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VIVO: A Semantic Approach to Creating a National Network of Researchers Part II. Technical Design

J. Corson- Rikert M.Conlon , B.Lowe , B.Caruso , K.Börner , Y.Ding , D.Krafft , L.McIntosh ; VIVO Collaboration*. VIVO: A Semantic Approach to Creating a National Network of Researchers Part II. Technical Design.

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VIVO: A Semantic Approach to Creating a National Network of Researchers Part II. Technical Design

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  1. J. Corson-Rikert • M.Conlon, B.Lowe, B.Caruso, K.Börner, Y.Ding, D.Krafft, L.McIntosh; • VIVO Collaboration* VIVO: A Semantic Approach to Creating a National Network of ResearchersPart II. Technical Design *VIVO Collaboration: Cornell University: Dean Krafft (Cornell PI), Manolo Bevia, Jim Blake, Nick Cappadona, Brian Caruso, John Cline, Jon Corson-Rikert, Elly Cramer, Medha Devare, Diane Dietrich, John Fereira, Keith Jenkins, William Klinko, Carl Jay Lagoze, Brian Lowe, Holly Mistlebauer, Mary Anderson Ochs, Simeon Warner, Frances Webb, Christopher Westling, Rebecca Younes. University of Florida: Mike Conlon (VIVO and UF PI), Cecilia Botero, Kerry Britt, Erin Brooks, Amy Buhler, Ellie Bushhousen, Valrie Davis, Nita Ferree, Chris Haines, Rae Jesano, Margeaux Johnson, Sara Kreinest, Yang Li, Paula Markes, Sara Russell Gonzalez, Nancy Schaefer, Michele R. Tennant, George Hack, Chris Barnes, Narayan Raum, Alicia Turner, Stephen Williams. Indiana University: Katy Borner (IU PI), William Barnett, Shanshan Chen, Ying Ding,  Russell Duhon, Jon Dunn, Micah Linnemeier, Nianli Ma, Robert McDonald, Barbara Ann O'Leary, Mark Price, Yuyin Sun, Alan Walsh, Brian Wheeler, Angela Zoss. Ponce School of Medicine: Richard Noel (Ponce PI), Ricardo Espada, Damaris Torres.  The Scripps Research Institute: Gerald Joyce (Scripps PI), Greg Dunlap, Catherine Dunn, Brant Kelley, Paula King, Angela Murrell, Barbara Noble, Cary Thomas, Michaeleen Trimarchi. Washington University, St. Louis: RakeshNagarajan (WUSTL PI), Kristi L. Holmes, Sunita B. Koul, Leslie D. McIntosh. Weill Cornell Medical College: Curtis Cole (Weill PI), Paul Albert, Victor Brodsky, Adam Cheriff, Oscar Cruz, Dan Dickinson, Chris Huang, ItayKlaz, Peter Michelini, Grace Migliorisi, John Ruffing, Jason Specland, Tru Tran, Jesse Turner, VinayVarughese.

  2. VIVO under the hood • RDF • Simple format • Read and write standard data and ontologies • Leverage open source and now commercial tools • More and more data available on the Web (e.g., Bio2RDF) Subject Verb Object

  3. Query and compare • By individual • Everything about an event, a grant, a person • By type • Everything about a class of events, grants, or persons • By relationship • Grants with PIs from different colleges or campuses • By combinations and facets • Explore any publication, grant, or talk with a relationship to a concept or geographic location • Explore orthogonally (navigate a concept or geographic hierarchy)

  4. Advantages of an ontology approach • Provides the key to meaning • Defines a set of classes and properties in a unique namespace • Embedded as RDF so data becomes self-describing • Definitions available via the namespace URI • Helps align RDF from multiple sources • VIVO core ontology maps to common shared ontologies organized by domain • Local extensions roll up into VIVO core

  5. Information flow with shared ontologies Log boom on Williston Lake, British Columbia

  6. Information flow without shared ontologies Log jam, looking up the dalles, Taylor's Falls, St. Croix River, MN. Photo by F.E. Loomis

  7. Linked Data principles Tim Berners-Lee: • Use URIs as names for things • Use HTTP URIs so that people can look up those names • When someone looks up a URI, provide useful information, using the standards (RDF, SPARQL) • Include links to other URIs so that people can discover more things http://www.w3.org/DesignIssues/LinkedData.html http://linkeddata.org

  8. VIVO and Linked Data • VIVO enables authoritative data about researchers to become part of the Linked Data cloud Tim Berners-Lee, http://www.w3.org/2009/Talks/0204-ted-tbl

  9. Challenges in our approach • Granularity levels • Terminologies • Scalability • Disambiguation • Provenance • Temporality Jim Hendler, 1997 or 1998, http://www.cs.rpi.edu/~hendler/LittleSemanticsWeb.html

  10. Major VIVO Components • A general-purpose, open source Web-based application leveraging semantic standards • Customizations of this application for VIVO • Ontology • Display theming • Installation • Additional new software to enable a distributed network of RDF by harvesting from VIVO instances or other sources

  11. VIVO’s 3 functional layers Search and browse interface end users Editing Display, search and navigation setup curators Curator editing Ontology Editing ontology editing & data flow Data ingest Data export

  12. Local data flow local systems of record data ingest ontologies (RDF) > VIVO (RDF) shared as RDF > > national sources > interactive input

  13. From local to national National Via http://www.vivoweb.org browse search share as RDF visualize text indexing Local search browse visualize filtered RDF local sources • Cornell University • University of Florida • Indiana University • Ponce School of Medicine • The Scripps Research Institute • Washington University, St. Louis • Weill Cornell Medical College > > VIVO share as RDF nat’l sources website data

  14. National networking Future VIVO Scripps VIVO UF VIVO WashU VIVO Future VIVO Future VIVO IU VIVO Ponce VIVO Other RDF Other RDF RDF Triple Store WCMC VIVO Prof. Assn. Triple Store Visuali- zation Cornell VIVO Other RDF RDF Triple Store Search Regional Triple Store Other RDF Linked Open Data Search

  15. Network Analysis & Visualization • At the individual investigator level • In-page, small graphs highlighting publication history, collaborations or co-authorship networks • At the department or institutional level • Trends in research grants or publications • Collaboration networks across a larger group • Topical alignment with base maps of science • At the network level • Patterns and clusters by geography, topic, funding agency, institution, discipline

  16. Animated co-authorship network

  17. VIVO deployments at our 7 sites • Before Release 1 • Familiarization with tools • Ontology experimentation • With Release 1 • Deployment on production hardware • Mapping local data to R1 ontology • Batch data ingest (extract-transform-load)

  18. Development teams • Cornell • VIVO itself • Usability and interface • Network aggregator • Semantic search • Reasoning • Ontology versioning • Indiana • Network analysis and visualization • Ontology design and mapping • Florida • Data acquisition • Data ingest • Identity management • Packaging • All 3 teams • Deployment • Documentation • Testing • All sites • Implementation • Evaluation and feedback

  19. Questions?http://www.vivoweb.org Andy Goldsworthy

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