As stewards of the scholarly record, Cornell University Library is developing a data and visualization service known as Scholars@Cornell with the goal of improving the visibility of Cornell research and enabling discovery of explicit and latent patterns of scholarly collaboration. We provide aggregate views of data where dynamic visualizations become the entry points into a rich graph of knowledge that can be explored interactively to answer questions such as: Who are the experts in what areas? Which departments collaborate with each other? What are patterns of interdisciplinary research? And more. Key components of the system are Symplectic Elements to provide automated citation feeds from external sources such as Web of Science, the Scholars "Feed Machine" that performs automated data curation tasks, and the VIVO semantic linked data store. The new "VIZ-VIVO" component bridges the chasm between the back-end of semantically rich data with a front-end user experience that takes advantage of new developments in the world of dynamic web visualizations. We will demonstrate a set of D3 visualizations that leverage relationships between people (e.g., faculty), their affiliations (e.g., academic departments), and published research outputs (e.g., journal articles by subject area). We will discuss our results with two of the initial pilot partners at Cornell University, the School of Engineering and the Johnson School of Management.

1. “VIZ”ualizing the Scholarly Record
Sandy Payette and Muhammad Javed
Cornell University Library
Presented at CNI Fall Meeting 2016

2. Graphs for knowledge
•What are hot research areas?
•What are the pa.erns of collabora3on?
•Who are expert faculty in what areas?
•Who co-authors in which areas?
Visualiza5ons
• Navigate the scholarly record
• Dynamic interac3ve views
Data
•People, publica3ons, organiza3ons
•VIVO ontology as data model
•Exposed as linked open data

3. The Expanding Landscape of
Research Information Management
Pure

4. Many systems have a piece of the action
• VIVO
• Symplectic Elements
• Pure
• ResearchGate
• Academia.edu
• Many More…

5. Profile
proliferation
• VIVO profiles
• ORCID records - “profiles?”
• PURE profiles (Elsevier)
• Scopus author profiles (Elsevier)
• Mendeley profiles (Elsevier)
• Symplectic Elements profiles
• OpenScholar faculty websites
• SciENcv (NCBI/NIH)
• ResearchGate
• Academia.edu.

6. How to make sense of this?
• The messiness of emerging knowledge infrastructure
• Private institutional vs. public perspective
• Proprietary vs. open data
• Commercial vs. open source vs. hybrid technology
• Isolated systems vs. interconnected networks

7. HR Feed
Machine
pub data
people data
External Data Sources Internal Data Sources
grants data
data/viz mediator
External Data Sources
Web and Linked Open Data
Scholars Positioning in Ecosystem

8. How we motivate our work
• The messiness of emerging knowledge infrastructure
• Private institutional vs. public perspective
• Proprietary vs. open data
• Commercial vs. open source vs. hybrid technology
• Isolated systems vs. interconnected networks

9. Backend
Inference
Graph
Links to external
knowledge
Authority Records
Extendable/Reusable Model OpenAccess to Data
Frontend
Semantic Data-driven Viz.
User-friendly
Navigate
through
LD
Fresh look & feel
ListView 2 VizView
Data Download

10. ….Domain Experts in any field
Journal Articles
Conference Paper
Book Chapters
Book
Patent
News letter
Video
Performance
Presentation
Essay
ReviewTranslation
Report
Play
Script

11. Scholars@Cornell
Highlights from Demo
VIZ-VIVO
Uberization
✴ semantic graph meets dynamic web
✴ turning data into a knowledge
✴ best of the best citation data

12. The article is published in
Personality and Social
PsychologyBulletin.
Chen, Y-R (Cornell) co-authored
an article with Blader, S.L. and
Shirako A. (New York).
https://www.linkedin.com/pulse/visual-analytics-uncovering-why-your-data-bartosz-mozyrko
Citation data
Zoomable Collaboration
Wheel
Global Impact
Past Future
Ethics
VIZ-VIVO Proposition
Fingerprints of a Faculty

13. Uberization Channel
of Citation Entries
(VIVO) Harvester
API
Citation Entry
Articles
Bin
Journals
Bin
Curation Bins
Ranked List of
Citation Data Sources
Uber Record
Data Validation
API
Linked Open Data
Clean and Complete Data
Inconsistent/Incomplete Data

14. Pilot Phase - Key Questions
• Library nudge a university-wide bottom-up coordinated process?
• Cornell highly decentralized in research info mgmt
• Role of library? Role of academic units?
• No central mandate or common RIM system
• Data Quality
• Automated curation - How much can we do?
• Human curation - how much? who?
• Many user stories - sweet spot for Scholars@Cornell?
• Deans, department chairs, university administration
• University communications and outreach
• Faculty and researchers
• Prospective students and faculty
• Ongoing investment to sustain?

15. QUESTIONS ?
Sandy Payette, Jon Corson-Rikert
Muhammad Javed, Tim Worrall, Jim Blake, Joseph McEnerney
Jill Wilson, Mary Beth Martini-Lyons, Kathy Chiang
George Kozak, Holly Mistlebauer, Jason Kovari, Adam Smith
http://about.scholars.cornell.edu
http://demo.scholars.cornell.edu/scholars/
username: scholars
password: libvivo1
Learn more….