attributes to org charts - ufdcimages.uflib.ufl.edu
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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 Schema1, an XML format. Tools
consuming RDF can operate on any VIVO as a data source.
R2, an open source system for data management, analysis and
visualization, is well-suited for reading and displaying network data.
R libraries for reading XML3, and constructing and displaying social
networks4, provide additional programming ease.
Here we extend work from last year5, with R functions for collecting
attributes for VIVO people, orgs, papers and grants, and using those
attributes in large scale displays of an organization’s 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 ActivityMike 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 <- get.vivo.org(org.uri)
person <- get.vivo.person(person.uri)
grant <- get.vivo.grant(grant.uri)
pub <- get.vivo.publication(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<-"http://vivo.ufl.edu/individual/UF/UF.rdf"
uf.n<-vivo.network("UF",get.vivo.orgs(uf.uri,0))
write.csv(vivo.data.frame(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,
units=“in”,res=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. Show organizations “size” in terms of papers produced, grants
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
1RDF Vocabulary Description Language 1.0: RDF Schema
http://www.w3.org/TR/rdf-schema/2R Project Home Page www.r-project.org3Lang, Duncan Temple Tools for parsing and generating XML in R,
http://www.omegahat.org/RSXML/4Handcock, 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 http://statnet.org, URL
http://CRAN.R-project.org/package=statnet5Conlon, M. and the VIVO Collaboration “Using the R Programming
Language for VIVO Application Programming,” poster presented at
2010 VIVO Conference, New York City, August, 2010.6Bastian M., Heymann S., Jacomy M., Gephi: an open source
software for exploring and manipulating networks, American Journal
of Sociology (2009), pp.361-3627R Project Archive http://cran.r-project.org
References
Visualizing the University of Florida
The University of Florida consists of 537 organizations (excluding Shands Hospital organizations not shown here). Each org is
colored by its “distance” from UF. Red nodes are distance one, orange distance two, light green distance 3, green distance 4,
cyan distance 5 and blue distance 6. The figure was produced using R software reading VIVO data from vivo.ufl.edu
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 gephi6 for network visualization
5. Create a CRAN7 package for distribution
Future Work