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).
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.
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.
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
Faceted search, simple and flexible, based on ontology hierarchy.
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
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
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.
1. Presented by:
Ellen J. Cramer Ph.D.
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".
3. In September 2009, seven
$12.2 million in funding
from the National Center
for Research Resources of
the NIH to to enable
•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
4. 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.
5. Who uses VIVO?
…and many more!
•Keep abreast of new work
•Rely on customizable profiles maintained
via automatic updates
•Locate mentors, advisors, or
•Locate events, seminars, courses,
•Showcase own research
•Showcase college, program,
•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
6. VIVO’s semantic advantage
Data modeled as bidirectional relationships
7. Faceted search, browse, and ontology hierarchy
8. 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,
• 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
9. 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
• Provide support, web site FAQs, etc.
• Engage with potential collaborators, participants
• Usability: Feedback, new use cases from users to
10. 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.
Repurposing and re-using data
12. 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
Supports local ontology extensions for institution-specific
Data in VIVO: Semantic Web standards
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
13. Mike Conlon’s VIVO profile
14. Mike Conlon’s VIVO profile as Linked Data
15. Detailed relationships for a researcher
research area for
Mining the record: Historical evidence for…
teaches research area for
Earth and Atmospheric
Cornell’s supercomputers crunch weather data to help farmers manage chemicals
faculty appointment in
16. Visualizing relationships
Linked Open Data