Presented at Research Output & Impact – New Tools and Concepts: (ROI-AV - A DEFF sponsored project, Denmark)

1. VIVO for visualization and analysis
Muhammad Javed
Ontology Engineer and Project Tech. Lead (Scholars@Cornell)
Cornell University Library
mj495@cornell.edu
September 14, 2017

2. The Expanding Landscape of
Research Information Management

3. Where VIVO came from

4. 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)]
http://vivoweb.org/

5. VIVO – Creates an Institutional Knowledge Graph

6. “VIVO-ISF” Ontology as Model
- Written in OWL
- Can express
Disjointness & Unions
Domains/Ranges
Transitiveness.
Inverse Prop.
..and more
VIVO – A semantic web-based tool

7. VIVO – Create records of scholarly works

8. Metrics in VIVO
Citation Count
Altmetrics

9. Metrics in VIVO
Citation Count
Altmetrics
PlumX metrics

10. VIVO – Creates profile pages

11. Temporal Graph
Co-investigators
Co-authors
Capability Map
VIVO – Analysis and Visualizations
Out of the box

12. @Cornell

13. Data
Size/Type Quality
Update
- Publication data > 60K
- Grants data > 2K
- People > 3.5K
- Clean
- Complete
- Things vs Strings
- Batch
- Daily
- Real time
- Stream
VIVO Data: The Value Proposition
Analysis
- What questions we can answer?

14. • What are the hot research areas?
• Who is collabora0ng with Whom ?
Internal/Global
• Top Journals where faculty publish?
• in last one year
• in last five years
• for College of Engineering
• overall
We believed that,
we can extract implicit knowledge graphs from the given clean data!
• What are research outputs of an organiza0on?
(faculty repor0ng)
• Who are the domain experts in what area?
• What the top funding agencies for a College?
• Are they missing some?
• Who Co-authored, how oJen?

15. FRESH START
VIVO Framework
Feed Machine
&
Symplectic Elements
Data Distribution API
User Interface
Scholars@Cornell
Visualizations
data generation

16. Data to Knowledge Germination
Global Collaboration (GC) Map Person-2-Subject Area Network MapKeyword Cloud CoAuthorship Wheels
Fingerprints/Domain expertise
of a Faculty
CrossUnit/InterDept
CoAuthorships b/w Faculty
Global
Collaborations
Research Interests
of a Faculty
Article Journal
Keywords
Abstract/
Subject Area
Classification
Author
Affiliation
Position
Organization
MeSH

17. DEMO

18. SCHOLARS@CORNELL

19. SCHOLARS@CORNELL

20. SCHOLARS@CORNELL

21. SCHOLARS@CORNELL

22. Near Future Plans
• Current focus was on Journal Article category. Next step
is to analyze and model other types of publications.
• Data Modeling between a published article and the
Working paper/Preprint.
• Viz. Data Download (in .svg, .json etc.).
• Embedding Visualizations in different academic unit web
pages.
• Exploring more Data -> Knowledge Case Scenarios..

23. More aggregate views

24. &
@ScholarsCornell