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The Research Lifecycle: Partnering for Success March 15, 2013 Salt Lake City, Utah

The Research Lifecycle: Partnering for Success March 15, 2013 Salt Lake City, Utah Michael Conlon, PhD Clinical and Translational Science Institute University of Florida. Six Trends. 1. Rise of the small. PubMed new publications per year. 2. Increasing v olume of science.

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The Research Lifecycle: Partnering for Success March 15, 2013 Salt Lake City, Utah

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  1. The Research Lifecycle: Partnering for Success March 15, 2013 Salt Lake City, Utah Michael Conlon, PhD Clinical and Translational Science Institute University of Florida

  2. Six Trends

  3. 1. Rise of the small

  4. PubMed new publications per year 2. Increasing volume of science

  5. 3. Increasing complexity of scientific problems The Problems Got Hard

  6. Data Got Big (IDR Slide) 4. Big Data

  7. 5. Competition rises 2012 Shanghai ranking of world universities http://en.wikipedia.org/wiki/Academic_Ranking_of_World_Universities Lots of Competitors

  8. 6. Internet disintermediation of science continues

  9. How can we know what is going on, build teams, solve data-driven problems?

  10. Research Discovery Research Discovery

  11. … And the connections between them

  12. VIVO: Data, Tools and Community

  13. Simple tools for presentation, traversal, search

  14. ScienceMap. Examine collections of publications for individuals, work groups, institutions

  15. Co-Funded Network Chris McCarty& Raffaele Vacca, UF Bureau of Business and Economic Research 2008 2012 • Data source: UF Division of Sponsored Research award data • Each node represents one Contract PI, Project PI or Co-PI linked by a common PeopleSoft Contract number • Nodes are sized by Total Awarded in UF fiscal year (July-June) • Main Component: what changes have occurred between 2008 and 2012? • More of Health Science Center comes under the CTSI umbrella • The CTSI has a broader reach in the whole network • Increasingly the CTSI incorporates all researchers in relevant areas (areas not relevant to CTSI research fields naturally remain out of its network)

  16. Ontology Process

  17. Everything has identifiers

  18. Software reads VIVO RDF and displays processOrg<-function(uri){ x<-xmlParse(uri) u<-NULL name<-xmlValue(getNodeSet(x,"//rdfs:label")[[1]]) subs<-getNodeSet(x,"//j.1:hasSubOrganization") if(length(subs)==0) list(name=name,subs=NULL) else { for(i in 1:length(subs)){ sub.uri<-getURI(xmlAttrs(subs[[i]])["resource"]) u<-c(u,processOrg(sub.uri)) } list(name=name,subs=u) } } VIVO produces both HTML and RDF

  19. Community

  20. Augmenting data

  21. VIVO Searchlight

  22. Mentoring

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