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Creating a Data Interchange Standard for Researchers, Research, and Research Resources: VIVO-ISF Dean B. Krafft Brian

Creating a Data Interchange Standard for Researchers, Research, and Research Resources: VIVO-ISF Dean B. Krafft Brian Lowe Coalition for Networked Information 10 December 2013. What is VIVO?. Software: An open-source semantic-web-based researcher and research discovery tool

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Creating a Data Interchange Standard for Researchers, Research, and Research Resources: VIVO-ISF Dean B. Krafft Brian

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  1. Creating a Data Interchange Standard for Researchers, Research, and Research Resources: VIVO-ISF Dean B. Krafft Brian Lowe Coalition for Networked Information 10 December 2013

  2. What is VIVO? Software: An open-source semantic-web-based researcher and research discovery tool Data: Institution-wide, publicly-visible information about research and researchers Standards: A standard ontology (VIVO data) that interconnects researchers, communities, and campuses using Linked Open Data Community: An open community with strong national and international participation

  3. NIH RePorter Researcher.gov VIVO Normalizes Complex Inputs VP Research HR data Univ. Communications Faculty Reporting Grants Tech transfer People Self-editing Grad School Data Research Facilities & Services Center/ Dept/ Program websites Publications HPC other databases Courses Other campuses arXiv Google Scholar Cross Ref Pubmed

  4. VIVO connects scientists and scholars with and through their research and scholarship

  5. SKE Knowledge Environment http://ske.las.ac.cn/

  6. Customization

  7. The VIVO Community is now over 100 institutions worldwide

  8. Why is VIVO important? It is the only standard way to exchange information about research and researchers across diverse institutions It provides authoritative data from institutional databases of record as Linked Open Data Structured VIVO data supports search, analysis and visualization across institutions and consortia It is highly flexible and extensible to cover research resources, facilities, datasets, and more

  9. An HTTP request can return HTML or data

  10. Value for institutions and consortia • Common data substrate • Public, granular and direct • Discovery via external and internal search engines • Available for reuse at many levels • Distributed curation • E.g., affiliations beyond what HR system tracks • Data coordination across functional silos • Feeding changes back to systems of record • Direct linking across campuses • Data that is visible gets fixed

  11. Example: U.S. Dept. of Agriculture Multiple agencies including Agricultural Research Service and U.S. Forest Service VIVO portal for 45,000 intramural researchers Goal to link to Land Grant universities and international agricultural research centers Using VIVO as an integration tool to send data for federal STAR METRICS/SciENCV projects RDF exposed via a SPARQL endpoint constitutes compliance

  12. VIVO Exploration and Analytics • Since VIVO is structured data, it can be navigated, analyzed, and visualized uniformlywithin or across institutions • VIVO can visualize the strengths of networks within and across institutions • You can create dashboards to help understand academic outputs and collaborations • VIVO can map research engagements and impact

  13. Providing the Context for Research Data • Context is critical to finding, understanding, and reusing research data • Contexts include: • Narrative publications • The researcher, research resources, grants, etc. • Dataset registries • Structured Knowledge Environments • The web of Linked Open Data

  14. VIVO Dataset Registries • VIVO/ANDS consortium in Australia • Link research data with researcher profiles and publications • Harvest to national registry • Datastar data registry tool • Add-on to VIVO or independent companion • Complement to other library data-related services • Institute for Museum and Library Services (IMLS) grant

  15. Melbourne Central Research Data Registry

  16. What is VIVO Today? An open community hosted by the DuraSpace 501(c)3 with strong national and international participation, for which we are currently hiring a full-time VIVO Project Director An open suite of software tools A growing body of interoperable data An ontology (VIVO-ISF) with a community-driven process for extension

  17. VIVO and the Integrated Semantic Framework

  18. What is the Integrated Semantic Framework? • A semantic infrastructure to represent people based on all the products of their research and activities • To support both networking and reporting • A partnership between VIVO, eagle-i, and ShareCenter • A Clinical and Translational Information Exchange Project (CTSAConnect) • 18 Months (February 2012 – August 2013) • Funded by NIH NCATS via Booz Allen Hamilton

  19. CTSAconnect Team OHSU: Melissa Haendel, Carlo Torniai, Nicole Vasilevsky, ShahimEssaid, Eric Orwoll Cornell University: Jon Corson-Rikert, Dean Krafft, Brian Lowe University of Florida: Mike Conlon, Chris Barnes, Nicholas Rejack Stony Brook University: Moises Eisenberg, Erich Bremer, Janos Hajagos Harvard University: Daniela Bourges-Waldegg Sophia Cheng Share Center: Chris Kelleher, Will Corbett, Ranjit Das, Ben Sharma University at Buffalo: Barry Smith, DagobertSoergel

  20. People and Resources genes affiliation anatomy roles techniques training publications protocols grants manufacturer credentials

  21. Connecting researchers, resources, and clinical activities

  22. Beyond Static CVs • Distributed data • Research and scholarship in context • Context aids in disambiguation • Contributor roles • Outputs and outcomes beyond publications

  23. Ontologies for Linked Data • First level text • Second level • Third level • Fourth level • Fifth Level

  24. Linked Data Vocabularies FOAF (people, organizations, groups) VCard (contact information) BIBO (publications) SKOS (terminologies)

  25. Open Biomedical Ontologies OBI (Ontology of Biomedical Investigations) ERO (eagle-i Research Resource Ontology) RO (Relationship Ontology) IAO (Information Artifact Ontology)

  26. Basic Formal Ontology Occurrent Process Continuant Spatial Region Role Site Szabolcs Toth http://www.flickr.com/photos/necccc/5726970855/

  27. Relationships Position Person Org. Author-ship Person Article

  28. Aggregate Data over Time Position Person Org. time interval

  29. Aggregate Data over Time Position1 Person Org. 1 time Interval 1 Position2 Org. 2 time Interval 2

  30. Aggregate Data over Time VCard Person Name time interval

  31. Aggregate Data over Time VCard 1 Person Old Name time Interval 1 VCard 2 New Name time Interval 2

  32. Aggregate Data over Time VCard Person Author-ship time interval

  33. Beyond Publication Bylines • What are people doing? • Roles in projects, activities • Other kinds of scholarly contribution • Datasets, resources Role Project Person

  34. Roles and Outputs Project Person Role document /resource / etc.

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