Attributes to Org Charts: Using R and VIVO for Visualization of Research Activity ( Publisher's URL )
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 Material Information
Title: Attributes to Org Charts: Using R and VIVO for Visualization of Research Activity
Physical Description: Conference Papers
Creator: Conlon, Michael
Conference: Second Annual VIVO Conference
Publisher: University of Florida
Place of Publication: Washington, DC
Publication Date: August 25, 2011
Acquisition: Collected for University of Florida's Institutional Repository by the UFIR Self-Submittal tool. Submitted by Michael Conlon.
Publication Status: Published
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Source Institution: University of Florida Institutional Repository
Holding Location: University of Florida
Rights Management: All rights reserved by the submitter.
System ID: IR00000553:00001


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VIVO: Enabling national Networking of Scientists is supported by NIH grant U24 RR 029822. The UF CTSI is supported in part by NIH awards UL1 RR029890, KL2 RR029888 and TL1 RR029889 VIVO provides a unique opportunity to collect, curate and use data regarding research activity at and across institutions VIVO makes its data available publically via RDF Schema 1 an XML format Tools consuming RDF can operate on any VIVO as a data source R 2 an open source system for data management, analysis and visualization, is well suited for reading and displaying network data R libraries for reading XML 3 and constructing and displaying social networks 4 provide additional programming ease Here we extend work from last year 5 with R functions for collecting attributes for VIVO people, orgs, papers and grants, and using those attributes in large scale displays of an research activity We use the University of Florida as an example VIVO and R Use Cases Objects networks, and displays Attributes to Org Charts: Using R and VIVO for Visualization of Research Activity Mike Conlon, UF Clinical and Translational Science Institute, Gainesville, Florida R code generates objects (people, pubs, grants, orgs) from VIVO URIs and returns a list of attribute name value pairs org < person < (person.uri) grant < (grant.uri) pub < (pub.uri) A network can be constructed by using a driver function pointed at an org node. The driver function recursively processes the sub orgs, assembling a network object. The network object can be saved as a CSV file for processing in other tools. uf.uri< "" uf.n < (" UF", (uf.uri,0)) write.csv( ( uf.n ),file="uf data.csv") The network can then be displayed with node colors, sizes, shapes and labels determined by object attributes. png (file=" BigUFDepth.png",height =72,width=72, =72) plot( uf.n,displaylabels =T, vertex.col= get.vertex.attribute ( uf.n,"depth ")) The R tools developed can be used to explore research activities : 1. awarded, grant dollars, personnel, faculty 2. Compare organizations visually within an institution or across institutions 3. Compare results for subsets by time, e.g. comparing years 4. Show results for subsets of organizations 5. Show grants and publications as nodes attached to people and people as nodes attached to organizations 1 RDF Vocabulary Description Language 1.0: RDF Schema schema/ 2 R Project Home Page www.r 3 Lang, Duncan Temple Tools for parsing and generating XML in R, 4 Handcock, M., Hunter, D.R., Butts, C.T., Goodreau S.M. and Morris, M. (2003) Software Tools for the Statistical Modeling of Network Data. Version 2.1 1. Project home page at URL http://CRAN.R 5 2010 VIVO Conference, New York City, August, 2010. 6 Bastian M., Heymann S., Jacomy M. Gephi : an open source software for exploring and manipulating networks, American Journal of Sociology (2009), pp.361 362 7 R Project Archive http://cran.r References Visualizing the University of Florida The University of Florida consists of 537 organizations (excluding Shands Hospital organizations not shown here). Each org is cyan distance 5 and blue distance 6. The figure was produced using R software reading VIVO data from Future work for visualization of research activity : 1. Simplify aggregation of attributes at levels of the network 2. Add additional objects events, projects, data sets 3. Create a web site with user interface for specifying visualizations. Visualization can begin at any VIVO org URI 4. Consider using gephi 6 for network visualization 5. Create a CRAN 7 package for distribution Future Work

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