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Charleston Conference: VIVO, libraries, and users.

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A presentation on what VIVO is, why it is implemented in the library, and how the interface is influenced by the user and user behaviors. …

A presentation on what VIVO is, why it is implemented in the library, and how the interface is influenced by the user and user behaviors.

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  • Presentation Goals: To provide a general overview of VIVO: semantics, profiles, search. How libraries fit in. Why semantics and how it can create a federated search, browse, and visualizations
  • VIVO is funded by the NIH, specifically the NCRR (National Center for Research Resources).
    Stimulus money from the American Recovery and Reinvestment Act (ARRA)
  • Cornell – UF – NIH grant

    International – National Science Library, Chinese Academy of Science (3 instances, visiting scholar at CU translating materials) and University of Melbourne in Australia (Research data and records registry).

    3 releases, a successful conference in Queens, and have garnished the interest of many universities, USDA, Star Metrics, CTSAs, SUNY and FL state schools
  • What is VIVO?

    It’s a semantic web application with rich profiles that display publications, teaching, service and professional affiliations. Faceted search for fast and meaningful results.
    ---------

    Foster team science by providing tools for identifying potential collaborators.
    Improve collaboration by creating tools using this information for enhancing new and existing teams.
    Not limited to science – at Cornell, VIVO covers all disciplines across the entire institution

    Talking points:
    Profiles are largely created via automated data feeds, but can be customized to suit the needs of the individual.
    Information is open source (free) and is stored in a framework that allows for exporting to other applications.
    Profiles are richer in content than typical [web pages or] social networking sites and will rank higher in general internet searches.

  • Semantic/ontology definitions (below RDF), Elly in RDF example for visual, point out links.
  • Simple semantic advantage

    Semantic web: describes methods and technologies to allow machines to understand the meaning or "semantics” of information on the web. -- W3C director Sir Tim Berners-Lee

    Ontology: a formal representation of the knowledge by a set of concepts within a domain and the relationships between those concepts. -- Wikipedia
  • Who uses VIVO?
    In addition to the faculty and researchers, it’s also useful to funding agencies, students, and administrators. These users will come from within and outside of the participating institutions.
    The technology is versatile and flexible making it responsive to innovation and user needs

    Talking points:
    VIVO is useful to many different users and audiences. Users will come from within and outside of the participating institutions.
    The technology is versatile and flexible enough to easily accommodate changes based on new and innovative demands that users make as they utilize VIVO.
  • Faceted search, simple and flexible, based on ontology hierarchy.
  • Authoritative data, diverse formats, filter out private information
    Centralizes the information into a pool to draw on (the bucket)

    Talk about verified data
    Talking points:
    Much of the data in VIVO profiles is ingested from authoritative sources so it is accurate and current, reducing the need for manual input.
    Private or sensitive information is never imported into VIVO. Only public information will be stored and displayed.
    Data is housed and maintained at the local institutions. There it can be updated on a regular basis.

    There are three ways to get data: internal, external, individuals. Internal is authoritative!

    Examples of internal data – Faculty reporting, course listings, grants, directory
    Examples of external sources – Pubmed
    Manual – affiliations, geographic locations
  • Since VIVO stores profile information drawn from a variety of sources in a single, flexible format, it can be easily “re-skinned” or “re-purposed” to present specialized views into the institution.

    For example:
    Graduate Programs in the Life Sciences - geared toward a specific user – prospective graduate students in the life sciences
    CALS Research Portal - Or a filtered view for a specific department
    CALS Impact statements- repurposed in a CMS (Drupal), development only
    Faculty profiles in Classics - have a dept pulling faculty profiles into Common Spot
  • How is this data stored?

    Talking points:
    Simple format
    Based on triples
    Shared ontology, giving meaning to names and terminologies
  • Example – Mike Conlon.
    See URI for Mike - html view (human readable), marbles RDF view (application use), straight-up RDF (machine readable)
  • RDF browser of Mike’s information…. person, thing, etc
    Keep going, you get more data.
    Machine and human readable
    Semantically labeled data, not just text.
  • Feel for the VIVO ontology, Point out examples of relationships or Susan Riha.
  • Individual, institution, network
  • National exemplar
    search, browse, share as RDF
    visualization – Katy Borner at Indiana University
    Mapped to the much larger world of the semantic web.

    Anyone running VIVO will provide this RDF data with a unique namespace. Marked from an institution and considered authoritative data.

    VIVO enables authoritative data about researchers to join the Linked Data cloud
  • Part of the solution

    Libraries are posed to meet participation challenges due to their role on campus as information resource and technology centers.

    Librarians are subject matter experts, understand their user’s needs and institution’s research environment.

    In VIVO-funded institutions, the librarians are the ones negotiating with the owners of local data sources to explain what data we need and why we need it.

    The library is a stable and natural home for VIVO, but the implementers need to work closely with the institution’s administration and faculty.
  • So what do librarians DO?

    Identification of content types – ontology ;development and interface refinement
    We negotiate with the owners of local data sources to explain what data we need and why we need it.

    We provide local and national support and training through the development of documentation, presentations and help-desk services

    Using the vivoweb.org website we liaise with potential collaborators – giving demos and answering questions
    Creating a community of support
    And delivering usability feedback to the technical team.

    Marketing – through demonstrations, conferences, workshops and the development PR materials designed both to attract new participants and to assist participants with local adoption
  • Notes to self: Need to create a diagram like in the Mental Models book and pull more features out .
    Mental Models: Aligning Design Strategy with Human Behavior, Indi Young, Rosenfeld Media, Brooklyn, NY 2008
  • Weighted by frequency of keyword and priority
  • Development guided by user analysis and feature list from scenarios.
  • Download, Adopt, and Implement:  VIVO is open source and is available for download.

    Provide Data:  You can participate by providing machine readable data for research discovery.  Bibliometric and funding data are of great interest to the research community. 

    Develop Applications: Many software applications can benefit from using information that will be provided by the national network. External application development: enhanced search, new collaboration capabilities, grouping, finding and mapping scientists and their work. Anything that will leverage VIVO and the semantic cloud.
  • Transcript

    • 1. Presented by: Ellen J. Cramer Ph.D. Research Associate Cornell University ejc12@cornell.edu A Closer Look at VIVO
    • 2. Cornell University: Dean Krafft (Cornell PI), Elly Cramer (Co-PI), Manolo Bevia, Jim Blake, Nick Cappadona, Brian Caruso, Jon Corson-Rikert, Elizabeth Hines, Huda Khan, Brian Lowe, Joseph McEnerney, Holly Mistlebauer, Stella Mitchell, Anup Sawant, Christopher Westling, Tim Worrall, Rebecca Younes. University of Florida: Mike Conlon (VIVO and UF PI), Chris Barnes, Cecilia Botero, Kerry Britt, Amy Buhler, Ellie Bushhousen, Linda Butson, Chris Case, Christine Cogar, Valrie Davis, Mary Edwards, Nita Ferree, Chris Haines, Rae Jesano, Margeaux Johnson, Sara Kreinest, Meghan Latorre, Yang Li, Hannah Norton, Narayan Raum, Alexander Rockwell, Sara Russell Gonzalez, Nancy Schaefer, Dale Scheppler, Nicholas Skaggs, Matthew Tedder, Michele R. Tennant, Alicia Turner, Stephen Williams. Indiana University: Katy Borner (IU PI), Kavitha Chandrasekar, Bin Chen, Shanshan Chen, Jeni Coffey, Suresh Deivasigamani, Ying Ding, Russell Duhon, Jon Dunn, Poornima Gopinath, Julie Hardesty, Brian Keese, Namrata Lele, Micah Linnemeier, Nianli Ma, Robert H. McDonald, Asik Pradhan Gongaju, Mark Price, Yuyin Sun, Chintan Tank, Alan Walsh, Brian Wheeler, Feng Wu, Angela Zoss. Ponce School of Medicine: Richard J. Noel, Jr. (Ponce PI), Ricardo Espada Colon, Damaris Torres Cruz, Michael Vega Negrón. The Scripps Research Institute: Gerald Joyce (Scripps PI), Catherine Dunn, Brant Kelley, Paula King, Angela Murrell, Barbara Noble, Cary Thomas, Michaeleen Trimarchi. Washington University School of Medicine in St. Louis: Rakesh Nagarajan (WUSTL PI), Kristi L. Holmes, Caerie Houchins, George Joseph, Sunita B. Koul, Leslie D. McIntosh. Weill Cornell Medical College: Curtis Cole (Weill PI), Paul Albert, Victor Brodsky, Mark Bronnimann, Adam Cheriff, Oscar Cruz, Dan Dickinson, Richard Hu, Chris Huang, Itay Klaz, Kenneth Lee, Peter Michelini, Grace Migliorisi, John Ruffing, Jason Specland, Tru Tran, Vinay Varughese, Virgil Wong. This project is funded by the National Institutes of Health, U24 RR029822, "VIVO: Enabling National Networking of Scientists". VIVO Collaboration:
    • 3. Overview 1. What is VIVO? 2. Why the library? 3. User experience (UX) 4. Discussion/questons
    • 4. In September 2009, seven institutions received $12.2 million in funding from the National Center for Research Resources of the NIH to to enable National Networking with VIVO •Originally developed at Cornell University in 2004 to support Life Sciences •Reimplemented using RDF, OWL, Jena and SPARQL in 2007 •Now covers all faculty, researchers and disciplines at Cornell •Implemented at University of Florida in 2007 •Underlying system in use at Chinese Academy of Sciences and Australian Universities VIVO history… born in the library
    • 5. iClicker Question 1 Had you heard of VIVO before the conference? A. Yes B. No
    • 6. VIVO is: Populated with detailed profiles of faculty and researchers; displaying items such as publications, teaching, service, and professional affiliations. A powerful search functionality for locating people and information within or across institutions. An open-source semantic web application that enables the discovery of research and scholarship across disciplines in an institution.
    • 7. iClicker Question 2 How familiar are you with the Semantic Web? A. Very (part of my everyday work) B. Moderately (can explain it to others) C. Mildly (understand the concepts) D. Not at all (new to me)
    • 8. Semantic web: describes methods and technologies to allow machines to understand the meaning or "semantics” of information on the web. -- W3C director Sir Tim Berners-Lee Ontology: a formal representation of the knowledge by a set of concepts within a domain and the relationships between those concepts. -- Wikipedia
    • 9. VIVO’s semantic advantage Data modeled as bidirectional relationships
    • 10. VIVO users …and many more! Faculty/Scholar/Researcher/Scientist •Find collaborators •Track competitors •Keep abreast of new work •Rely on customizable profiles maintained via automatic updates Student •Locate mentors, advisors, or collaborators •Locate events, seminars, courses, programs, facilities •Showcase own research Administrator •Showcase college, program, departmental activities •Identify areas of institutional strength •Manage data in one place Donor/ Funding Agency •Discover current funded projects •Search for specialized expertise •Visualize research activity within an institution
    • 11. iClicker Question 3 Who are you? A. Faculty/researcher B. Librarian C. Vendor D. Other
    • 12. Faceted search, browse, and ontology hierarchy
    • 13. VIVO harvests much of its data programmatically from verified sources • Reduces the need for manual input of data • Provides an integrated and flexible source of publicly visible data at an institutional level Data, data, data Individuals may also edit and customize their profiles to suit their professional needs. External data sources Internal data sources
    • 14. http://gradeducation.lifesciences.cornell.edu/ Repurposing and re-using data
    • 15.  Stored in Resource Description Framework (RDF) triples  Uses the shared VIVO Core Ontology to describe people, organizations, activities, publications, events, interests, grants, and other relationships  Incorporates Friend-of-a-Friend (FOAF) and Bibliographic Ontology (BIBO)  Supports local ontology extensions for institution-specific needs Linked Data Subject Predicate (verb) Object Riha, Susan research area crop management Riha, Susan international geographic focus Brazil Riha, Susan submitter of impact statement Climate change and its impact on the distribution of invasive weeds Riha, Susan selected publication (authorship) Biomass, harvestable area, and forest structure estimated from commercial timber inventories and remotely sensed imagery in southern Amazonia
    • 16. Mike Conlon’s VIVO profile
    • 17. Mike Conlon’s VIVO profile as Linked Data
    • 18. Detailed relationships for a researcher Andrew McDonald author of has author research area research area for academic staff in academic staff Susan Riha Mining the record: Historical evidence for… author of has author teaches research area for research area headed by NYS WRI Earth and Atmospheric Sciences crop management CSS 4830 Cornell’s supercomputers crunch weather data to help farmers manage chemicals head of faculty appointment in faculty members taught by featured in features person
    • 19. Visualizing relationships
    • 20. Visuali- zation Ponce VIVO WashU VIVO Scripps VIVO UF VIVO IU VIVO WCMC VIVO Cornell VIVO RDF Triple Store RDF Triple Store Future VIVO Future VIVO Future VIVO Other RDF Other RDF Other RDF Prof. Assn. Triple Store Regional Triple Store Search Other RDF Search Linked Open Data NIH VIVO Network Exemplar
    • 21. iClicker Question 4 Which one of these features is most important for VIVO to be successful? A. Publications ingest B. Visualization of relationships C. Collaboration tools D. Search/browse the network
    • 22. Overview 1. What is VIVO? 2. Why the library? 3. User experience (UX) 4. Discussion/questions
    • 23. Why Libraries? • Are a trusted, neutral entity • Have a tradition of service and support • Strive to serve all missions of the institution • Are technology centers and have IT and data expertise • Have skills—information organization, instruction, usability, subject expertise • Have close relationships with their clients (buy in) • Understand user needs • Understand the importance of collaboration and know how to bring people together • Have knowledge of institution, research, education, clinical landscape Librarians: Libraries:
    • 24. Library staff as facilitators Oversight of initial content development • Oversee content, local ontology and interface refinement • Negotiate with campus data stewards for publicly visible data Support and training: local and national level • Use existing VIVO documentation, presentation/demo templates • Provide support, web site FAQs, etc. Communication/liaising • Engage with potential collaborators, participants • Usability: Feedback, new use cases from users to implementation team
    • 25. iClicker Question 5 How do you feel about the directions libraries and publishers are moving in? A. Excited by the new opportunities B. Scared my job is in jeopardy C. I don’t think it’s going to change that much D. Anything goes…..
    • 26. Overview 1. What is VIVO? 2. Why the library? 3. User experience (UX) 4. Discussion/questions
    • 27. Our Process
    • 28. Audience Analysis – Mental Model
    • 29. Contact User Scenarios Search Profiles Collaboration CV Reports Login Friends Events Funding Site management Ingest Linked data Visualize Publications
    • 30. Features based on users and scenarios
    • 31. User testing and Morae
    • 32. Earlier feedback with InfoMaki
    • 33. iClicker Question 6 - InfoMaki
    • 34. iClicker Question 7 - InfoMaki
    • 35. iClicker Question 8 - InfoMaki
    • 36. Overview 1. What is VIVO? 2. Why the library? 3. User experience (UX) 4. Discussion/questions
    • 37. 1. In our new state of information overload, how should librarians connect people with information? Is it the role of the librarian to connect people with people? 2. What ways are your libraries fostering collaboration? 3. In light of collaborative team science/research, how do you envision the role of the library changing within the university setting? Discussion/questions
    • 38. http://vivoweb.org http://sourceforge.org/projects/vivo THANK YOU! ejc12@cornell.edu