with the formal criteria for the definition of ca tegories and relations in DOLCE provide the basic vocabulary for the formalization of the Functional Representation (FR) schema adopted in thi s research. In particular, the FR notions of 1) function as effect ; 2) function as a role ; and 3) function as beha vioral constraint introduced in FR are formalized in DOLCE FR using different participation and composition relations. This in turn allows the formalization of functional viewpoints and levels of functional abstraction following the notions of mode of depl oyment , device centric and environment centric functions proposed in the FR schema. All these definitions are used in the formalization of Asp ect Systems, providing the semantics required to enable the queries described above, which constitute the core of the functional modeling framework presented here. FORMALIZATION OF ASPECT SYSTEM UNDER DOLCE FR The meaning of an A spect S ystem is formalized primarily based on the axiomatic definition of environment centric function ( EnvFunc(b 0 , b 1 , a , a , e) , and a small set of auxiliary definitions dealing with participation, causality and parthood (Borgo, Carrara et al. 2009) . The following listing provides a preliminary, general formalization us ing an equivalent class axiom in OWL DL. IN the formalization, the environment centric is referred to as _E_function. Listing 1 : OWL DL Equivalent class axiom for an Aspect System. General form. Different types of structural and behavioral constraints, as well as constraints on participation, causality and composition, can be added to this general definition of an Aspect Syst em, either by changing the object properties types involved (i.e. object relations), or by adding extra logical connectives. This is illustrated in the two queries below, which provide variations of the most general form . The example is based on a case

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Future of Information Exchanges and Interoperability 25 stu dy developed for this research, dealing with the design of photovoltaic r acking systems for commercial building rooftops. Specifically, each variation specifies different constraints for the inference of the Aspect System associated with the functional req fe7 . 1 _maintain_ position , which along with fe7 .2_maintain_f orm are sub function s of the environment function of maintaining overall s tructural integrity of the PV racking system. Figure 2 . Variations of the gene ral axiom of Aspect System (in Protégé) . Additional constraints reduce the set of inferred elements with functional participation. T his type of PV racking system usually relies on a combination of ballast and wind deflectors to maint ain its structural form and position, without any penetrati ng connection into the roof. For this reason, weight per area and aerodynamic drag coefficient are important behavioral constraints, along with friction coefficients of rubber pads used in footing s for interfac ing with r oof membranes. In the Figure, some of these constraints are added in the specification of queries for the Aspect System of structural position function. Co participation of inferred members in other functional requirements can be ded uced by querying other Aspect Systems. In this model, equivalent classes are used for the query, in an approach known as DL Query. However, the modeling framework also supports use of SPARQL queries.

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Future of Information Exchanges and Interoperability 26 Figure 3 . SPARQL query of Aspect System for maint enance of form function. Behavioral constraints are specified in terms of functional capabilities. Specific performance properties can also be included. DISCUSSION / CONCLUSIONS A functional modeling framework h as been implemented , based on a subset of the Functional Representation schema formalized under the DOLCE foundation ontology. The prototype implementation involved the translation of axioms from F irst order L ogic into D escription L ogic using th e Web Ontology Language OWL DL. This allows leveraging t he capabilities of available OWL DL reasoners to support the dynamic inference of building elements from different building sub systems with participation in the satisfaction of functional requirement s. Inferred building elements represent cross cutting ag gregations that explicitly capture functional interdependencies that emerge across different building components and subsystems, and that are relevant for multiple criteria performance evaluation. Suc h an aggregation, called the Aspect System of a function al requirement, is considered a necessary abstraction to provide better computational support, particularly in collaborative tasks involving design analysis integration, conflict resolution, trade off analysis and decision making. Envisioned i nference ca pabilities of the proposed functional modeling framework are based in part on information asserted during the design process in different BIM applications. However, the current implementation does not deal with such type of integration, relying instead on a simplified OWL representation of hypothetical design models. The focus so far has been on the formulation of functional and behavioral models as an independent layer of semantics, that could be adde d on top of different building models. In this regard, the development of the IfcOWL standard offers the most direct path towards the integration of the proposed functional modeling framework with different BIM applications. This would allow to study issu es of modularity and scalability of functional models, a long with soundness and completeness of inferences dealing with real world design models and use case scenarios. R EFERENCES Augenbroe, G. (2011). The role of simulation in performan ce based building. Building Performance Simulation for Design and Operation. J. L. M. Hensen and R. Lamberts, Spon Press: 15 36. Borgo, S., M. Carrara, P. Garbacz and P. E. Vermaas (2009). "A formal ontological perspective on the behaviors and functions of technical artifacts." Artificial Intelligence for Eng ineering Design, Analysis and Manufacturing: AIEDAM 23: 3 21. Standards: An Initial Study of IFC. Ontolog y Modeling in Physical Asset Integrity Management. V. Ebrahimipour and S. Yacout. Cham, Springer International Publishing: 17 43. Chandrasekaran, B. and J. R. Josephson (2000). "Function in Device Representation." Engineering with Computers 16(3 4): 162 17 7. Eastman, C. (1994). "A Data Model for Design Knowle dge." Automation in Construction (3): 135 147. Goel, A. K. (1992). "Integrating case based and model based reasoning: a computational model of design problem solving." AI Mag. 13(2): 50 54. Kamara, J. M ., C. J. Anumba and N. F. Evbuomwan (2002). Capturing Client Requirements in Construction Projects, Thomas Telford Publishing 200. Kiviniemi, A. (2005). Requirements Management Interface to Building Product Models. Doctor of Philosophy Dissertation, Stanfo rd University.

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Future of Information Exchanges and Interoperability 27 Pauwels, P., S. Törmä, J. Beetz, M. Wei se and T. Liebich (2015). "Linked Data in Architecture and Construction." Automation in Construction 57: 175 177. Qamar, A., C. J. J. Paredis, J. Wikander and C. During (2012). "Dependency Modeling and Model Management in Mechatronic Design." Journal of Co mputing and Information Science in Engineering 12(4): 041009 041009. Smith, B. (2012). "Classifying Processes: An Essay in Applied Ontology." Ratio 25(4): 463 488.

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Future of Information Exchanges and Interoperability 28 A Graph Database and Query Approach to IFC Data Management Zhengyang Chen 1 , Yiying Pu 2 , and Dennis R. Shelden 1 1 S chool of Architecture, Georgia Institute of Technology, 245 4 th St NW, Atlanta, GA 30332, USA 2 Sc hool of Computational Science and Engineering, Georgia Institute of Technology, 266 Ferst Dr., Atlanta, GA 30332, USA Keywords: Ind ustrial foundation class, Graph database, Database management systems OVERVIEW The Industry Foundation Class (IFC) Model i mplemented by schema and data format definition in EXPRESS language is the industry standard for open data modeling and exchange. Th is data model, based on E R model with deep object class instance hierarchy for both elements and relationships has presen ted challenges in implementing scalable database approaches for managing and serving BIM objects while maintaining requisite relatio nships necessary for inferring relationships across the complex E R network. Alternative models based on alternative data enc odings with associated data topologies, database strategies and supporting tool sets such IFCXML, IFCJSON and RDF/IFCOWL have been p roposed, with associated affordances and limitations in terms of semantic richness, validation and querying capability and s calability. Graph databases are a recent development in modern databasing technology that is gaining prominence in the broader compu ting community. Graph databases promise general support of complex entity relationship networks in a manner that supports ri ch semantic inference at scale. Consider those limitations stated above, this paper propose a method of database mapping between IFC Model to Graph database, and presents opportunities for drawing on graph querying capabilities to develop inferences about the semantic relationships among objects in IFC BIM models. The implementation and examination of this mapping is achieved by transl ating the IFC data and then store them into Neo4j, a commonly used graph database application. As part of this translation, broadly available IFC to XML conversion utilities we re used to convert the BIM software output to XM. A python based parser was deve loped and used to parse the IFC component information and generate a Cypher script the structural language for graph database construction.. This Cypher script encapsulati ng the IFC E R model is imported into the Neo4j graph database in batches with Neo4j Shell. By implementing this mapping method, we can benefit from the flexibility of relationship management in graph database, as it provides the interface for dynamic relationship inserting, updating, deleting and modifying. Significantly, user defi ned queries ca n be constructed for graph database, similar to the ambitions of the IFCOWL approach. Those cascaded queries or relationship path finding which need to self construct the data graph algorithm in normal SQL database are no longer an issue her e since they are embedded in graph database and have optimized querying performance. Moreover, by executing this mapping rule application we keep the relationships which is essential during data exchange, and provides capability to migrate the model to oth er technical software which provide interface for graph database. Further work

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Future of Information Exchanges and Interoperability 29 suggests that advanced algorithms and techniques network analysis algorithms in machine learning could be developed via the node edge model provided by the graph database. METH ODOLOGY & APPLICATION FUNCTIONALITY The goal of the proposed work flow is to utilize the flexibility of transformation between SQL and NoSQL database and typically trying the possible schema and data exchange in between. To implement this the paper foc uses on the scope of making mapping rules to extract schema definition in IFC(national standard database model for BIM) EXPRESS G schema and data from IFC file into Neo4j Graph database. It is an urgent need for BIM to solve the data exchange and interoper abil ity problem. Chuck Eastman, stated in recent years that BIM are facing five main limitations during data exchange, among which the information loss on relationship between IFC entities is expected to be solved as an important issue. Hence, by proposing thi s workflow, a possible approach on solving this problem can be explained by utilizing graph database as a media for IFC data exchange. Automatic converting from IFC file exported from BIM project instances in commercial BIM to Neo4j database will be th e ma in functionality of the application. By using this application, we can store IFC data as an option for further exchange into other software. Typical user of application based on this work flow will mostly be the engineers and BIM project managers of t echn ical side in AEC industry. Contemporary practice in BIM database today are mostly functions and plugins embedded in commercial BIM software like project schedules in Revit, however, these functions are mostly based on relational database. The normal qu ery approaches at the back end by writing SQL can also be achieved by NoSQL languages, specifically, graph database queries with more flexibility, e.g. the most familiar SQL query to us, namely, SELECT FROM WHERE query series, can be written in typical graph d atabase query called Cypher in MATCH WHERE RETURN query series. Moreover, by mapping IFC data into graph database we keep the relationships whi ch is essential, and provides capability to migrate to other technical softwares. Another groups of typical user will be BIM developers, as recent years more and more researchers and developers focuses on web based BIM application. The robust information s tored in graph database provides an option for them to choose for implementing their back end. S YSTEM INTERFACE AND DATABASE DESIGN As stated before, the application of this work flow can achieve converting IFC data and manage them in graph database. With a provided IFC file as data source, the application is built to parse all the IFC component information inside I FC file and generate the Cypher script as output, which can be used for batch import in graph database application browser, namely, Neo4j browser. The output script file contains all the Cypher commands to create nodes and links, which representing entiti es and relationships in graph database, respec tively. Here, the work flow of IFC data format conversion from IFC to XML, which could be easily implemented by external libraries, will be briefly introduced here, rather than go into detailed discussion in se ction 5 of the paper. Such format transformati on process is actually realized by converting the original file to XML file. The IFC file is converted into well structured XML file by IfcConverter, the application included in the open source software librar y called IfcOpenShell. The IFC objects in the original file include some very fundamental

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Future of Information Exchanges and Interoperability 30 objects like the measurements, directions and basic geometry types (points, curves). This part of information is integrated in the XML file as the value of objects' a ttributes. The concise and well organized XML file helps to build a graph database without redundant and abstract information. As this work flow engaged the exchange between SQL based IFC database model to NoSQL based graph database by creating the mapping rule. Some modifications will also happen dur ing the exchange and the main change of design will be so Figure 1. P runing process of the database schema . IFC Model has a strict layered schema definiti the entities defined in higher layer schema can reference the entities in the same layer or lower layer schema, and those entities remain in the lowest layer schema(cal cannot be indepen dently exist. Recall the content in class we can easily figure out that all entities definition in that lowest layer, are so we discovered that they usually contain one or several proper ties indicating the same kind of information type. And those supertype entities in the lowest schema layer are also well categorized. Hence, our plan is to aggregate these weak entities into proper ties and apply them to those higher layer schema entities w ho referred them. By doing this major change the amount of schema layer had reduced from 4 to 3, and hence reduce the depth of query and simplified the structure. Notice that the no entity will exi contrary, since they are of the most fundamental entities, if higher layer entities will exist, they must refer attri independent element is init ialized, resource layer entities related to them actually plays the role of attributes, thus we do not suffer information loss when pruning the lowest layer.

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Future of Information Exchanges and Interoperability 31 DATA EXTRACTION AND PREPROCESSING BIM data in common practical use are stored in forms of IFC fi les, which are already in constraints of IFC Schema definition. The IFC files are exported from Revit, where all the building information is defined by users within the graphic user interface. The I FC data files are exported from the existing BIM projects . In current stage, the files used for testing can vary from simplest building structure to other ones of a realistic construction project. The IFC schema file written in EXPRESS G is used for under standing how the IFC objects are defined. IfcConvert is ap plied to convert the IFC file into XML file. This is an application converts IFC file into several file formats. This application is conveniently used with Windows command line. To parse information from XML file, the ElementTree module is used with python to work with XML. The re module for regular expression is also applied for string modification and information filtering. COMPUTATION IMPLEMENTATION FOR MAPPING AND RELATED QUERIES Figure 2. W ork flow diagram The mapping conversion workflow is realize d mainly in two parts with three steps (see figure) The first step is to realize the converting process from IFC to XML, then the next step is generating valid Cypher commands with XML based on the mapping rule conducted, which then lead to the final step of creating the Neo4j database with Cypher scripts. The original IFC file written in EXPRESS G has the following format: every entity has its unique object ID with its type and attributes defined. The Cypher script will be generated by executing the pytho n file in command line. Then the Cypher script is use d with Neo4j Shell to import information and build the graph database. The main challenge for the automatic database generation work is making use of the XML file structure to parse information and gene rate the valid Cypher command.

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Future of Information Exchanges and Interoperability 32 Figure 3. P rogramming process of work flow . To implement this arithmetic steps needs the implementation of regular expressions, Advantages of XML files could benefit us by its initial layered structure, where we can extra ct it into tree data structure and apply traversing algorithms. the key to success is to precisely recognize the node label, and by applying reg expressions we transform them into attributes and integrate them into Cypher. Original IFC database are defined in IFC EXPRESS schema under the p rincipal of Entity Relationship describes all the data structure schema into entities. Attribute values in ER Model ar e described as entities with prope rty values. Relationships in ER name, and such entities are referencing other non relational entities and aggregate them together to represent a relations hip. Hence it is easy to transform and implement them into relational database with proper normal form applied. However, graph database does not emphasis on how to construct proper data table that enables SQL queries. On the contrary, it is looking for the sists of vertex and edges, namely, the entities and relationships. Thus the algorithmic implementation will mainly be two steps the construction of entity nodes, and the construction of relationships in between. Cypher query language for constructing nodes are described as CREATE query: Query 1: CREATE ( return _variable :Entity_name{ property_name_1: property_value] , property_name_2 : property_value, ...... property_name_n:property_value}) Where variable name are used for retu rn query result. Hence if given XML file describes an 8 inch

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Future of Information Exchanges and Interoperability 33 wall case with name, id and obje ct type, we want to construct it in graph database and return the constructed node, we can transform it according to Query 1a as: Query 1a (single entity construct ion): CREATE (n:IfcWallStandardCas e{ Name:"Wall", id:"0001", ObjectType:"Basic Wall:Generic 8"} ) RETURN n; We can also do multiple create in an integrated query to construct several entities: Q uery 1b (multiple entities construction): CREATE (m:IfcWallStandardCase{ Name:"Wall", id:"0001", ObjectType:"Basic Wall:Generic 8"} ), (n:IfcWallStandardCase{ Name:"Wall", id:"0001", ObjectType:"B asic Wall:Generic 8"}) RETURN m,n; The re lationship construction could be constructed in full path CREATE query: Q uery 2: CREATE ( return_variable_1:Entity_name{ property_name: property_value , ...... }) [return variable: relationship_name{property_na me_: property_value , ....... }] > ( return variable :Entity_name{ property_name: property_value , ...... }) This query returns a triple entity1,entity2 and relationship in between. Thus if we wanted to add write the query as: Query 2a(full pat h create query): CREATE r = ( a: IfcElementType1{ name: sample element 1 , id: 0001 }) [b: IfcRelType {name: aggregation }] > ( c: IfcElementType2{ name: sample element 2 , id: 0002 }) RETURN r; However, if we want to add relationship to existing IFC elements in the graph database, we will need to do MATCH CREATE RETURN query: Query 2b (match create return): MATCH ( a: IfcElementType1) , (b:IfcElementType2) WHERE a.id= 0001 AND b.id= 0002 CREATE (a) [r: IfcR elType{name: aggregation }] > ( b) RETURN r; Advanced query comparable to aggregated query in SQL could also be written in Cypher for further graph database maintenance and operation after the graph database is fully constructed, which is beyond this pape scope and will not be discussed. So the key to succeed the final stage of mapping method is quite explicit the first step is to traverse the XML by applying tree algorithms, parse the information of entity names and attributes by writing regular expr ession in python and overwrite them into CREATE Cypher query to construct nodes. The next step is to figure out the relationship, which need to find the entity label and index them in Ifc EXPRESS schema

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Future of Information Exchanges and Interoperability 34 definition to extract the involved relationship e ntit y, then use the regular expression to parse the relationship attributes and generate the relationship query sentence. At this step we have the option of full path create query (Query 2 a) and match create return query (Query 2b). However, in real BIM pro ject s, the model built by BIM application users are tremendous in size, and the correlated IFC data always result to be tens of thousands in entity cases, thus it is not possible to input the generated Cypher sentence by sentence. So practically we ll need bat ch import, where the generated Cypher query should be integrated into paragraph. To succeed in batch import, simply connect each sentence together is not sufficient and will potentially lead to fatal errors of creating too much wrong and duplicated rel atio ns. The reason of this kind of error is caused by MATCH queries when we proceed multiple look ups by doing MATCH queries, the return value from each sentence will be stacked and when we then do CREATE to construct relationships, it will bring in all the return value of previous MATCH as the CREATE input and build relationship between them, thus redundant and wrong relationships will be added. The key solution to this is to UNION all the MATCH CREATE RETURN queries, which will group the result at the e nd o f total batch import paragraph, rather than stack the return values sentence by sentence.The UNION can be achieved either by doing UNION ALL query or UNION query: Query 3a (union all): MATCH ( a: IfcElementType1) RETURN a.id AS id UNION ALL MATCH (b: Ifc ElementType2) RETURN b.id AS id; Query 3b (union): MATCH ( a: IfcElementType1) RETURN a.id AS id UNION MATCH (b: IfcElementType2) RETURN b.id AS id; The difference between these two is that union all will keep duplicates while union will not, thus, t o achieve batch import we will need aggregated CREATE MATCH UNION CREATE RETURN query series to succeed. To summarize, the computation process for this application is described in following steps: Step 1. import ifcConverter and transform the ifc d ata file format into xml; Step 2. traverse the xml file using tree traversing algorithm start from root, and store all children information int o tuple list ENTITIES[] ; Create batch query string list B_QUERIES[]; Step 3. for each entity E in ENTITIES[] : use regular expression to extract entity information; append CREATE query string c_query to string list C_QUERIES[]; return C_QUERIES[] ; Step 4a. for each entity E in ENTITIES[] : find its referencing entity E_ref ;

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Future of Information Exchanges and Interoperability 35 find its parent entity E_par ; find its chil d entity E_chi ; concat and store E_ref , E_par , E_chi into entities tuple E_Rel[] ; If all related entities found, go to Step 4b. Step 4b. for each relationship pair < E,E_R > (i.e. for each E_R in E_Rel ): call regular expression to traverse ifc EXPRESS schema t o find IfcRel entities, get the return value in CREATE string c_query_r ; append MATCH query string m_query to list M_QUERIES[] ; append c_query_r to M_QUERIES[] ; if ( E_R has E_Ref , E_parent, E_child ): go to Step 4a and recurse; return M_QUERIES[]; Step 5. for each quer y string CQ in C_QUERIES[] : append to B_QUERIES[]; for each two query strings MQs in M_QUERIES[] : append MQs to B_QUERIES[]; if ( MQs is the last item): break ; else append UNION query string u_query to B_QUERIES[] ; Step 6. append RETURN query string r_query to B_QUERIES[] ; return B_QUERIES[] ; A generated graph database from ifc file exported from Sample Project in Revit can be displayed in figure 4. Figure 4. G enerated graph database from R evit project .

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Future of Information Exchanges and Interoperability 36 C ONCLUSION By implementing this mappin g method, application users and developers can benefit from the flexibility of relationship management in graph database, as it provides the interface for dynamic relationship inserting, updating, deleting and modifyin g. Also, user defined queries could be constructed for graph database. Those cascaded queries or relationship path finding which need to self construct graph algorithm in normal SQL database are no longer an issue here since they are embedded in graph data base and have optimized querying perfo rmance. Moreover , by executing this mapping rule application the workflow keep the relationships which is essential during data exchange, and provides capability to migrate the model to other technical software which p rovide interface for graph database. A dvanced algorithms and techniques could also be developed based on the graph database, e.g. network analysis algorithms in machine learning could be run via the node edge model provided by it. REFERENCES Eastman C.(1 981) Database facilities for engineeri ng design, Proceedings of the IEEE, 1981(69):1249 1263 You, S. J., D. Yang, and C.M. Eastman. (2004) Relational DB Implementation of STEP based product model, in CIB World Building Congress, Toronto, Ontario, Canada Eastman C., Y. S. Jeong ; R. Sacks , I. Kaner (2010) Exchange Model and Exchange Object Concepts for Impleme ntation of National BIM Standards, Journal of Computing in Civil Engineering /Volume 24 issue 1. Nour M.(2009) Performance of different (BIM/IFC) exchange formats within a private collaborative workspace for c ollaborative work [J]. Electronic Journal of In formation Technology in Construction, 2009(14):736 752.

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Future of Information Exchanges and Interoperability 37 Smart Grid/Building Semantic Integration for Interoperability Jack Hodges , Ph.D. 1 and Wei Xi Xia, MS 1 1 Siemens Corporate Technology, Artificial and Human Intelligence Group, 1936 University, Suite 3 20, Berkeley, CA 94704; e mail: jack.hodges@siemens.com , brianxia@siemens.com ABSTRACT We report on a project to develop round trip interoperability between the grid utility and building management systems ( BMS), and between buildings running heterogeneous management systems, which have traditionally been information silos. The approach is based on the semantic inte gration of energy and building information models with a common, or system agnostic, semantic l ayer. Standards tend to have a very narrow focus of applicability, so growing a system agnostic domain model involves the integration of several standards (in th is case FSGIM, OpenADR, IFC, SAREF, QUDT, SOSA, NIST Tariff, and BRICK) into a cohesive model. The resulting information layer provides a foundation for round trip translation, validation, logic, and reasoning, and is part of a cloud based platform that pr ovides a messaging hub. The approach is currently being tested in a pilot study with 23 buildin gs in the two primary California power utilities, PG&E and Southern California Edison. INTRODUCTION Demand response between a utility and a consumer has, to dat e, been a one way relationship. The utility provides incentives to consumers in the form of red uced power rates and in return, during demand events the utility can reduce power to the consumer. This is of course a high level look at something substantially more complex, since contracts and tariffs vary all over the map, and vary with time of day, da y of the week, and season. So far, demand events are determined by the utility and the metrics they use to declare a demand event (generally lasting 4 hours duri ng peak demand) are not transparent to consumers, though they are generally dictated by forecas t temperatures. In recent times, Time of Use pricing has been employed, whereby the utility provides a price event, in the form of an OpenADR price payload, and commercial customers (those with systems that can manage building consumption) can decide how m uch power to use based on price. This has also been a one way interaction since the utility is not expecting to see the forecast values returned, so it cannot re ally adapt to forecast demand across the community. In this paper we present a semantic platfor m designed and implemented to support round trip interactions between the utility and BMS (using OpenADR), as well as to mediate interactions between buildings u sing like/dislike management systems to help stabilizing supply and demand. We recognize that t he utility information models are based on a different set of standards than buildings, and that this produces information silos which are challenging to negotia te in terms of

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Future of Information Exchanges and Interoperability 38 interoperability. As such, we have developed a standards based, system agnostic (or common) information model that serves as both a translator as well as a negotiation mediator between the players. This information model makes it possible fo r the utility to publish a pricing event and to receive forecasts and then to turn around and p ublish new prices, etc., until the demand meets the supply. It also enables buildings that act as a single VEN (in the OpenADR context) to collaborate on their r espective forecasts until they meet tariff requirements. Being an integrated information model allows this approach to adapt to changing metrics for defining demand events, as well as to negotiate using different building information, without changing any code, since the models reside outside the Utility and the BMS, and are fully declarative (can t hus be modified at run time). The remainder of this paper will present the architecture of this system as well as the information model and the mechanisms we use d to integrate the ontologies used in the platform. BACKGROUND / RELATED WORK Smart Grid and S mart Building each have compliance standards that apply to various aspects of their operation. Implementing and integrating these standards can improve generalit y and interoperability without sacrificing legacy models. In the case of the Smart Grid, there are many standards, but in terms of interactions with buildings, energy use and management ASHRAE Standard 201, implemented in the Facility Smart Grid Informatio n Model (FSGIM, ANSI/ASHRAE/NEMA 2016) provides ample content for representing electrical loads , generation, measurement, and management. The OpenADR (IEC/PAS 2014) and BACnet (ASHRAE 2016) protocols provide messaging and payload models for representing de mand response interactions between a utility and buildings, or between building devices, respec tively. On the building side, we also see standards such as the Industry Foundation Classes (IFC, ISO. 2014), and SAREF (Poveda Villalon 2018), which represent b uilding architecture and systems. These standards (and others) provide the foundation material for growing an interoperability model used in this project. There have been growing pains in this regard, most notably the acquisition of standards into high quality OWL ontologies, and the integration of acquired models. With respect to model acquisition, many standards have no structured (or, at least, not in OWL) implementation so they must be translated. Modern declarative modeling languages such as OW L provide the ability to define semantic relationships precisely enough to support machine to machine ( M2M) interoperability (i.e., interaction and understanding) but the translation process of acquiring standards into OWL models is anything but standardiz ed. Two similar efforts, to convert the IEC 61970 standard, and later the ASHRAE 201 standard, from UML to OWL were reported in (Crapo 2010 and Dangi 2012), respectively. In each of these cases assumptions and choices are made that would differ across onto logists.

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Future of Information Exchanges and Interoperability 39 A second problem is the basic ontology implementation approach, and this covers several metric s covered under the rubric of best practices, from naming conventions to design principles. In order to integrate ontologies they must be mapped to each other, but the intentions of the designers and the manner in which the ontologies were developed often makes integration challenging. On the intent side, many ontologies are developed without M2M understanding in mind, so they are ambiguous from an M2M per spective (Obrst 2007). Also, most ontologies are currently developed in house, with no broad based inte rnational consensus or input involved, to resolve interoperability needs in an enterprise environment. One way to resolve the preciseness problem is to i mplement models with a layering approach (Hodges 1993, Kitamura 2002) so that lightweight models and he avyweight models can be integrated and continue to provide value at their designed abstraction level. One way to resolve the in house model development p roblem is to use standards as much as possible, as they have at least been adopted by international com munities. Improving the translation mechanisms for acquiring standards into OWL, and developing a consensus on semantic best practices needed to effectiv ely implement and integrate semantic models are ongoing topics beyond the scope of this paper. In a rec ent paper we proposed the approach being used in this project, namely to integrate the standards associated with the Smart Grid and Smart Building to pro vide a system agnostic information model (SAIM) and to do it in a manner that integrates models into fu nctional abstraction layers (Hodges 2017, Mayer 2017, Koh 2017). The layering approach has also been proposed in (Xu 2004), and larger communities are be ginning to see the need to grow interoperable domain models (e.g. the NIST Industrial Ontologies Foundr y, Kulvatunyou 2018 ), and the IEC, which are talking about how to enable semantic interoperability using standards. PLATFORM APPROACH / ARCHITECTURE The platform, which we call EPIC (after the California Energy Commission program) is depicted in Figure 1. Figure 1. EPIC architecture.

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Future of Information Exchanges and Interoperability 40 The three major components of this system (shown as 1 3 in Figure 1) are implemented using web services so that they can r eside on separate machines (though in the current version they reside on an Amazon cloud instance). The primary component, the Information Mediator (at 1 ), serves as a proxy for all interactions and dispatches as necessary to the Information Management sys tem (at 2 ) and the Message Management System (at 3 ). The Information Mediator interacts with external e ntities (Utility, at 4 ) and BMS such as the XBOS (at 5 1 ) using the OpenADR protocol via a publish subscribe messaging pattern. All content shared by the utility or BMS is translated into what we call the System Agnostic Information Model (SAIM) so that lat er negotiation (and content negotiation) can be supported. SMART GRID / SMART BUILDING MODELS The goal in supporting interactions between the grid a nd BMS is not just to support data interoperability (very straightforward) but to support semantic interope rability between unlike systems and to do so without implementing O(N 2 ) adapters to the various entities that might engage in collaboration in the pr ocess. This is what gives rise to the EPIC System Agnostic Information Model (SAIM). Moreover, we do not be lieve that many institutions would adopt the use of ad hoc models, so we try to use existing standards and standards compliant models as much as poss ible. We do this using a functionally layered approach as shown in Figure 2. Figure 2. Model layering i ncreasing specificity radially. 1 In the current project, only an adapter to BRICK has been develo ped. In a parallel project an adapter to Siemens Desigo CC has been partially developed.

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Future of Information Exchanges and Interoperability 41 Figure 2 shows a conceptual aggregation of semantic models into groups (annuli) defined by their degree of specializa tion. The outer annulus represents more specialized domain models, such as Smart Grid, Smart Buildings, and Building Management, which can be cross accessed by traversing through more general (or cross domain) models in the inner circle (i.e., Core). The f igure makes no claim as to how these models are integrated; it only suggests that a path from any of the ou ter annulus domains to any other outer annulus domains can be affected through interoperability with the core. In fact, Figure 2 is only one such vis ualization of standards integration. In another visualization there are any number of annuli built on top o f each other by degree of abstraction, where a specific application is seen as a slide of all annuli, from the innermost or upper ontology to the out ermost domain specific ontologies. M ODEL INTEGRATION Essential to growing a standards based semantic domai n model for building interoperability is the integration of building automation system models such as XBOS, which uses BRICK (Balaji 2016) or VOLTTRO N (Akyol 2012), both of which use variants of a tag based information model but implemented so differently that direct interoperability is not possible. There are two approaches that can be used to drive integration: (1) one in which legacy models such as these are embraced and the integration is used to map across ontologies rather than to migrate data to the new model, and (2) one which is used to migrate both models and data and replace the originals. In our work we are implementing the former approach. In (Hodges 2017) we discuss our integration approaches (and associated issues) in greater detail, but here we identify the integrations we have performed to aid in the development of a system agnostic information model for Smart Grid and Smart Building, on e of which is shown in Figure 3. Figure 3. IFC to QUDT Unit class mapping. This diagram shows the initial phase of a mapping between the unit portion of the IFC and QUDT curated ontologies. In this phase subject matter experts have looked at the two ontologies and have determined appropriate class mappings along with potential co nflicts at the property or res triction

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Future of Information Exchanges and Interoperability 42 level. In this case, a single Unit class (green) was proposed as subclassing the IfcUnit and qudt:Unit classes as there was no conflict with other property restrictions. The same exercise can take place across all of the ontologies deemed necessar y for the kind of integration desired, as shown in Figure 4. Figure 4. Bridge and adapter mappings. Figure 4 illustrates 7 ontologies (qudt, ifc, ssf, saref, ssn, fsgim, and brick, in green) which are a part of this common m odel, along with the pairwise integrations between them (in blue). The integrations follow the example shown in Figure 3, though some are [much] more involved than the one depicted in Figure 3. The result of these integrations is the ability to traverse fr om a legacy model such as BRIC K, as shown in Figure 5. Figure 5. Mediator building to building mapping through SAIM.

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Future of Information Exchanges and Interoperability 43 Figure 5 depicts a path from supplied building identification data (at 1 ), and meter data which is associated with Brick tags such as bri ck:Electrical_Power_Meter (at 2 ) into the various SAIM models. The green line shows how brick meter data can be associated with SAREF and QUDT models to access Quantity and Unit structured models, and with the CIM_TARIFF model to access the contract tariff for the building in question. This information can then be used to perform analysis and optimization on energy usage compared to the pricing and contract tariff. VISUALIZER A visualizer was developed to expose some of the functionalities and data generate d in the EPIC system. It adopt s a dashboard layout to help users conveniently visualize the communication between the utilities and the buildings. Users can monitor the current prices and demands as well as retrieve historical data. The data are presented on the plots to showcase the t ime of use pricing hike during an event and how the buildings respond by adjusting demand accordingly. Figure 6. EPIC System Visualizer CONCLUSION A platform was presented that supports round trip interactions between the g rid utility and BMS using a st andards based, system agnostic information model. Several issues underlying and complicating the successful integration of standards, to produce a viable domain model for energy and building management, were presented. Most no tably the lack of consistency in ontology development and best practices, and equally challenging being the difficulty of developing mappings across ontologies where gaps or conflicts might exist. Nonetheless, a viable system agnostic information model has been developed and has been i n a pilot study using 23 buildings in northern and southern California.

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Future of Information Exchanges and Interoperability 44 REFERENCES Akyol, B., Haack, J., Ciraci, S., Carpenter, B., Vlachopoulou, M. & Tews, C. (2016). Proceedings of t he 3rd International Workshop on Agent Technologies for Energy Systems. Technical report . ANSI/ASHRAE/NEMA Standard 201:2016. Technic al report . ASHRAE Standard 135 :2016. Proceedings of the 3rd ACM Workshop on Embedded Sensing Systems for Energy Efficiency in Buildings. ACM. anics: A Computational Model f or Representing and Reasoning , 50(11), 26 36. IEEE. Hodgson . Qudt.org. Technical report . IEC/PAS Standard 62746 10 1:2014. Technical report . ISO Standard 16739:2013. its application to automatic identification of functional st Engineering Informatics. Volume 16, Issue 2. Kulvatunyou, B ., Wallace, E., Kiritsis, D., Smith, B. & Will, C. (201 Ontologies Foundry Proof of Conference Advances in Production Management Systems. Mayer, S. and Hodges, J., Yu, D., Kritzler, M. & Micha Framework for the Intelligent Systems. Poveda Requirement Specification for Smart Irrigation Systems: A SOSA/SSN and SAREF Comparis Monterey, CA. Technical report . World Wide Web Consortium. Xu, B., Wang, P., Lu, J le in semantic 334.

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Future of Information Exchanges and Interoperability 45 Using Linked Data to facilitate smooth and effective workflow in a federated model environment Leif Granholm, M.SC. (Eng) 1 , and Seppo Törmä D.Sc. (Tech) 2 1 Trimble Solutions Oy, Metsänpojankuja 1, 02130 Espoo, Finland, +358400440608, leif.granholm@trimble.com 2 VisuaLynk Oy, Holmanpää 3B, 02240 Espoo, Finland, +358503160979, seppo.torma@visualynk.com ABSTRACT BIM has had a major impact on the design of new buildings but it ha s so far had little effect on workflows in construction projects. In this paper we present how BIM enhanced with linked data can provide comprehensive workflow support with natural data ownersh ip and governance, granular online data sharing, and change man agement based on notifications downstream and change requests upstream. Linked data is used to link object instances in different models and many of the links can be created automatically as by product of design progression using a reference modeling paradi gm for BIM software. I NTRODUCTION BIM was originally understood as a single coherent centralized model representing a building. Recently that view has evolved into a concept of a federated mod el where every discipline and often each phase within a disci pline create their own self contained models whose data can then be combined in different ways for coordination and other purposes. However, it can be argued that BIM can and should be unders tood even more broadly as the transformation from human underst andable documents to machine understandable data. This requires that data published and shared is expressed in a machine readable format such as IFC instead of traditional human readable do cuments, such as drawings, schedules and natural language text. The whole information management process should become digital, including the consumption of data. A brief executive summary of BIM could be automating reception and consumption of data . A major consequence of using structured data is the separation of content and presentation, which means that a consumer decides how the data will be presented and used. In a traditional document based process the producer of data decides this. Figure 1 shows a part of an example workflow. Tasks are shown with their pre cedence relations and also their resources and information produced are indicated. Information created at the earlier tasks is needed in the execution of downstream tasks, and consequently a solution for information sharing is required. Traditionally it wa s based on the exchange of drawings, more recently on exchange of BIM files, and nowadays increasingly on access to online data in the models. Whatever the solution, it is important to tak e into account that the results of activities may need to

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Future of Information Exchanges and Interoperability 46 change, pe rhaps multiple times: there can be new requirements, new versions of architectural models, corrections that are needed to structural model, and so on. Consequently, parts of the workflow m ust be re executed later on, perhaps limited to a small portion of t he previously shared information. Figure 1 . A part of an example workflow indicating the resources and results of tasks In smooth and effective workflows all tasks should be able to access and utilize the information resulting from previous tasks in a focused manner as a compact set of relevant d ata and in a format that can be efficiently processed with appropriate tools. Drawings typically contain focused information but unfortunately not in a machine understandable format. BIM models, on the other hand, are machine understandable but usually n ot well focused to support change management workflows. When some objects in one model are changed, effective change management requires the understanding what objects in other models might be affected. This c an be achieved by cross model links between obj ects using principles described in Berners Lee (2006) and Bizer (2009). This paper addresses the questions of how to solve the problems of digitalization of construction workflows and argues that a technolog y that allows flexible publication, access and linking of data is an important part of the solution. The technology is based on standard representations, online access to data, reference modeling, link generation supported by BIM tools, change notification s downstream and change requests upstream. The concrete realization can be based either on Linked Building Data representations (Beetz 2009, Törmä 2013, Törmä 2014, Hoang 2016I) or centralized BIM collaboration systems.

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Future of Information Exchanges and Interoperability 47 MANAGING WORKFLOWS This chapter presents the concept of workflow management in an inter organizational setting based on granular sharing of data published online, the design process based on the use of reference model and cross model linking and change management processes in the workflo w. O rganizing Principles As Figure 1 suggests, the workflows in construction often cross organizational boundaries. Different tasks typically require specific types of resources, expertise and tools; each task is are naturally allocated to an actor with p roper capabilities. From the perspective of wor kflow management, an important question is what information each task consumes, what information it produces, and how these two are related. In the following these are discussed as the incoming information, ou tgoing information, and linking information (Fi gure 2). Incoming information . Almost all tasks whether in design or construction stages have at least some incoming information flows. In Figure 2, the task "Structural modeling" has two incoming infor mation flows, the requirements model and the ar chitectural model. The outgoing information of that task, a structural model, should conform to the contents of these incoming models. The central questions with incoming information relate to the effective ac cess to the information that all relevant inf ormation and no irrelevant information will be received and the changes to the information over time. The task may need to be executed many times when the incoming information changes, and there should be ef fective ways to determine whether the changes a ffect the task and to what extent. Figure 2 . Incoming, outgoing and linking information of task "Structural modeling" Outgoing information . When a task produces information as its result there are natural questions of ownership and responsibility of that information. In contrast to the early concept of BIM based design where the idea was to merge all BIM models together into a single unifi ed model in the workflow management approach presented in this pa per each model remains separate for several reasons. The ownership of a model is explicit and defines who is allowed to modify it during change management workflows. A model can only be mod ified by the assigned designer who understands the rationale of the existing design and who has the proper expertise and tools to make the changes without breaking the design.

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Future of Information Exchanges and Interoperability 48 This concept has additional benefits over a single merged model. Firstly, inte llectual property rights remain the same as with documents; consequ ently there is no need to change processes or business models to fully utilize BIM. Secondly, any model intelligence for example, internal solutions developed for parametrized design do es not need to be shared with other parties in the project, since p ublished data need only contain a snapshot with same information content as documents. Thirdly, full audit trail of the information can be recovered simply from the saved versions of datase ts. Moreover, it allows the control of the access of the informatio n based on the concept of digital sovereignty, as presented in Otto (2016). Linking information . The outgoing information produced by a task is usually derived from incoming information, and is dependent on the contents of that information. This dependenc y can be determined at different points of time: during the creation of the dependent informatio n, following its creation, or when the information is utilized. The information about the dependencies are called links, and they can be stored for later uses i n specific linksets. When incoming information changes, the changes can be projected over the li nkset to the outgoing information, to indicate to areas that are likely to be affected by the changes. Links can be generated with a variety of methods. They could be specified manually or derived automatically based on graph matching algorithms. The thi rd option explained below in more detail is to supply BIM design tools with interactive link generation capabilities. Data Sharing To proceed swiftly, workflo w tasks should be able to receive all relevant and no irrelevant information from incoming infor mation in a commonly usable format. However, in traditional BIM practice it has not been straightforward to achieve this. To provide smooth support for workflow management, especially taking into account the need to efficiently react to frequent changes, t he following principles have been adopted: online publication of data, granular access to data, standard data formats, and access to objects' links. Online pu blication of data . Whether on the Web or in a centralized cloud based service, up to date data o f previous models should be available for the consuming tasks and applications. Online availability of data can give a lot of flexibility to the contents that a re shared. Same model information can be published at different levels of detail, and if desired , links to further data can be provided into unlimited level of detail. Models can be also published as use case specific sets or as deliverables corresponding to contractual milestones. Granular access to data . The consuming tasks or applications should be able to access the data in a granular manner, even just one object at a time if needed. This means that replies to requests must support data formats that a llow for the representation of individual objects, including links

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Future of Information Exchanges and Interoperability 49 to further objects. The granu lar access is essential to keep the processing in consuming applications efficient and focused. Standard data formats . The data should be returned in standar d data formats. In the case of BIM, this means IFC or its derivative ifcOWL (Beetz, 2009) in the Linked Building Data approach. At the level of data serialization, Linked Building Data offers various alternatives ranging from XML and JSON to specific forma ts such as Turtle and N3. IFC itself is normally serialized either in the Step File Format or if cXML, but neither of these allow a granular serialization of models. However, various APIs of BIM platforms can provide a objects descriptions in JSON or XML, t hat can be usable although not completely standardized formats. Access to objects' links . When information about an object is accessed, it should be possible to either include the links of the objects in the reply, or to provide a related request that re turns the links of the object. There are many variations of how the applications that access inf ormation about objects can be made aware of the related links. There can be an separate linking service that returns the links when accessed with the identifier of the object. In a centralized service there can be a default database for such links which ma kes it possible to include links to object descriptions transparently. Another approach is to use backlinking (Hoang, 2016); when a link is created, the target of the link is notified which allows it establish an (remote) inverse link to the referring obje ct. Reference Models a nd Link Generation Since the focus in BIM has so far been on data production, the mechanisms to support data consumption in the downstr eam of a workflow are relatively undeveloped, especially in a multivendor environment. However, at Trimble there has been several years of development on some principles concerning structured machine readable data that have proven to work well in daily use of Tekla Structures. Figure 3 . An example of a multikernel architecture Application layer IFC access Native data storage GML access GML access Standard data abstraction Direct access

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Future of Information Exchanges and Interoperability 50 This concept is called a multikernel architecture (Figure 3) that maintains a clear separation between native and published data. Each appl ication can have its internal native sch ema for creation, storage and management of data. The native schema is typically optimized for the specific functionality of the system. The application can publish and receive data in standard formats, such as IFC. When receiving data, application does no t convert it back to its native schema but instead uses it together with native data. In a sense, the application has two geometric kernels that can run in parallel and can interact with each other. Multikernel archi tecture works much better than the alter native in which the received published model is imported and converted into a native format. The multikernel software architecture concept as implemented, for instance, in Tekla Structures can be used to provid e support for design work based on a ref erence model. The structural engineer can load a published version of the architectural model in Tekla Structures that renders it based on its IFC geometry. The designer can create the objects of a structural model a s reference to the corresponding archite ctural objects. Some design tasks can even be supported by further automatization that enables the conversions of architectural objects into corresponding structural entities. The functionality so far missing from this support it the link creation and pu blication. The event when a new object is created and positioned in a structural model is the correct point to suggest a link between the structural object and co located architectural object. The links could be easi ly exported after the model has been com pleted as pairs of GUIDs, together with the nature of the relationship and enriched with metadata such as the time and user. Change Management When changes happen to a dataset produced in the workflow, the differences of the new version of the dataset wi th respect to previous version need to be identified. Methods for this have been studied in Oraskari (2015). Using the difference between two mod el versions, and linking to each downstream model, the possibly affected objects in the latter model can be ide ntified. The result can be used to create a change notification to the responsible party of the model, which can start a ripple of change actions in the subsequent models. When a information creation task ends up in a situation that needs changes from ups tream models, it can create a change request using BCF messages (BIM Collaboration Format). BCF makes it possible to pinpoint the desired change using the view to the BIM model as the explanation of an existing problem. The cornerstone of the concept is that all actors create their own data that is based on data from other (previous) actors that is then published in a standard format to be used b oth upstream and downstream in the value chain. This new data is owned and managed by the creator and cannot be

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Future of Information Exchanges and Interoperability 51 changed by anybody else. Changes downstream and change requests upstream are facilitated by linking information between models. IMPLEMENTATION TECHNOLOGIES Two collaboration technologies to facilitate the workflow concept presented are reviewed: Linked B uilding Data and a Common Data Environment (CDE) to serve a federated model. Linked Building Data Web of Data technologies spec ified by Web Consortium allow the online publication of and access to structural data. The set of standards from globally uniq ue identifiers (URIs) and graph based data representation (RDF) to ontology description language (OWL) and query language (SPARQL) , have been applied to the representation of building data with the ontology version of IFC, called ifcOWL and converters that can translate IFC data to Web oriented graph format (ifcRDF). In the Linked Building Data approach, the models are published on line on the Web. Each of the identified objects has a URI which can be used to retrieve a description of the object in the RDF format, using the concepts of IFC as available in ifcOWL ontology. The online publication makes the model data accessible in a gr anular manner for all users over construction workflows, naturally taking the access control restrictions into account. The da ta can be accessed to the extent it is necessary: one object or a collection of related objects. It can be easily consumed by appl ications, as there are many tools to parse RDF data and the volume of data retrieved can be kept reasonable. The Linked Buildi ng Data approach enables in a natural manner the linking of objects across different models. Since the URI identifiers are globall y unique and retrievable, links across can be created as ordinary RDF triples. However, the practices, methods and tools to ac tually create them those links that should exist between objects is a large open area of development. Common Data Environment (CDE ) CDE (British Standard Institute 2013) is an emerging technology that has its roots in traditional servers in a client serv er scenario. They contain the traditional database functions associated with client server architecture amended with features from document management systems and cloud based functionality for documents and models. Development has been rapid in recent year s with the following main areas of development: Integrated Web based viewers that can use both BIM and GeoSpatial data. API and bu ilt in functionalities to support application development on CDEs. Support for BCF and workflow, issue management, and status management. It seems that CDEs will be the main way the information is conveyed in the AEC industry. CDEs are the natural place to implement the linking functionality outlined above. The focus in BIM is shifting from data creation software to data consumpt ion software; a large part of that software will be developed on the CDE platforms. All major BIM software vendors already have th eir own platforms on the market and under continuing development. It is therefore likely that no single

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Future of Information Exchanges and Interoperability 52 platform will gain a m onopoly in the market, and not even in a single project. Interoperability between the platforms is consequently of paramount impor tance. This can happen on two levels, interfaces directly between the platforms or through applications or middleware. The int eroperability should be implemented using open standards, such as IFC and Linked Data. DISCUSSION Many parts of the workflow conce pt presented in this paper have so far been implemented. For data sharing, a Linked Building Data environment was implemented in a DRUMBEAT project (Hoang, 2016) and Trimble has implemented Trimble Connect, a Common Data Environment with workflow managemen t support. The DRUMBEAT platform supported the backlinking based link management. Solibri Model Checker has been used for link generation between architectural, structural and MEP models. The reference modeling support has been implemented in Tekla Struct ures using the multikernel architecture. It has also support for BCF for notifications. The diff computation of Oraskari (2015 ) has also been implemented and tested with a large variety of models. In the future research the different pieces of functionality need to be combined into a integrated solution for complete workflow support. REFERENCES Beetz, J. 2009. Facilitating di stributed collaboration in the AEC/FM sector using semantic web technolog ies, PhD Thesis, Eindhoven University of Technology. Berners Lee, T., 2006. Linked Data Design Issues, W3C, vol. 2009, no. 09/20. Bizer, C., Heath, T. & T. Berners Lee, 2009. Linked data the story so far, International Journal on Semantic Web and Informa tion Systems (IJSWIS), vol. 5, no. 3, pp. 1 22. British Standards Institution 2013. PAS 1192 2:2013 Specification for information management for the capital/delivery phase of constr uction projects using BIM. Hoang, N. V., & Törmä, S. (2017). DRUMBEAT pla tform a web of building data implementation with backlinking. In eWork and eBusiness in Architecture, Engineering and Construction: ECPPM 2016. CRC Press. Oraskari, J., & Törmä, S. (2 015). RDF based signature algorithms for computing differences of IFC mod els. Automation in Construction, 57, 213 221. Otto, B., Auer, S., Cirullies, J., Jürjens, J., Menz, N., Schon, J., & Wenzel, S. (2016). Industrial data space: digital sovereignty over data. Fraunhofer White Paper. T rm , S. Semantic Linking of Building Information Models. IEEE 7th International Conference on Semantic Computing. IEEE, 2013, pp. 412 419. T rm , S. (2014) Web of Building Data ­ Integrating IFC with the Web of Data . eWork and eBusiness in Architecture, Engineering and Construction: ECPP M 2014; Mahdavi, A.; Martens, B.; Scherer, R., Eds. CRC Press, pp. 141 148.

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Future of Information Exchanges and Interoperability 53 Ontology Based Building Information Model Design Change Visualization Ning Wang, SM.ASCE 1 , and Raja R.A. Is sa, PhD, JD, PE, F.ASCE, API 2 1 Ph.D. Student, M.E. Rinker, Sr. School of Construction Management, University of Florida, Gainesville, FL 32611 5703; e mail: n.wang@ufl.edu 2 Rinker Professor and School Director, M.E. Rinker, Sr. School of Construction Man agement, University of Florida, Gainesville, FL 32611 5703; e mail: raymond issa@ufl.edu ABSTRACT The use of Building Information Modeling (BIM) has become popular in the architectural, engineering, construction and Operations (AECO) industry , and BIM has been used in the lifecycle of p rojects. As more data is added to a BIM model, the complexity and data volume of the model increases. Further, many design changes are made to a building information model during design and construction phases, and it is dif ficult to extract and visualize the changed objects. Research on the use of ontology in BIM is also limited. The purpose of this study therefore is to use an ontology to visualize revised objects in BIM models. This research uses the Industry Foundation Cl asses (IFC) format, a widely sup ported open standard for building information models. The changed objects in the BIM model are extracted by comparing the revised model to the original model, and a model report of the design change is provided. A prototype program using a sample IFC model is developed to validate the system. The results indicate that the proposed methodology is valid for the extraction and visualization of design changes in BIM models. INTRODUCTION Building Information Modeling (BIM) is a c ollaborative process in the architectural, engineering, construction and Operations (AECO) industry. Because it is collaborative, data interoperability is key. According to Gallaher et al. (2004), inefficient data interoperability costs the construction i ndustry more than $15.8 billion annually. Industry Foundation Classes (IFC) is one of the most popular BIM data exchange formats for data interoperability and has been widely used in the AEC industry. However, curr ent BIM applications do not support IFC pe rfectly (Jongsung and Ghang 2011). The size and complexity of IFC models increases as information is added (Jongsung and Ghang 2011; Zhang and Issa 2013). In addition, design change in BIM is considered a dynamic f eature of construction projects (Juszczyk et al. 2016). BIM models and IFC models must often be modified as design changes in construction projects are made. Redesigning IFC models is almost evitable in construction projects. Even though BIM can provide va luable information supports for constructi on practitioners, due to design errors and project design changes, BIM design changes cannot be avoided. Construction practitioners are required to track IFC model changes during the lifecycle of a construction pro ject (Shi et al. 2018). However, construct ion managers often face the overwhelming task of managing different versions of BIM models (Brittany et al. 2013). Although

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Future of Information Exchanges and Interoperability 54 the vendor specific software BIM 360 has a model change visualization function, the method was designed for vendor based Revit files rather than open source IFC files. Currently, the work of tracking design changes in IFC models is time consuming and complicated. This research aims to provide a methodology of visualizing changed 3D building elements in BIM models to track design change s. To achieve this goal, a comparison algorithm for use with two IFC models is required, as is an extraction method. In the literatu re review, the authors examine different extraction and comparison algorithms. Following the review, a methodology is develo ped for the comparison of a revised IFC model with the original IFC model and for the extraction of the changed building elements to several new IFC models for visualization. An ontology appropriate for the IFC schema and hierarchy tree was used. In accord ance with the proposed comparison and extraction algorithms, the authors developed a python based prototype application to validate the methodology. IfcOpenShell, an open source IFC parsing python library, was implemented to develop the prototype applicati on. The result indicated that the proposed methodology is valid to visualize design changes in IFC models. LITERATURE REVIEW Indust ry Foundation Classes (IFC). As more efforts are made in BIM data interoperability and specifications, many BIM standards ha ve been proposed such as in bSDD (buildingSMART Data Dictionary), OmniClass, COBie (Construction Operations Building Information Exc hange), and other XML based schemas (Sacks et al. 2018). Industry Foundation Classes (IFC) is the most popular BIM data exch ange format in use in the AEC industry. BuildingSMART International (formerly International Alliance for Interoperability, IAI) prop osed IFC as the international standard (ISO 16739). IFC is based on the ISO STEP (Standard for the Exchange of Product model data) EXPRESS data modeling language (buildingSMART 2019). The advantages of the IFC specification are that they are open source an d easily accessible. The information in an IFC model can be seen, checked and freely modified without any license restrictio ns. For these reasons, the IFC specification has become the most popular BIM data exchange medium. BuildingSMART has published many versions of the IFC specifications such as IFC2x3 TC1, IFC4 Addendum 1, and IFC4 Addendum 2. Although IFC4 Addendum 2 is the latest released version, IFC2x3 TC1 is the latest stable version of the IFC specifications. IFC2x Edition 3 Technical Corrigendum 1 defines the IFC instance names, Globally Unique Identifiers (GUIDs), referenced instances, and property names in the IFC fi le (see Figure 1).

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Future of Information Exchanges and Interoperability 55 Figure 1. Basic Terms of IFC Instance in IFC2x3 File Comparison of BIM Models. Ghang et al. (2011) proposed c omparison criteria for identifying the rate of similarities and differences between two IFC files. The comparison metrics, b ased on GUID and other referenced values of the IFC instances, were used to provide the comparison report. However, this methodology was developed mainly on a syntactic level rather than a semantic level building information comparison. Brittany et al. (20 13) developed a Navisworks Plug in for tracking the number of 3D objects Ducts changes in several versions of BIM models. This autom ated tool, however, focused on the number of changes of objects instead of the changes of objects themselves. A framework (F angxiao et al. 2014) of integrating change management and BIM was developed on BiMserver to update IFC models by change request. Shi et al. (2018) proposed a method and software called IFCdiff to identify the differences between two IFC models for model ch anges tracking. Their approach compared the two IFC files through an analysis of the IFC hierarchy structure and IFC content to find similarities and differences. However, their methodology fo cused on a syntax comparison instead of a semantic comparison, a nd differences in geometry and attributes were not reflected in their approach. Extraction from BIM Models. An IFC file contains a large amount of information about the building and the cons truction such as geometry and attributes of building elements. E xtracting relevant information from BIM models is time consuming work (Jongsung et al. 2013; Nepal et al. 2013; Zhang and El Gohary 2015). Jongsung and Ghang (2011) proposed two algorithms for extracting information from an IFC model. Algorithm 1 extracted the requested data, and Algorithm 2 eliminated unrequested data from the IFC model. Based on that research, Jongsung et al. (2013) developed another algorithm to extract a partial model from an IFC model not based on IFC schema. This algorithm, however, o nly extracts selected building element types and selected objects within one building area. In other research, Nepal et al. (2013) proposed an

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Future of Information Exchanges and Interoperability 56 ontology based methodology for information extrac tion regarding the construction domain from BIM models. Zhang an d Issa (2013) proposed an ontology based partial BIM model extraction methodology which implemented an ontology API to extract objects from the BIM model. Objects and the relationship between objects were considered in the extraction algorithm. Semantic na tural language processing (NLP) techniques have also been implemented to extract logic based semantic information from BIM models to support automated compliance checking (Zhang and El Gohary 2015). Ontology. y is a formal, explicit specification of a knowledge domain. An ontology modeling process converts concepts and the relations between concepts into a formal ontol ogy within one knowledge domain (Zhang and Issa 2013). Creating an ontology involves defining and describing vocabularies and relationships in a knowledge domain. In most research on construct ion ontology, RDF and OWL are the languages adopted to solve int eroperability problems. RDF and OWL, defined by XML schema, were proposed by the World Wide Web Consortium in 1999 as ontology languages within semantic web technology. OWL, built on RDF (RDF/ XML), can provide more descriptive expression for data interoper ability than RDF (W3C 2012). Figure 2 showed the hierarchy structure of IfcRoot in Protégé, an OWL language modeling software. This study implemented OWL as the ontology modeling language. Figure 2. Hierarchy Structure of IfcRoot in Protégé

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Future of Information Exchanges and Interoperability 57 METHODOLOGY To achieve the research goals, a comparison algorithm for extracting and visualizing 3D objects was developed (see Table 1). In this research, the extraction of 3D objects involves extracting the IfcBuildingElement (under IfcElement ) in the IFC files. To compare each IfcBuildingElement in the IFC files, the selection of the identifier of each IfcBuildingElement is important. The instance identifier number can change depending on the total inst ance numbers in the IFC model (Ghang et al. 2011). GUID is a sys tem independent identifier used to track objects in BIM models (Sacks et al. 2018). GUID remains consistent in the instances of the IfcBuildingElement . Therefore, this research implemented GUID as the first comparison criterion for the revised IFC model an d the original model. If the GUID is new in the revised IFC file, the IfcBuildingElement will be extracted from the revised IFC model as an added 3D o bject. The deleted IfcBuildingElement will also be extracted from the original IFC file, if the GUID does not exist in the revised IFC model. The visualization of each extracted model can be conducted separately and in combination. Table 1. Model Change E xtraction and Visualization Determination Original Model Object GUID Revised Model Object GUID Attribute/G eometry Instances Status Exist Exist Not Changed Not Extracted Exist Exist Changed Extract & Visualize Exist Not Exist NN Delete & Visualize Not Exist Exist NN Add & Extract & Visualize *Each model objects visualization can be conducted separately and in combination. *NN=Not Needed The challenge of developing the comparison algorithm was in the comparison of the geometry and attribute information of the IfcBuildingElement . For an attribute comparison, this research implemented the property name of th e IfcBuildingElement as the criter ion. For a geometry comparison, the referenced values regarding the geometry information were identified to compare the IfcBuildingElement in the two IFC models. The modified IfcBuildingElement was extracted from the revis ed IFC file. Based on the above co mparison and extraction algorithm, this research proposed a methodology to visualize the design change in the BIM model (see Figure 3). After the IfcBuildingElement was extracted from the original and the revised IFC model s, the ontology augmented IFC model was built to contain semantic information about the IfcBuildingElement in the output IFC files. IfcProject information was required for the extraction from the or iginal and the revised IFC models to build a relationship of IfcBuildingElement , IfcBuilding , and IfcBuildingStorey (see Figure 4). Upon the extraction of the ontology augmented IFC models, the visualization of the added, deleted, and modified 3D objects w as performed.

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Future of Information Exchanges and Interoperability 58 Figure 3. Meth odology of Extraction and Visualization for IFC Model Change Figure 4. Relationships between IfcProject and IfcBuildingElement Prototype Application. A python based Prototype Application based on the proposed visualization met hodology was developed (see Figure 5). For the extraction and visualization function, the prototype application was built on IfcOpenShell to copy the require d IfcBuildingElement to the new IFC files. The test IFC models were exported from Autodesk Revit 20 20. Figure 5. Python Prototype Application for BIM Model Design Change Visualization

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Future of Information Exchanges and Interoperability 59 VALIDATION AND DISCUSSION The research implemented two sample IFC models (samples A & B) to test the proposed prototype application (see Tabl e 2 and Table 3). The computer used to validate the prototype was an Intel i7 9700 CPU of 3.00 GHz with 16.0 GB RAM memory. For the smaller IFC m odels, the visualization time of the prototype was within one minute, while the visualization of the larger IFC model took over 10 minutes. The proposed prototype can visualize the extracted objects (see Figure 3) either from the original or the revised mo del to visually identify the differences between the IFC models (see Figure 6). The added model (solid) can be visualized with the original BIM model (transparent) to track design changes. Table 2. Original, Revised, and Output Information of IFC Model Sa mple A Model Information Original Model Revised Model Added Model Deleted Model Modified Model Number of IfcB uildingElement 8 10 4 2 6 File Size 40 KB 51 KB 8 KB 5 KB 12 KB Visualization Response Time 0.70s 0.72s 0.54s 0.54s 0.57s Table 3. Original, Revised, and Output Information of IFC Model Sample B Model Information Original Model Revised Model Added Mod el Deleted Model Modified Model Number of IfcBuildingElement 940 948 16 8 782 File Size 10 MB 11 MB 49 KB 72 KB 3 MB Visualization Response Time 50.65s 51.54s 2.48s 2.78s 20.77s The results indicate that the proposed methodology is valid to visualize the changed 3D objects in the IFC models. The python based prototype application quickly responded to track the design changes by comparing the original IFC file to the revised IFC fi le. However, the proposed methodology of visualizing has some limitations in its comparison algorithm. For the attribute comparison, the property name within the IFC instances was used as comparison criteria. The placement of the IfcBuildingElement is not taken into account in the geometry comparison algorithm. The IfcCartesian Point geometry information of the IfcBuildingElement was used to compare the two IFC models. CONCLUSION Previous methods of tracking design changes in IFC models were time consuming and vendor specific. This study proposes a new methodology for visualizin g the changes of 3D building elements based on open source IFC models. The results indicated that the proposed prototype is valid for the tracking of design changes in BIM models; it also responded quickly generated responses to comparison requests. The on tology based BIM model design change visualization system will assist construction practitioners by quickly identifying the changed building elements

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Future of Information Exchanges and Interoperability 60 within a large and complex BIM mo del. The proposed comparison algorithm, however, has some limitations. In future work, the authors will further refine the proposed methodology and prototype application with more semantic information extraction from BIM models. Future versions of the comp arison algorithm will cover the placement and relevant detailed property information of the building elements. Figure 6. Visualization of Design Changes of Sample IFC Model in Prototype Interface REFERENCES desk.com/bim 360/bim collaboration software/design collaboration/change visualization/>. Brittany, G., A., I. R. R., Rui, L., and Le, Z. (20 Changes in BIM to Assist Construction Managers in Coordinating and Ma naging Computing in Civil Engineering (2013) , Proceedings, 500 507. . . ork for Integrating Computing in Civil and Building Engineeri ng (2014) , Proceedings, 439 446. Analysis of Inade National Institute of Standards and Technology , U.S . Department of Commerce Technology Administration, Gaithersburg, MD. Quantifying the Journal of Computing in Civil Engineering , America n Society of Civil Engineers, 25(2), 172 181. .

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Future of Information Exchanges and Interoperability 61 IFCwiki. ( ing IFC Building Computing in Civil Engineering (2011) , 713 719. Jongsung, W., Schema Algorithm for Extracting a Partial Journal of Computing in Civil Engineering , 27(6), 585 592. based Design Procedia Engineering , The Author(s), 164(June), 518 525. National Institute of Buildi . Nepal, M. P., Sheryl, S. F., Rachel, P., and J Based Feature Journal of Co mputing in Civil Engineering , 27(5), 555 569. Sacks, R., Eastman, C. M., Teicholz, P. M., and Lee, G. (2018). BIM ha building information modeling for owners, designers, engineers, contractors, and facility managers : John Wiley & Sons, Inc., 2018; Third edition. content based automatic Automation in Construction , 86(June 2016), 53 68. Studer, R., Benjamins, V. R., 197. guide/>. ow l2 primer 20121211/>. Zhang, J., and El Goha Information Models into a Semantic Logic Computi ng in Civil Engineering 2015 , 173 180. based web services framework for building informa University of Florida, Gainesville, FL. Based Partial Building Information Model Journal of Computing in Civil Engineering , 27(6), 576 584.

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Future of Information Exchanges and Interoperability 62 Blockchain and the Built Environmen t: Automated Design Review Process Nawari. O Nawari, Ph.D., P.E., F.ASCE, 1 and Shriraam Ravindran, M.Sc. 2 1 School of Architecture, College of Design, Construction & Planning University of Florida; e mail: nnawari@ufl. edu 2 Ph.D. student, School of Architecture , College of Design, Construction & Planning University of Florida ; e mail: shr1raam@ufl.edu ABSTRACT Blockchain is a technology concept that originated from the first cryptocurrency known as Bitcoin and was soon noted to have a much wider range of applications beyond serving as the platform for digital cryptocurrency. A blockchain (BC) is essentially a de centralized and an immutable ledger that records every transaction made in the network. The implementation of decentralized technology in any industry would result in augmented security, enforce accountability, and could potentially accelerate a shift in w orkflow dynamics from the current hierarchical structure to a decentralized, cooperative chain of command by e ncouraging trust and collaboration. This paper present examines the potential integration with the BIM process in advancing the automation of the design review process. Moreover, the study explores how employing distributed ledger technology (DLT) could be advantageous in the automating the design review process by reinforcing network security, providing more reliable data storage and management of permissions, ensuring change tracing and data ownership. The paper evaluates the potential application of bloc kchain technologies such as Smart Contracts in cybersecurity, data ownership and other aspects, as well as enhancing the framework for automating the design review process with a demonstration using Hyperledger Fabric. INTRODUCTION The blockchain is a di gitized, decentralized public ledger of data, assets and all pertinent transactions that have been executed and shared among participants in the n etwork. While it is most associated with digital cryptocurrencies such as Bitcoin, blockchain is viewed as an emergent technology that could potentially revolutionize and transform the current digital operational landscapes and business practices of financ e, computing, government services, and virtually every existent industry (Crosby et al., 2015; Crosby M, 2016) . The chief hypothesis behind blockchain is the c reation of a digital distributed consensus, ensuring that data is decentralized among several nodes that hold identical information and that no single actor holds the complete authority of the network. A Decentralized Ledger Technology (DLT) is a peer to peer network generally incorporates a decentralized consensus mechanism, distributing the computational workloa d across multiple nodes present throughout the network, facilitating the nodes to create con nections, and they ensure the connections stay alive, while also ensuring every node in the network receives and transfers out data (Nakamoto 2008; Wang, Yingli, Jeong Hugh Han 2018; Zheng et al. 2017) .

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Future of Information Exchanges and Interoperability 63 This mechanism excludes the likelihood of a system failure or a complete network blackout. DLT usually achieve this by integrating a decentra lized consensus structure before the blockchain initiating transaction operation. The networ k participants agree in advance and decide on a consensus mechanism appropriate to their requirements. Every endorsing node in the network runs the same consensus a lgorithm , thus , the system does not need any third party administrator to oversee the transa ction operations (Brakeville and Perepa 2016) . Blockchain can ad dress accessibility and visibility of the data in a secure and efficient manner since the ledger is distributed (Brakeville and Perepa, 2016; Clack et al. ,2016a; Frantz and Seijas et al. , 2017) . It facilitates setting different levels of privacy as every participant is essentially a stakeholder and no single participant has full administrative privilege. Thus, formulating and enforcing consensus is crucial to the blockchain operation, with terms to data updates, error checking, and collective decision making. The selecti on of which BCT to uses Smart contracts are contracts programmed with the blockchain that a utomatically executes upon the fulfillment of certain conditions. , removes the requirement of a third party intermediary for overseeing the transaction in real tim e (Dhawan, 2016; Bhargavan et al. , 2016; Clack et al. , 2016a, 2016b; Seijas, Thompson and McAdams, 2017) . T Hyperledger Fabric is a platform for generatin g distributed ledger blockchain systems, supported by a modular design, offering a flexible digital framework that delivers high levels of confidentiality, and scalability. It is designed to support pluggable implementations of different components and acc ommodate the complexity and details that exist across the economic ecosystem. The Hyperledger blockchain aims to be a general purpose, enterprise grade, open source DLT that features permission management, plu ggability, enhanced confidentiality, and consen sus mechanism and is developed through a collaborative effort. BIM is at the forefront of digital transformation in the AEC industry, encouraging collaboration and trust, and simplifying data exchange. BIM mo dels present a comprehensive design and constru ction model of the building that can include all aspects of the facility such as architectural components, structural elements, and MEP design areas. Further, several built in plug ins in BIM platforms like Au todesk Revit enable the simulation of external site conditions, geography, weather, as well as carry out energy analysis, building energy modeling, structural analysis, etc. In the future, BIM development will eventually aim to unify all design and analysi s tools in one platform. However, the current B IM process has several limitations such as no archival of BIM model change and modification history, difficulties in assigning responsibilities and liabilities, insufficient cyber resilience and cybersecurity , and lack of legal framework detailing model d ata ownership and legal contractual issues (Eastman et al. 2011; Ahn et a l., 2015) Employing BCT in the BIM process can address several issues that are currently phasing the BIM implementation in the AEC industry. For instance, these include cybersecurity, reliable data storage a nd management of permissions, change tracing, a nd data ownership. This paper proposes a framework that is based on integrating HLF and the automation of the design review process in a BIM workflow.

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Future of Information Exchanges and Interoperability 64 GOALS AND OBJECTIVES The primary purpose of this study is to examine the BCT and its integration with th e BIM workflow to enhance the automation of the design review process. The objectives include a) review Hyperledger Fabric (HLF) and its potential applications in BIM workfl ow, b) propose a framework for integrating HLF and the Automation of the Design Rev iew process to enhance the cyber resilience and security, data storage and management of permissions, and data ownership. METHODOLOGY The study approach is based on an organ ized review and evaluation of the HLF, and the potential of its integration with BI M workflow to improve the security and efficiency of the design review process. This includes the retrieval of the relevant data from the literature sources assessing the q uality of the content, and synthesizing the data to develop a framework for integra ting the HLF with the automation of the design review process. HYPERLEDGER FABRIC Hyperledger is a collaborative effort founded by the Linux Foundation in 2016 to advance cr oss industry BCT. It aims at the development of distributed applications written in standard general purpose programming languages (Andreoulakis et al , 2018). It is a cross industry open standard platform for blockchain that seeks to transform the techniqu e business transactions are conducted universally. HLF is one of the blockchain pro jects within Hyperledger. Like other BCT, it has a distributed ledger, uses Smart Contracts (SC), and is a system by which participants manage their transactions. In HLF, SC is known as chaincode. It is executable code, deployed on the network, where it is invoked and validated by peers during the consensus process. The common programming language used in developing chaincode is Go, Ruby, Java, and NodeJS (Hyperledger, 2018). The fundamental differences between HLF and other blockchain systems are that it i s private and requires permissions (Nawari and Ravindran 2019). In contrast to an open permission less system that allows unknown identities to participate in the network, t he nodes of an HLF network join through a trusted Membership Service Provider (MSP) . Moreover, Hyperledger Fabric has the ability to create channels, allowing a subgroup of participants in the network to establish a separate ledger of transactions (Nawari and Ravindran 2019). This is an especially important option for BIM workflow where subcontractors can exchange data within the only subgroup of the network . For example, the structural engineer of record of the project can exchange information with steel connection subcontractors only while still being part of the HLF network and sharin g those transactions with the rest of the nodes (N awari and Ravindran 2019). AUTOMATED DESIGN REVIEW PROCESS Regulations are normative text prescribed by governing entities to enforce constraints to design and engineering processes and manufacturing base d on existing conditions, and function as

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Future of Information Exchanges and Interoperability 65 the defi ning text for laws, codes, specifications, standards, etc. Automating design review and compliance processes in the AEC industry would benefit the industry, saving time, money, labor, and minimizes scope fo r risk and human errors. While much of the decisio n making and consideration of the code is dependent on the experience of the reviewers, automation could at least enforce the upper and lower limits and report results instantaneously. Translation of variou s clauses and statements into computable language presents a major challenge in achieving automation (Eastman et al. 2009; Nawari 2018) . However, following an ideal framework to develop a tool that successfully accounts for all regulations through the accurate interpretation of formal language and model data exchange could be pivotal in increasing efficiency and upholding safety standards in any AEC projects. Automating design review and compliance processes in the AEC industry would greatly benefi t the industry in terms of increasing productivity, minimizing resource consumption and reducing the scope for human errors. Nawari (2019) developed the Generalized Adaptive Framework (GAF) that aims at a ttaining a computable model with the clear syntax to accurately characterize building code requirements, to reduce model complexity and develop a unified format to exemplify building regulations and building information modeling to automate design review a nd compliance processes. However, the compliance c hecking process must be secure with reliable data storage and management of permissions, change tracking, and collaborative. Thus, this study proposes a framework that integrates the HLF and the GAF to impr ove the security and efficiency of the automatic d esign review process in a BIM workflow PROPOSED FRAMEWORK The proposed framework aims to use HLF to implement an automated the Design Review Process based on the Generalized Adaptive Framework (GAF) (Nawa ri 2019). Figre 1 below delineate an overview of t he integrated HLF and GAF framework to automace design review and compliance checking process. The four main elements of the framework are the GAF, Smart Contracts (Chaincode ), membership services, and ord ering services.

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Future of Information Exchanges and Interoperability 66 Figure 1. Overview of the Integrative HLF + GAF Framework for automating design review Process The HLF is based on a permissioned blockchain network that provides security to pro tect data exchanges between mem bers of entities who share a mutual goal but have intellectual properties that they need to secure while exchanging information. The proposed framework has a modular architecture. The main modules are depicted in figure 1 and include: (a) Membership services: A membership service provider (MSP) allocates cryptographic identities to peers participating in the network, and maintains the identities of all nodes in the system . This module serves to create a root of trust during the network fo rmation. (b) Ordering s ervices: A service that broadcasts the state updates to peers in the network and establishes consensus based on the order of transactions via, the Ordering Service Nodes (OSN), or orders that establish the total order of all transaction s in the Fabric. The ordering services in HLF represent the consensus system. The ordering service groups multiple transactions into blocks and outputs a hash chained sequence of blocks containing transactions. (c) Chaincode (Smart Contract) services: It is an application level c ode stored on the ledger as a part of a transaction. The chaincode runs transactions that may modify the data on the ledger. states to perform read and write operation s. The chaincode is then instantiated on particular channels for specific peers. (d) GAF: The GAF represents the business logic that is written as a chaincode. The GAF has algorithms that can be expressed and executed in JAVA programming o bjects to extract, a ccess and link BIM and regulations data to report the results of the design review process.

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Future of Information Exchanges and Interoperability 67 CONCLUSION The Blockchain is a growing digital technology which is characterized bys a decentralized, full lifecycle traceable public ledger o f transactions for a ll participants, and security and privacy of the network that is based on consensus algorithms. Due to these characteristics, Blockchain has gained recently widespread traction in various fields. HLF is a blockchain that is principally suited for developin g the automation of design review process in BIM workflows, due to its ease of programming (using SDK), flexibility, user defined smart contract (chaincode), robust security, identity features, and modular architecture with pluggable co nsensus protocols. T he the proposed integrative BCT+BIM framework aims to provide secure, reliable automaion process of the design review and compliance checking in BIM workflow. The chaincode technologies (also known as Smart Codes) available in HLFs are promising technolog ies for advancing the security and efficiency in the AEC industry, particularly for the compliance checking process. Furthermore, the HLF can address many of the current concerns facing the BIM workflow, such as data security, privacy, the speed of transac tions, and change tracing and permission management that arise from using centralized BIM work processes. Future research will focus on expanding the integrative framework to include other issues related problems such as data ownership and legal issues. REFERENCES Journal of Management in Engineering 32(1): 05015005. B Proceedings of the 2016 ACM Workshop on Programming Languages and Analysis for Security : 91 96. in Basics: Introdu ction to Business Ledgers Get to Know This Game 1 6. Essential Requirements and Design Options 15. http:// arxiv.org/abs/1612.04496. 15. Crosby, M., Nachiappan, Pattanayak, P., Verma, S., and Kalyanaraman, V. 2015. Blockchain Technology: Beyond B lockchain . Crosby Applied Innovation Review (AIR) : 6 19. ` Based Checking of Building Des Automation in Construction 18(8): 1011 33.

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Future of Information Exchanges and Interoperability 68 Auto to Www.Bitcoin.Org : 9. Nawari, N. 2018. Building Information Modeling: Automated Code Checking and Compliance Processes . Boca Raton, Florida.: CRC Press, Taylor & Francis Group, LLC. Nawari, N., 2019. " A Generalized Adaptive Framework (GAF) for Automating Co de Compliance Checking." Buildings 2019 , 9 (4), 86; https://doi.org/10.3390/buildings9040086 Lecture Notes in Computer Science (in cluding subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformati cs) 10323 LNCS: 631 32. Wang, Yingli, Jeong Hugh Han, and Paul Beynon Technology for Future Supply Chains: A Systematic Lite rature Review and Research Supply Chain Management: An International Journal . Zheng Proceedings 2017 IEEE 6th International Congress on Big D ata, BigData Congress 2017 : 557 64.

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Future of Information Exchanges and Interoperability 69 BIM Framework for Sustainability in Saudi Arabia F atma Hasanain MIA 1 and Nawari O. Nawari 2 , Ph.D., P.E., F.ASCE2 1 Ph.D. student, University of Florida, College of Design, Construction & Planning, School of Architec ture , P.O. Box 115702, 1480 Inner Road, Gainesville, FL 32611 5702; email: fhasanain@ufl.edu 2 University of Florida, College of Design, Construction & Planning, School of Architecture , P.O. Box 115702, 1480 Inner Ro ad, Ga inesville, FL 32611 5702; email: nnawari@ufl.edu ABSTRACT Improving the performance of existing buildings has provided a broad market for the green renovation of US building stock currently estimated at 76 bil lion s quare feet. Building Information Modeling (BIM) has had a remarkable impact on the building industry by enhancing productivity and document accuracy. The integrative nature of BIM technology renders it an ideal tool for implementing sustainable strat egies into the renovation and retrofit of existing structures. The intent of this research is to determine what functions of BIM could be utilized to implement sustainable design principles in new and existing structures in Saudi Arabia by exploring the na ture o f the relationship between BIM platforms and sustainability. The study sought to establish a framework for sustainability in Saudi Arabia. necessitating the kingdom to establ ish its 2030 vision. The 2030 vision aims to make Saudi Arabia an ideal sustainable society by reducing its reliance on petrol, creating more sustainable buildings, and using renewable energy resources. Due to the lack of a national rating system in the ki ngdom, LEED will be used as a guideline to formulate a unique rating system suitable for Saudi Arabia This research aims to provide a BIM framework to achieve the envisioned sustainability goals and implement sustai nable design principles in Saudi Arabia. Further, the study aims to develop a new rating system for Saudi Arabia that is fully integrated with BIM platforms. Keywords BIM, Sustainability, Green buildings, Sustainable Buildings, Rating System, Saudi Arabia, 2030 Vision.

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Future of Information Exchanges and Interoperability 70 INTRODUCTION Even though green buildings are created in many countries worldwide, they do not have the same popularity and acceptance in Saudi Arabi a. This gap has been apparent by the lack of guidelines and regulations that encou rages green buildings and sustainability in the country. Due to the lack of a national green building rating system in the Kingdom of Saudi Arabia, LEED is used as a rating s ystem, but it does not apply to the Saudi Arabian infrastructure. The Saudi Vision 2030 has set ahead the roadmap for future generations to prosper and live their lives in a steady economic state where both the private and public sectors join hands to enha income and natural resources. Recently the Architecture, Engine ering, and Construction (AEC) industry started to implement BIM in their practices. BIM has tremendous capabilities and positive influence on green building certifications. V arious countries worldwide started to require green building certification for pro jects as a mandatory procedure; the utilization of BIM in all built projects will be a standard protocol shortly. Consequently, BIM will continue to grow at a steady pace and it will be utilized as a tool for construction practices and sustainable design. BACKGROUND After the discovery of oil in Saudi Arabia, petroleum became a vital industry. Since the 1980s the economy of Saudi Arabia boomed and has been developing at a dra matic pace due to the massive revenues from oil exports. According to Mubarak, eve n though Saudi Arabia was once an undeveloped country the oil wealth led to various project developments, modernized the country and led to low unemployment rate (1999). Rece have dropped dramatically making it nece 2030 vision aims to make Saudi Arabia an ideal sustainable society by reducing its reliance on petrol, creating more sustainable buildings, and using renewable energy resources. When creating a perfe ct sustainable society there must be equal access to nutrition, healthcare, clean water, shelter, education, energy, economic opportunities, and employment. The EIA indicate exporter of pe troleum liquids, it is also considered to be the largest consumer of petroleum liquids in the Middle East (2013). Rahman and Khondker mentioned that Saudi Arabia faces green gashouse emissions since its economy is based on oil and in which the energy secto r is entirely dependent on fossil fuels (2012). Investing in renewable energy sources and the use of public transportation is discouraged (Rahman & Khondaker, 2012). Saudi Ar abia is ranked 61st in the Climate Change Performance Index of 2014, which is last position on the index (Burck, et.al,

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Future of Information Exchanges and Interoperability 71 2013). Therefore, it is crucial for Saudi Arabia to reduce its environmental footprint and enhance its building sustainability (Taleb & Pitts, 2009). Due to the decline in oil supply in Saudi Arabia, and due to the ab rupt decrease in oil selling prices, the kingdom is looking into new ways to diversify its economy and its energy future. The embarked upon a new economic journey, towa rds diversification and long term prosperity. The Saudi Arabia Renewable Energy Investment Forum (SAREIF), will seek to accelerate the rogram a key component of economic transformation (Jurgenson & Bayyari, 2016). Another important factor regarding rgy efficiency by just 4 percent a year could save the equivalent of 1 million bar rels a day of crude by 2030 (Mosly, 2015). Currently, the rate of green buildings in SA is relatively slow compared to other countries due to the lack of a national green bui lding rating system; therefore, a BIM based metric can accelerate the process of o btaining more green buildings in the Kingdom. RESEARCH OBJECTIVES The main goal of this research is to examine how BIM currently function concerning sustainable practice s and develop a BIM based framework for sustainability in Saudi Arabia (SA) to ach ieve the kingdom vision for 2030. The objectives include 1) review existing methods and frameworks to measure sustainability, 2) propose a rating system for the kingdom of Sa udi Arabia (KSA), 3) identifying the critical elements of the 2030 vision 4) integ rate the findings into a BIM based Metric for Sustainable Built Environment in Saudi Arabia. LITERATURE REVIEW Sustainability he most talked about and less understood scholarly concepts. Even though it is a w ell established term, there some general and vague understanding of sustainability especially in places where environmental origins of sustainability come second (Lew et al., 2016; Marchese et al., 2018) . In such fields the simplest def inition of seems to be serving the purpose

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Future of Information Exchanges and Interoperability 72 (Lew et al., 2016; Sayer et al., 2004) . There are about 200 definitions of the concept of sustainability and most commonly used one is defined by the World Commission on Environment and Develo ability of future generations to meet the ir own needs. It contains within it two key concepts: the o which overriding priority should be given; and the idea of limitations imposed by the state of technology and social organ 2017). This common definition of sustai nable development with some minor alteration is widely capability of maintaining over indefinite periods of time specified qualities of human well being, social equity, and environmental (Leach, et al., 2010) . importance of the economic, social and environmental respo nsibility (Lizarralde et al., 2015) , Gr een building certification as well as sustainable construction in developed countries concentrates on carbon reduction as well as energy consumption with paying very little attention to the social aspects of sustainability (Kibert, 2007; Lizarralde et al., 2015) . Assessment tools in regards to sustainability are often being judged for marking boxes without considering the relation between the variables of intervention and the consequences (Lizarralde et al., 2015) . Therefore, sustainabili ty in the built environment and green building rating systems in general, are considered (Reed, 2007) that serve as a technical solution to save issues created by the syst em itself (Lizarralde et al., 2015) . I n the Architectural, Engineering, and Construction (AEC) industry, sustainability relies resources to meet societal needs and aspirations, considered a major part to achieve this paradigm change. According to Lengar and Pearce, each part of the comparison provide ideas to imp rove sustainability in the built environment. For example, enhancing technologies to stay within the limits imposed by the environment as well as better handling or reducing human needs. BIM must be implemented in order to better enhance sustainability in the built environment and meet human needs (2017).

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Future of Information Exchanges and Interoperability 73 Green Building Green building design is defined as the practice o f building structures and implementing procedures resource efficient and environmentally responsible for their entire life cycle. Accordin g to the EPA Green buildings are also defined and known as high performance building, sustainable building and green b uildings (2014). Leadership in Energy and Environmental Design (LEED) is a voluntary green building rating system developed by the United States Green Building performance and promote sustainability. The theoretical fra mework of LEED is based on a critique of contingencies inherent to various definitions of sustainability and an analysis of the new politi cs that are emerging through the discourse of sustainability (Cottrell, 2010). Recently many countries around the wor ld have pursued sustainability. Both the general public and world governments are pursuing sustainability due to the worldwide environment al disasters and negative impact caused by manmade activities and pollution. The World Business Council for Sustainabl e Development ( WBCSD ) indicated that the building sector by itself is accountable for about 40% of th to focus their attention on producing more sustai nable buildings that have a minimal negative effect on the environment and its surrounding. Green LEED certified buildings represent a sig nificant component of sustainability, as their creation is intended to decrease natural resource consumption through e nergy and water conservation (Mosly, 2015). Even though Saudi Arabia is ations in the construction sector are limited and the number of green LEED certified buildings within the country is r emarkably small. An essential foundation for promoting sustainable green building development is the creation of a system that assesses gr een buildings. For instance, in 1990 in the UK introduced the Building Research Establishment Environmental Assessment Method (BREEAM) and few years later the United States Green Building Council created LEED (Leadership in Energy and Environmental Design) . According to Zafar, several other countries followed the same steps. It has been evident that in these countries the public, investors, and owners are pushing towards certified green buildings. Green buildings bring numerous advantages besides contributi ng to sustainability. For example, green buildings have fewer maintenance costs, enhanced durability, low operation co

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Future of Information Exchanges and Interoperability 74 Green Building Rating Systems in the Middle East and North Africa (MENA) In addition to LEED and BREEAM multiple green building rating systems are used worldwide. Nowadays, In the MENA region sustainability is a top priority. The United Arab Emirates (UAE) and Qatar, as well as other countries, established their own gree n building rating system to promote sustainability (Zafar, 2017). Below is a list of the green building rating sys tems in MENA: a) Global Sustainability Assessment System used in (Qatar) b) Pearl Rating System used in (Abu Dhabi) c) ARZ Building Rating System in (L ebanon) d) The Green Pyramid Rating System in (Egypt) Saudi Vision 2030 In June 2016 the Saudi Vision 2030 was approved and announced by King Salman by King Salman Bin Abdulaziz the custodian of the two holy mosques (Government of Saudi Arabia, 2016). The ole dependence on oil export (Hashmi, 2016). The vision includes specific targets, certain objectives and obligations to be accomplished by the private and public and non profit sector s in the Kingdom. Several of ambitious goals of the Saudi Vision 2030 in clude: 1. oil government revenue from SR 163 billion ($43.5 billion) to SR 600 billion by 2020, increasing further to SR 1 trillion by 2030 2. Increasing t 3. Raising the oil exports in non oil GPD from the current 16% to 50% (Almasoud, 2016) The Saudi Vision of 2030 collaborated with the National Transformation Plan (NTP) 2020 t o include a new enhanced determination for efficiency, planned tax incre ases, providing major roles to private divisions starting with privatization of airport ground service and operation., and strategically executed spending cuts. (Hashmi, 2016). Accord ing to Almasoud, the NTP 2020 aims to accomplish the Saudi Vision 2030 t hrough four major pillars that will make this plan attainable. The four pillars are privatization, governance, investing in human capital and Economic Diversification (2016). Supporti ng the NTP four pillars are the following goals:

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Future of Information Exchanges and Interoperability 75 Reduce depend on oil Re view the performance of ministries and combat corruption Achieve maximum efficiency Develop sectors like tourism and enhance the Hajj and Umrah operations Create more jobs for Saudi na tionals Utilize resources to support future projects (Hashmi, 2016). I n addition to that, the vision demonstrates an effort to enhance all aspects of the Saudi t and its natural resources. The vision also seeks to protect the enviro nment by enhancing the effectiveness of waste management, reducing ally types of pollution, establishing major recycling projects, rehabilitating and safeguarding beaches and natural r eserves and islands and making them accessible to everyone, promoting th e optimal use of water resources by utilizing renewable and treated water as well as eliminating desertification (Government of Saudi Arabia, 2016). The government, as well as local en gineering bodies, started working together to establish the concept of s ustainability and how it can be applied which is crucial to the success of the execution. Oil in Saudi Arabia Petrol has made Saudi Arabia a rich and a prosperous country economical ly. Since the 1930s Saudi Arabia had a radical economical growth due to having the highest petrol stock in the world. Consequently, this innovated the country to become one of the most rapidly developing countries in the MENA region (Al Surf, 2014). The re venue generates per barrel of oil for Saudi Arabia had more than doubled from $0.22 in 1948 to $1.56 in 1973 (Mubarak, 1999). The price continued to soar to $10 and higher in 1974 follo wing the Arab oil embargo. Oil revenues continued to climb and by 1982 had reached over $30 per barrel. The peak of oil revenue occurred on December 1979 when the price was at $121.28 per barrel and June 2008 at $141.32 per barrel. Government oil revenue m ade massive leap from $4.3 billion to $101.8 billion between 1973 and 1 980 (Conca, 2015). The plentiful income from oil revenue gave Saudi officials the resources to implement major changes to the economy. Today the price of oil has experienced a large dro p, the price of barrel of oil today typically ranges below $60 and it i s no expected to rise above $100 any dependence and reliance on oil is due to this drop in o il revenue.

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Future of Information Exchanges and Interoperability 76 LEED Certified Buildings and Green Building Codes in Saud i Arabia Multiple obstacles exist in Saudi Arabia slowing the adoption of LEED certified buildings. Some of the are: the climate in Saudi Arabia is not favorable to the typical sprawl of Western suburban development, lack of public awareness, lack of stak eholder interest, low levels of investment in sustainable buildings, lack of financial incentives, and lack of government regulations on sustainable buildings. In addition to that desig n firms lack the knowledge to design and create sustainable buildings t hat suite the Saudi Arabian culture (Mosly, 2015). In Saudi Arabia, there is currently no mandatory building codes nor regulations that features the principles of a sustainable built environment in the country. According to Karam, many researchers argued that it is essential to set a comprehensive set of green building standards and codes to widely spread sustainable practices and reduce water and energy consumption (2010) (Karam, 2010 ). Recently the Saudi government created the Saudi Green Building Foru m (SGBF), which is responsible for developing regulations and laws that encourage green building initiatives, seminating green building information, engaging stakeholders and promot ing green building concepts and cultural awareness of green building among citizens through workshops, conferences and publications. The ng system is recognized in projects in Saudi Arabia, and SGBF is the so Building Information Modelling (BIM) BIM is defined by the Whole Building Design Guide (WBDG) as ation of physical and functional characteristics of a facility which se rves as a shared knowledge resource for information about a facility forming a reliable basis for decisions during its life cycle from process built on coordinated r eliable information about a project from the design through Institute of Architects dimensional model linked to a dat abase of project information, combining all information from the design inception to the facility tial BIM features:

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Future of Information Exchanges and Interoperability 77 Use of BIM as a combination of products/tools which produces three dimensional models, with enhanced visualization, and that is rich in information pertaining to the project. Use of BIM as an integrated process which enables the flow of information between stakeholders up to and including the management/op erations of the facility. A combination of product and process that helps stakeholder decide about the building over the life cycle. Due to its ability to serve stakeholders, BIM has multiple definitions. In addition to that BIM allows collaboration bet ween designers, owners, architects, contractors, and other building specialists. BIM has rich information that is necessary for sustaina bility and green certification aspects that can be used in different phases of the project by stakeholders (Azhar et al. 2008; Mahdavinejad and Refalian 2011; Siddiqui et al. 2009). Miller (2010) also indicated that BIM is utilized to enhance sustainabilit y in built environment. For instance, in a green building the amount of energy consumed can be measured. In the BIM mode l various design options for sustainability can be easily traced and implemented. Additionally, advanced visualization methods such cons truction animation of green buildings, 3D renderings as well as solar studies can be utilized (Azhar et al. 2011). Visua to quantify the savings to a certain extent, thereby resulting in improved design insights, risk mitigation, 4D and 5D analysis, clash detection, prefabrication, systems coordination, widening the search for solutions, improved integration in decision mak ing, differentiation of objective and subjective judgment, and s to establish a cohesive holistic analysis, eliminate waste, reduce cost escalation and solve interdisciplinary issues. BIM is not sole ly considered a graphical tool, it is also a comprehensive information modeling program that can have various advantages in regards of life cycle assessment, sustainability, energy efficiency, construction waste and rainwater harvesting (Lengar & Pearce, 2 017). The use of BIM for designs purposes in the construction industry has seen tremendous growth due to its potentials to improve collaborations among project stakeholders. It contains information and data essential in defining product development standar ds and approvals. This is important, as models developed using BIM provides several effective solutions and potential ap plications in almost every stage of development. This makes it different from Computer Aided Designs (CAD) as its operations are based o n an internalized system of integrated information

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Future of Information Exchanges and Interoperability 78 while CAD operates on external sources of information. To this, Krygi el and Nies (2008) affirmed that BIM contains the planning, construction and operation information of a building as opposed to CAD which only contains two CAD as it manages all graphics information, and operates within a controlled environment, nd this. BIM main concepts were described by Krygiel and Nies (2008) to include capabilities to: D evelop project design, construction, and maintenance management strategies, I ntegrate and manage the flow of graphical data with information data, and process description. D ecentralize individual tasks into complex processes; transforming individual processes into teams. R apidl y and effectively perform life cycle operations of building projects. BIM offers the ability to accomplish rigorous functions con currently as it provides potential benefits with its application in the AEC industry. METHODOLOGY This research follows a mixe d approach that is both qualitative and quantitative. This study requires both primary and secondary data. To achieve the researc h objectives, the qualitative data collection methods used will include a semi structured interview, an online survey for the p ublic, two Delphi rounds, and three case study analysis. The research targets input from experts in the construction field in Sau di Arabia, primarily because of a lack of public awareness. The public at this point in time is unaware of the matter being stu died. The quantitative data collection methods used include surveys and questionnaires, correlation coefficient, linear regressio n, and chi square and results will be numerical and quantified in order to obtain the required result. This research work emplo ys the following outlined method for the purpose of obtaining the results. Data about the 2030 vision of the KSA will be analyzed and contrasted with the existing rating system in the Middle East. A new BIM based metric will be developed based upon the dat a analyzed to assist in attaining the KSA 2030 vision. The diagram below depicts the methodology process. It includes scope iden tification, the selection of relevant articles, abstracts assessment, excluding irrelevant articles, determining the

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Future of Information Exchanges and Interoperability 79 sustaina bility parameters, and finally, developing a BIM Framework to measure KSA 2030 vision attainment levels. Figure 1 . Methodology Process. PROPOSED BIM FRAMEWORK The proposed framework targets nine themes to be measured to determ ine the level of attainment of the KSA 2030 vision. This framework is implemented in Autodesk Revit to give a quick assessment of a new or existing building of its contribution to achieving the KSA 2030 vision (see figure 2). Figure 2 delineates an overvie w of the user interface of the proposed BIM framework. Figure 2. BIM Framework for Sustainability in KSA.

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Future of Information Exchanges and Interoperability 80 CONCLUSION The KSA supply of gasoline is not sustainable at the current rate. Thus, the Kingdom established its 2030 vision to address this issu e. The vision aims to make KSA a sustainable society and reduce its reliance on fossil fuel. Even though green buildings ar e created in many countries worldwide, they do not have the same acceptance and popularity in Saudi Arabia. This gap has been observe d by the absence of policies and regulations that promotes sustainability and green buildings in the country. Due to the la ck of a national green building rating system in the KSA, LEED is used as a rating system but it does not apply properly to the Saudi Arabian climate, culture, and infrastructure. The Saudi Vision 2030 has set ahead the roadmap for future generations to pr osper and live their lives in a steady economic state where both the private and public sectors ncome and natural resources. Building Information Modeling (BIM) can greatly assist in establishing a cohesive building p erformance analysis to assure having an enhanced sustainable building design. It is evident that using BIM plugins to conduct a sun p ath analysis, life cycle assessment as well as carefully analyzing things such as solar, ventilation, heat gain, and energy efficiency and energy demand in buildings are important ways to enhance sustainability and encounter economic saving. Furthermore, t he study aims to develop a new BIM framework to estimate the level of attainment of the KSA 2030 vision. Future research is recommended to assess the BIM framework to support multiple analysis functions and testing tools that can assist architects, enginee rs, and contractors with sustainable integration initiatives in the built environment. REFERENCES Almasoud, S. (2016). Tr ansforming Saudi Arabia: National Transformation Program 2020 Approved Retrieved from LONDON, UK: http:// www.shearman.com/~/medial/Files/NesInsights/Publications/2016/06/Transforming Saudi Arabia National Transform ation Program 2020 Approved PDF 061016.pdf AIA (2014) Integrated Project Delivery: An Updated Working Definition AIA Cal ifornia Council, Sacramento, CA [online]. Available from: http://www.aiacc.org/wp content/uploads/2014/07/AIACC_IPD.pdf. Asadi, E., da Silva, M.G., Antunes, C.H., Dias, L. and Glicksman, L. (2014) Multi objective optimization for building retrofit: A mod el using genetic algorithm and artificial neural network and an application. Energy and Buildings. 81 pp. 444 456. Burck, J., Marten , F., & Bals, C. (2013). The Climate change Performance Index: Results 2014.

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Future of Information Exchanges and Interoperability 81 Conca, J. (2015, July 24). U.S. Winning Oil W ar Against Saudi Arabia. Retrieved December 09, 2017, from https://www.forbes.com/sites/jamesconca/2015/07/22/u s winning oil war against saudi arabia/#231a59a81678 Cottrell, M. (2010). Guide to the LEED ® Green Associate exam. Hoboken: John Wiley & Sons, Inc. E IA. (2013). Overview: Saudi Arabia. U.S. Energy Information Administration (EIA) viewed 12/03 2014. Retrieved from ht tp://www.eia.gov/countries/cab.cfm?fips=SA EPA. (2014). Basic Information: Definition of Green Building. United States Environmental Protection Agency, viewed 3/9 2015. Retrieved from http://archive.epa.gov/greenbuilding/web/html/about.html Government of online: http:// vision2030.gov.sa/en . [ Google Scholar ] Gray, R. & Bebbington, J. 2001. Acco unting for the Environment, Sage. Hashmi, N. (2016). Saudi's Strategic Vision for 2030. Retrieved from Washington DC: Nati onal Transformation Program 2020. (2016). vision2030.gov.sa/sites/default/files/NTP_En.pdf Jurgenson, S.; Bayyari, F.M.; Parker, J. A comprehensive renewable energy program for Saudi Vision 2030. Renew. Energy Focus 2016, 17, 182 183. [ Google Scholar ] [ CrossRef ] Karam, S. (2010). Special report: Can Saudi Arabia fix its housing time bomb?, Reuters. Retrieved from http://www.reuters.com/article/2010/08/26/us saudi real estate idUSTRE67P2CQ20100826 Krygiel, E. & Nies, B. 2008. Green BIM: successf ul sustainable des ign with building information modeling, Wiley. com. Kibert, C.J., Sendzimir, J., and Guy, B.G. (2002). Construction Ecology Nature as the basis for green Buildings, 1st Edition, Spon Press, New York, NY. Kibert, C. J. (2007, November). The next generatio n of sustainable construction. Building Research and Information. https://doi.org/10.1080/09613210701467040 Langar, S., & Pearce, A. R. (2017). The Role of Building Information Modeling (BIM) in the implementation of Rainwater Harvesting Technologies and S trategies (RwHTS). Journal of Architectural Engineering,23(1). Leach, M., Stirling, A., & Scoones, I. (2010). Dynamic sustainabilities: technology, environment, social justice. Retrieved from https://www.taylorfrancis.com/books/9781136541 674 LEE, N. & GEOR GE, C. 2013. Environmental assessment in developing and transitional countries: principles, methods and practice, Wiley. Lew, A. A., Ng, P. T., Ni, C. C., & Wu, T. C. (2016). Community sustainability and resilience: Similarities, differe nces and indicator s. Tourism Geographies, 18, no. 1, 18 27. Retrieved from https://www.tandfonline.com/doi/abs/10.1080/14616688.2015.1122664 Lizarralde, G., Chmutina, K., Bosher, L., & Dainty, A. (2015). Sustainability and resilience in the built environme nt: The challenges of establishing a turquoise agenda in the UK.

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Future of Information Exchanges and Interoperability 82 Mosly, I. (n.d.). Barriers to the Diffusion and Adoption of Green Buildings in Saudi Arabia. Retrieved December 09, 2017, from http://www.ccsenet.org/journal/index.php/jms/article/view/54413 Mubarak, F. A. (1 999, June 1 7 1999). Cultural adaptation to housing needs: A case study, Riyadh, Saudi Arabia. In IAHS Conference Proceedings. Nguyen, T., Shehab, T. & Gao, Z. 2010. Evaluating sustainability of architectural designs using building infor mation modeling. T he Open Construction and Building Technology Journal, 4, 1 8. Rahman, S., & Khondaker, A. (2012). Mitigation measures to reduce greenhouse gas emissions and enhance carbon capture and storage in Saudi Arabia. Renewable and Sustainable En ergy Reviews, 16(5 ), 2446 2460. http://dx.doi.org/10.1016/j.rser.2011.12.003 Taleb, H., & Pitts, A. (2009). The potential to exploit use of building integrated photovoltaics in countries of the Gulf Cooperation Council. Renewable Energy, 34(4), 1092 1099. http://dx.doi.org/10.1016/j.renene.2008.07.002 Zafar, S. (2017, March 04). Green Building Rating Systems in MENA. Retrieved from ht tps://www.ecomena .org/green building mena/

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Future of Information Exchanges and Interoperability 83 Digital Twins of Urban Buildings with a D a ta and Computing Web Platform Xuan Luo 1 and Tianzhen Hong 2 1 Building Technology and Urban Systems Division, Lawrence Berkeley National Laboratory, Mail Stop 90R3147C, 1 Cyclotron Rd, Be rkeley, 94720; e mail: xuanluo@lbl.gov 2 Building Technology and Urban System s Division, Lawrence Berkeley National Laboratory, Mail Stop 90R3111, 1 Cyclotron Rd, Berkeley, 94720; e mail: thong@lbl.gov ABSTRACT More than half of the world population lives in urban areas. U.S. cities consume 70% of primary energy, produces 80% of GDP, and are facing challenges of aging infrastructure, impact of climate change and extreme weather events. With the growing visibility to city data, virtualized paradigms and integrated platforms of urban systems can inform urban scale analytics, and therefore help city policymakers to evaluate district and city scale energy efficiency issues and opportunities. This demo will showcase an open and free data and computing web platform CityBES, which uses CityGML based 3D city models, simulates building performance to identify retrofit measures that can cut building stock energy use by 50 %, and evaluates city wide PV potential. CityBES vis ualizes 3D GIS integrated building performance in dozens of metrics (e.g., energy, water, demand, cost, GHG, savings, and regulation compliance status) for each building at urban scale. There are three la yers in the software architecture of CityBES: the Da ta layer, the Algorithms and Software layer, and the Use Cases layer. The Data layer includes the weather data, and the CityGML 3D city models. The Software layer capsules the simulation cores Commercial Building Energy Saver (CBES) which is built upon Ene rgyPlus and OpenStudio. The Use Cases layer provides examples of potential applications. The demo intends to introduce some of the applications and workflows of CityBES at the data level, regarding data i ntegration, visualization and utilization. Functiona lities include integrating building data from different resources to compile and visualize building performance related database, and to construct city scale building energy models. Utilizing the models t o link and interact with district utility data and s ensor network data, the platform is able to simulate and predict the spatiotemporal energy fluctuations of cities. BUILDING DATA INTEGRATION CityBES leverages existing data from several sources that are compiled into a central database, including assessor sources are combined and integrated into CityGML files to represent 3D city models in the database. CityBES uses typical mete orological year weather data in EnergyPlus simulatio ns, and allows user defined weather data measured at local stations. For retrofit analysis, CityBES integrates more than 100 energy conservation measures (ECMs) with technical performance data

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Future of Information Exchanges and Interoperability 84 as well as cost data. Economic data such as energy costs, inves tment costs, discount rate and payback years are also incorporated. The integrated database provides the majority of the data required for urban building energy modeling and performance analysis. BUILDING PERFORMANCE DATA ANALYSIS AND VISUALIZATION CityBES performs district to city scale building energy simulation, and provides performance analysis results in many applications, including energy benchmarking, urban energy planning, energy retrofit analysis , building operation improvement. CityBES renders a 3D view of the city building stock to visualize these performances. A suite of performance metrics of buildings can be visualized by color coding the 3D view of the buildings, including site or primary en ergy use (absolute amount or per floor area), greenh ouse gas emissions, whole building peak electric demand, Energy Star score, retrofit energy savings, weekly operating hours, energy use breakdown into end uses (lighting, plug loads, cooling, heating, and process loads), and code and compliance status. Mor eover, monthly utility data of the buildings can be used to fine tune the baseline model before retrofit analysis to estimate energy savings of ECMs. DIGITAL TWINS OF URBAN BUILDINGS Modeling the urban b uildings integrated with city utility data and live measurement data from city sensor network, the CityBES platform has the potential to learn and connect the spatiotemporal information of the city. Spatiotemporal fluctuations of the city, in terms of buil ding energy demands and consumption, are enabled thr ough virtualization at the real time intersection of Internet of Things. Analytical results can be used to evaluate and optimize urban system design decisions and development options. The digital twins of urban buildings, virtualized with CityBES, can help stakeholders understand dynamics of building stock changes, technology evolution and policy change related issues, such as evaluating city energy resilience considering the deployment of renewable energy , energy storage, electric vehicles, and advanced co ntrol strategies. To conclude, CityBES offers insights into resource efficiency, environmental sustainability, and ormance and growth, leveraging emerging opportunitie s in big data and artificial intelligence. References: Y. Chen, T. Hong, X. Luo. Development of City Buildings Dataset for Urban Building Energy Modeling, Energy and Buildings, 2018. Y. Chen, T. Hong, M. A. Piette. Automatic Generation and Simulation of Ur ban Building Energy Models Based on City Datasets for City Scale Building Retrofit Analysis. Applied Energy, 2017. T. Hong, Y. Chen, S.H. Lee, M.A. Piette. CityBES: A Web based platform to support city sc ale building energy efficiency. Urban Computing, Aug ust 2016, San Francisco. T. Hong, Y. Chen, M.A. Piette, X. Luo. Modeling City Building Stock for Large Scale Energy Efficiency Improvements using CityBES. ACEEE Summer Study, 2018.

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Future of Information Exchanges and Interoperability 85 Data Integration and I nnovation: The Future of the Construction, Infrastru cture, and Transportation Industries Ron Perkins 1 , C. Douglass Couto 2 , and Aaron Costin, Ph.D. 3 1 Jobsite Technology Group, LLC; e mail: rperkins@jobsitetechgroup.com 2 Former CIO at the Michigan Departme nt of Transportation and Senior Fellow at the Center for Digital Government; dougco28@outlook.com 3 M.E. Rinker Sr., School of Construction Management, University of Florida; e mail: aaron.costin@ufl.edu A BSTRACT There can be no doubt of the impact emergi ng and innovative technology is making across the entire construction industry. From planning, design, construction, and facilities or asset s are also becoming more prevalent in the infrastructure and transportation industries. There are challenges to consider when adopting new software or hardware solutions, in which people can be the biggest hurdle. Business owners must be convinced the ROI is there and users must see that the lear ning curve is not so disruptive that it impacts the project schedule. There can also be reluctance to embrace agrees th at IT makes sense and it is inevitable in the coming years. The questions that need to be addressed are what to adopt and how to do it remain the primary concerns? With examples from the transportation industry, this paper discusses the latest practices, c hallenges, practical solutions, and the ou tlook of information technology and data integration in the construction, infrastructure, and transportation Industries. I NTRODUCTION With an ever expanding list of devices and means of field data acquisition tied to project delivery systems , it is growing more important every day to automate or streamline as many of these data paths as possible. It is also essential to design an effective method to realize data integration and interoperability between the various in formation systems (Costin and Eastman 2019 ). Efficient interaction between devices and applications and reduces the time and effort needed for communication and information exchange among different stakeholders during the project lifecycle. Leveraging thes e technologies is critical because of the accuracy and efficiency they bring to the project. Incorporating this data into project workflow while maintaining integrity is only the first step in the process. Infotech 2 developer that has a project go ing with Leica and HNTB to streamline the path for inspection data coming from the Leica rover and bringing that data into the Appia® construction administration 2 https://www.infotechinc.com/

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Future of Information Exchanges and Interoperability 86 software us ed to manage the inspection data. Maintaining the data and adding functionality to manipulate or run analysis during project delivery is the stage where the greatest benefits will be achieved. Consider ing the latest statistics from Dodge Analytics (2019), McKinsey Global Institute (2017), KPMG International (2019), and others, there is a sense for what is being referred to as the many of them to a digital wor kflow. Plan distribution, bidding, and invoicing have all migrated in that directio n. The benefits include more efficient processes with a higher level of accuracy. According to Command Alkon 3 , their eTicketing solution for concrete saves on average ten m inutes per load, per day t hat equates to an extra load can be obtained almost ever y day. This is just one of many examples throughout the AEC industry. C URRENT PRACTICE option levels for construction firms: Innovative Leaders at the top 20%; Followers i n the middle 60%; study further illustrates the fact that those Innovative L eaders are not only ahead of the curve with well known technology such as laser scan ning, rovers and drones, they are now leveraging that expertise in emerging technology like artificial intelligence ( AI ) , Predictive Analytics and the internet of things ( I oT. ) The point here is that software and hardware dev cycles are increasing, not dec reasing. This means that the longer it takes for many of the Behind the Curve firms to begin on this journey they grow further behind than they probably even know. That s ame study states that 70% of construction companies believe those who do not adopt d igital ways of working will go out of business. The next level of innovation comes from hardware and software developers. Firms , such as Leica 4 , have introduced faster and more accurate laser scanners, rovers, and total robotic stations. The use of drones has exploded with departments of transportation ( ) , contractors , and inspectors working on construction projects. Virtual Reality and Augmented Reality ( VR/AR ) are now coming into the fold with leading edge firms looking for better ways to communicate and collaborate more effectively with owner agencies, engineers, and other project team members. Building Information Modeling (BIM) has the potential to be the sa me catalyst it was in the vertical construction market. According to Federal Highway Adminis tration ( FHWA ) , BIM is a collaborative work method for structuring, managing, and using data and information about transportation assets throughout the lifecycle (F Florida DOT, have joined the Transportation Poo led Fund TPF 5(372) BIM for Bridges 5 initiative along with FHWA and software vendors. BIM has been a paradigm shift in the building 3 http://com mandalkon.com/getetickets/ 4 https://leica geosystems.com/ 5 https://bimforbridgesus.com/

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Future of Information Exchanges and Interoperability 87 environment, so the transport ation industry is developing ways to integrate these technologies and solutions for transport ation and infrastructure projects. With several states now working on their Model as Contract programs, it is inevitable that anyone working on a transportation p roject is going to have to know how they interact with the model during the bid, build, and h andover process. THE IMPORTANCE OF DATA AND KNOWLEDGE MANAGEMENT IN TRANSPORTATION The endgame of all this data is better lifecycle asset management, which is d riving BIM and many of these other technologies. 3D modeling has been widely adopted across t ransportation and infrastructure projects and it is well known that Bentley was helping firms design in 3D long before Autodesk. The demand now is not just to help firms design better, but to have better visualization, improved communication, and more effe ctive collaboration. These reasons are tangible benefits and should be considered when embracing 3D and the growing demand for model as the contract. What cities, states, and other owners and agencies are asking now is: how can I better manage my assets, p hysical and digital, for the life of the asset? In the transportation sector this does not just mean identifying guardrail location or streetlight condition anymor e. The new assets will include sensors and cameras and other real time data that are applied to what many refer to as Smart City technologies. The advances in technology, applications, and our ability to deploy the array of innovative solutions has the pot ential to revolutionize the transportation industry. It should be noted all these solutions rely on abundance of dat a . Transportation organizations have relied on data for planning, design, building and maintenance of road and bridge infrastructures , as t hey understand that data is a valuable resource. As we gather more data about our transportat ion systems, we are now beginning to understand the importance of data as an enterprise asset that like other assets must be managed and developed to remain valuab le. Also, the emerging technologies and the processes that will evolve as a result will chall enge the next generation of employees. The American Association of State Highway and Transportation Officials (AASHTO) recognized the impact of this data surge for ming the AASHTO Data Management and Analytics Committee and the Knowledge Management Committe e. These committees were instrumental in consuming the work of the National Cooperative Highway Research Program (NCHRP) reports related to Information and Knowle dge Management (KM) research projects. There were three core projects that provided a set of tools to transportation leaders about how to create better programs to support transportation systems and have formed a foundation for later research. The panels also adopted defin itions of common terms to create a better understanding of these concepts. NCHRP Report 829, Leadership Guide for Strategic Information Management for State Departments of Transportation (NASEM 2016a). The guide provides a direction for creating a program, establishing policies, and implementing a strategy. It targets the c l evel suite and division managers.

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Future of Information Exchanges and Interoperability 88 NCHRP Report 846, Improving Findability and Relevance of Transportation Inform ation (NASEM 2017). The guide addresses the need for cooperation between business units and the tools that are needed to help employees find the information they need. NCHRP Report 813, A Guide to Agency Wide Knowledge Management for State Departments o f Transportation (NASEM 2015a). This guide provides a course of action for developing an enterprise knowledge management plan and program. The work continues as later research is adding to the necessary tools and addresses the emerging concerns aroun d cybersecurity and privacy. NCHRP Document 221, Protection of Transportation Infrastructure from Cyber Attacks: A Primer (NASEM 2016b) NCHRP Report 754, Improving Management of Transportation Information (NASEM 2013). NCHRP Report 814, Data to Support Tr ansportation Agency Business Needs: A Self Assessment Guide (NASEM 2015b). NCHRP SCAN 12 04, Advances in Transportation Agency Knowledge Manag ement (Halikowski et al. 2014). These systems rely on trusted data sources for all aspects of the enterprise busi ness activities. Those who use the data must be confident that the data are accurate. Around 1997, the Michigan DOT decentralized operations to bring delivery closer to their customers at the local levels. The reorganization required better improved shari ng of data and better knowledge management. The chief information officer created a governance structure with a steering committee and designa ted data owners for each of the data elements. Data owners were the only people who could make changes/correction s to the data based on the guidance from the steering committee and their functional business knowledge. There was a time when people would s hop the department for answers that supported a specific agenda. This was possible because every business unit we re stewards of a unique data source. The AASHTO Data Management and Analytics Committee (AASHTO 2013) was established to address the collec tion, processing, analytics, reporting, and sharing of data within a multimodal transportations organization to su pport the entire program and project lifecycles. The vision is for the data to help transportation leaders make better informed decisions such as allocating resources to support the project life cycle rtation systems. The committee working with the other AASHTO committees and the US DOT data leadership promulgated seven core data principles (AASHTO 2013):

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Future of Information Exchanges and Interoperability 89 Principle 1 VALUABLE: Data is an asset; Data is a core business asset that has value and is manag ed accordingly. Principle 2 AVAILABLE: Data is open, accessible, transparent, and shared; Access to data is critical to performing duties an d functions, data must be open and usable for diverse applications and open to all. Principle 3 RELIABLE: Data quality and extent is fit for a variety of applications; Data quality is acceptable and meets the needs for which it is intended. Principle 4 AUTHORIZED: Data is secure and compliant with regulations; Data is trustworthy and is safeguarded from unauthori zed access, whether malicious, fraudulent, or erroneous. Principle 5 CLEAR: There is a common vocabulary and data definition; Data dictionar ies are developed, and metadata established to maximize consistency and transparency of data across systems. Principle 6 EFFICIENT: Data is not duplicated; Data is collected once and used many times, for many purposes. Principle 7 ACCOUNTABLE: Decision s maximize the benefit of data; Timely, relevant, high quality data are essential to maximize the utility of data for decision making. It is the g technologies. With the m ounting topics and research, data is at the heart of each. One could argue that data powered the models and innovative uses of these emerging technologies. There has been an ongoing debate about the role of Information Technology (IT) and Operational Tech nology (OT) in managing these technologies, in which both are needed for success. The information and communications technology (ICT) traditionally managed by a chief information officer (CIO) or chief technology officer (CTO) bring the skills, technologie s, and processes to collect, store, and manage the data. The deployment of transportation technologies that support functional business activities works best when handled by those with business expertise. Another argument is that a balanced team would in clude I CT professionals who know the business operations and OT professionals who understand the challenges for managing the infrastructure needed to use functional data and information. DATA INTEGRATION CHALLENGES AND SOLUTIONS There are still significan t chall enges in accomplishing this streamlined data path (Costin et al. 2018). First is the human component. Attempts to force change in workflow presents a multitude of challenges from training and education to overcoming resistance from individuals who feel l ike: Adding to that potential complexities and impact on project schedule, while staff members are working their way over the learning curve with new technologies or business processes and successful results could be di fficult to obtain. Second, there are software and technology challenges. Moving data from devices to applications and then to other applications, also referenced as interoperability, also present a variety of challenges. Solutions including software vendor s provi ding open application programming interface (API) and the use

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Future of Information Exchanges and Interoperability 90 of neutral exchange standards, such as IFC, are being utilized to mitigate some of these challenges. However, often times competitive software companies do not make it easy to move data f rom the ir solutions into others in the hope that they hold the data captive and thus the user committed to their software suite as well. Third, t he increase in data , IoT , and AI will expand the technology risks and exposure to cybersecurity attacks. We are witnes sing transportation organizations being attacked by bad actors and those seeking to enrich themselves through ransomware attacks or worse simply disrupt our daily operations. There is also a risk associated with loss of services through natural disa sters a nd other local events that impact critical ICT infrastructure. These issues are addressed when the organization develops their resilience plans. Critical technologies, data, information, and knowledge must be protected to assure continuity of the o peratio ns. The Florida DOT is a leader in addressing the challenges for data and knowledge management and presented a model that addresses people, processes, and technologies. They are demonstrating the necessity of managing transportation technology an d the a ssociated data as an enterprise asset ( FDOT 2019). Namely the Data Governance (001 325 064) establishes data governance as a priority, and the Enterprise Technology Governance ( 001 325 062) establishes a technology governance structure to effectivel y suppo rt the delivery of the Work Program, align technology and data, automate services, improve customer experiences, and bolster safety and connectivity on Florida roadways. T he CIO/CTO community has successfully used this construct for deploying techno logy so lutions. The Florida approach takes it to the next level to include both the IT and OT communities. Significantly, this model forces them to work together, identify the business needs, and address gaps in strategy, technologies, people skills, proce sses, a nd investments. An important aspect of future deployment is also making information and data available when needed to allow for repeatable results when used by employees. The concepts associated with knowledge management provide these tools. Transp ortatio n organizations are concerned about the impact of an aging workforce that is also becoming more mobile. The result is a loss of knowledge when people move on to new chapters of their life through retirement or new career opportunities. AASHTO estab lished the Committee on Knowledge Management (KM) to address these emerging issues (AASHTO 2019). A KM program can help a transportation organization manage the challenges of a transitional workforce. When considering the knowledge gained by employees work ing wit h and deploying the next generation of transportation technologies, a great deal can be lost during a transition. The KM Committee defines Knowledge Management as an umbrella term for a variety of techniques that retains the know how of transportat ion emp loyees. While there may be some application and technology considered in creating a KM program, the real driver is , and not the data in the system. When developing a KM program, the focus is on the peo p le and the processes used by the organization with less emphasis on technology.

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Future of Information Exchanges and Interoperability 91 The Virginia DOT is a recognized early adopter of a KM program. They were faced with a huge loss of knowledgeable people due to a large bubble of retirements. The department n eeded t o figure out how to transfer the knowledge that was about to leave. VDOT explains the difference between information management and knowledge management this way: If we only needed information to get things done, then institutions would just be ma nuals a nd procedures, but it takes more than information to perform a function, particularly one why to do it a particular way Michigan DOT morphed their knowledge and data programs along a lengthy timeline that started when they were migrating to client server technology (TRB 2016). They created data sources to ourney when faced with huge employee reductions and the requirement to build new management systems mandated by the Intermodal Surface Transportation Efficiency Act (ISTEA) of 1991. While the an chose to complete the central databases that became the single trusted source for data about the program. As the Michigan DOT continued to adopt new technologies for e construction, they applied the concepts from their knowledge management program to be sure that the data and information captured from all parties involved with a construction project are given access to the knowledge and information (TRB 2016). People have access to the information they need to perform the many tasks associated with deli vering a project. CONCLUSION AND FUTURE OUTLOOK The recent Commercial Real Estate study performed by Deloitte (Deloitte Center for Financial Services 2019) states that investors want companies to prioritize predictive analytics and business intelligence to make buildings future ready. The significance of this study is that it clearly illustrates the fact that the commercial construction market has moved on beyond BIM. Virtual Design and Construction (VDC) practices have become the norm in the vertical build ing industry. The Transportation Research Board (TRB) studies and those done by countless universities and others across the country all suggest that the horizontal market is following the path of vertical. This provides us with a glimpse into the future. Many of these disruptive construction technology innovations are already here. There is a wealth of statistical data and studies that have been done whose data can be used to help construction businesses of all sizes determine their path and where the mos t ROI will come from. As mentioned before, the risk versus reward can only be measured by each organization. There is a benefit to wait and see and learn from the pioneers. There could also be a significant risk as those early adopters not only become m ore proficient with the technology others have yet to adopt but are also moving on the next phases to benefit their organization, their projects and their clients.

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Future of Information Exchanges and Interoperability 92 Throughout the process of adopting data integrated solutions and shifting from paper centri c p ractices to digital solutions there are countless benefits. The most obvious are removing redundancies of multiple data entries by all parties involved in the data capture and usage cycle. The risk of human error when data is manually transferred from one system to another are always very high. Developing methods to acquire this data directly from the device that captured it, e.g. rovers, cameras, drones, etc., will not only all but eliminate the margin of human error it could also incorporate more met ada ta associated with the source file. Once the digital data has been captured, transferring that content from one system to another also becomes less of a challenge if neutral exchange standards are used. On October 9, 2019 The American Association of Sta te Highway Transportation Officials (AASHTO) signed an Administrative Resolution AR 1 19 Title: Adoption of Industry Foundation Classes (IFC) Schema as the Standard Data Schema for the Exchange of Electronic Engineering Data (AASHTO Board of Directors 20 19) . Data standards are a necessity for successful BIM programs and the integrations being developed today. Firms like Infotech are forming strategic partnerships with academics, public sector committees, and other consultants to gain knowledge and develop st rategies required to support the use of IFC. As we move forward with the implementations of the technologies and processes discussed during the recent events and forums, we are compelled to address the ever growing need for information, data, and knowle dge management systems and processes. Without them, industry organizations will be overwhelmed and drowned in the data created. A good approach is to ask: what question do these data answer and for whom do they serve? R EFERENCES American Association of Stat e and Highway Transportation Officials (AASHTO). (2013). https://data.transportation.org/aashto core data principles/> Accessed February 20, 2020 American Association of St ate and Highway Tra nsportation Officials (AASHTO). (2019). December 20, 2020 as the St andard Data Schema Administrative Resolution AR 1 1. for transportation infrastructure Literature review, applications, challenge s, and recommendati 281. Engineering, 33 (3), 04019008.

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Future of Information Exchanges and Interoperability 93 Delo < htt ps://www2.deloitte.com/content/dam/Deloitte/uk/Documents/real estate/2019 commercial real estate outlook.pdf > https://www.construction.com/toolkit/reports/q4 2018 commercial construction index > Inf s://www.fhwa.dot.gov/construction/bim/> Integrated Managemet. Halikowski, J., Burk, B., Dabling , L., Dexter, A., E llis, A., Hammer, M., Michel, C., Oman, L., 68A, Scan 12 04 < http://onlinepubs.trb.org/onlinepubs/nchrp/docs/NCHRP20 68A_12 04.pdf> KPMG Intern uture Ready Index: Leaders and Followers in the Engineerign https://assets.kpmg/content/dam/kpmg/xx/pdf/2019/04/global construction survey 2019.pdf> McKinsey Global Institute McKinsey and Company. National Academies of Sciences, Engineering, and Medicine (NASEM). (2013). Improving Management of Transportation Information. NCHRP Report 754. The National Academi es Press, Washingto n, DC. National Academies of Sciences, Engineering, and Medicine (NASEM). (2015a). A Guide to Agency Wide Knowledge Management for State Departments of Transportation. NCHRP Report 813The National Academi es Press, Washingto n, DC. National Academies of Sciences, Engineering, and Medicine (NASEM). (2015b). Data to Support Transportation Agency Business Needs: A Self Assessment Guide. NCHRP Report 814. The National Academies P ress, Washington, D C National Academies of Sciences, Engineering, and Medicine (NASEM). (2016a). Leadership Guide for Strategic Information Management for State Departments of Transportation. NCHRP Report 829. The National Academies Press, Washington, DC.

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Future of Information Exchanges and Interoperability 94 National Academies of Sciences, Engineering, and Medicine (NASEM). (2016b). Protection of Transportation Infrastructure from Cyber Attacks: A Primer. NCHRP Document 221. The National Academi es Press, Washington, DC. National Academies of Sciences, Engineering, and Medicine (NASEM). (2017). Improving Findability and Relevance of Transportation Information: Volume I A Guide for State Transportation Agencies, and Volume II Background Research. NCHRP Report 846. The National Academies Press, Washington, DC. Number 305, September October, p32.