Presentation given at NISO Virtual Conference.
"Research Information Systems: The Connections Enabling Collaboration".
https://www.niso.org/events/2017/08/research-information-systems-connections-enabling-collaboration
VIVO: A Community-driven Research Information Management System: Challenges and Opportunities
1. VIVO: A Community-driven
Research Information
Management System.
Challenges and Opportunities
8/16/2017
Muhammad Javed, Ph.D.
Ontology Engineer/Tech. Lead (Scholars@Cornell)
Cornell University Library
mj495@cornell.edu | @mjaved495
3. Cornell University
What is VIVO?
• A web resource for single point of access for information on
scholarly activity at Cornell. [Jon Corson-Rikert et. al. (Sep. 2007)]
• A semantic web-based researcher and research discovery tool.
[Duraspace & VIVO Sponsor Webinar (2012)]
• An open source tool for describing and linking researchers and
research. [Dean B. Krafft and Jon Corson-Rikert (2012)]
• VIVO creates a connected, integrated record of the scholarly
work of your institution, ready for reporting, visualization, and
analysis. [VIVO: website (2017)]
4. Cornell University
What is VIVO?
• A web resource for single point of access for information on
scholarly activity at Cornell. [Jon Corson-Rikert et. al. (Sep. 2007)]
• A semantic web-based researcher and research discovery tool.
[Duraspace & VIVO Sponsor Webinar (2012)]
• An open source tool for describing and linking researchers and
research. [Dean B. Krafft and Jon Corson-Rikert (2012)]
• VIVO creates a connected, integrated record of the scholarly
work of your institution, ready for reporting, visualization, and
analysis. [VIVO: website (2017)]
6. Cornell University
VIVO – A semantic web-based tool
“VIVO-ISF” Ontology as Model
- Written in OWL
- Can express
Disjointness & Unions
Domains/Ranges
Transitiveness.
Inverse Prop.
..and more
https://www.w3.org/OWL/
https://wiki.duraspace.org/display/VIVODOC19x/Ontology+Reference
10. Cornell University
Researcher profile systems:
Community of Scholars
Google Scholar
LinkedIn
SciENcv
VIVO
Subject author identifier system:
Subject repository: arXiv
Research & collaboration hub: nanoHUB
Reference management:
Online encyclopedia: Wikipedia
Credits: OCLC - https://www.slideshare.net/oclcr/registering-researchers-in-authority-files/5
That is how world look at VIVO ?
12. Cornell University
FPS vs. RIMS
Examples FPS
(acceptable?)
RIMS
(acceptable?)
1. “Selected” Publication List OK No. Requires as
complete as possible.
2. “Selected” Award and Honors OK No. Requires as
complete as possible.
3. Research Interest Statements (“Text”) OK Not useful, unless
topics are inferred.
4. “Different texts” representing the same entity OK No. Cannot analyze
the data.
5. Citation data details (e.g. journal, page nos., list
of co-authors)
Not required Required
15. Cornell University
• Though VIVO is based on a model that allows
inference, the model in under-utilized.
• Built-in inference engine with limited functionalities.
VIVO-ISF Ontology: An under-utilized model
16. Cornell University
• We have built Institutional
Knowledge Graphs (IKGs)
at national / international
institutions, using the
same data model.
Cross-Institutional Search & Discovery
Cornell
Texas A&M
Duke Brown
UF
…
Institutional Knowledge Graphs
17. Cornell University
• How do we create now
linkages between these
IKGs for national /
international networking
and discovery.
Cornell
Texas A&M
Duke Brown
UF
…
Cross-Institutional Search & Discovery
19. Cornell University
• How does a person
use long lists views
that are available in
out of the box VIVO?
Representation
20. Cornell University
• Out of the box,
– Limited analysis & visualizations.
– Data can only be downloaded/shared in RDF format.
• RDF to JSON transformation ?
– Limited data reuse: Cannot push data to other sites.
• An API ?
VIVO: Under-developed for reporting and analysis
21. Cornell University
• Manual curation
• Using upstream sources (web of science, scopus, pubmed, crossref etc.)
• Data updates
Data quality is still an issue!
25. Cornell University
1. Scholars pages are non-editable.
2. Date quality is a high priority.
3. No manual assertions. Infer knowledge graphs from the given
research data.
4. Use D3 visualizations to present aggregate views.
5. Visualizations: another way to navigate through the linked data.
Some important notes
34. Cornell University
VIVO HAS THE POTENTIAL TO BE A
GREAT RESEARCH INFORMATION
MANAGEMENT SYSTEM
VIVO – A Research Information System?
Data
Modeling
Data
Recording
Data
Analysis
35. Cornell University
• VIVO: A Semantic Approach to Scholarly Networking and Discovery
http://www.morganclaypool.com/doi/pdf/10.2200/S00428ED1V01Y201207WBE002
• Research Information Management Systems – A new service category ?
– Loran Dempsey (Vice-President and Chief Strategist - OCLC)
http://orweblog.oclc.org/research-information-management-systems-a-new-service-category/
• Scholars@Cornell: Visualizing the Scholarship Data
https://figshare.com/articles/Scholars_Cornell_Visualizing_the_Scholarship_Data/5303620
Some other useful links
36. Cornell University
Muhammad Javed, Ph.D.
Ontology Engineer/Tech. Lead (Scholars@Cornell)
Cornell University Library
mj495@cornell.edu | @mjaved495