This presentation was provided by Jan Fransen of the University of Minnesota - Twin Cities during the NISO virtual conference, Research Information Systems: The Connections Enabling Collaboration, held on August 16, 2017.
Fransen From Researcher Profiling to System of Record
1. From Researcher Profiling to
System of Record
Jan Fransen
Service Lead for Discovery and
Research Information Management Systems
University of Minnesota Libraries
NISO Virtual Conference: August 16, 2017
https://experts.umn.edu/en/persons/jan-fransen
3. Biological Sciences
Continuing Education
Dentistry
Design
Education and Human
Development
Extension
Food, Agricultural and Natural
Resource Sciences
Graduate
Law
Liberal Arts
Management
Medicine
Nursing
Pharmacy
Public Affairs
Public Health
Science and
Engineering
Veterinary Medicine
UMTC Colleges
4. • http://experts.umn.edu
• Based on Elsevier Pure (since 2015)
• Originally Elsevier SciVal Experts (2012-15)
• Covers University of Minnesota-Twin Cities
• Faculty
• Researchers (including post doc)
• Staff members who are likely to publish research (like librarians)
7. Is Experts@Minnesota helping people
find each other?
• Maybe…
• We don’t have a good way to determine
whether new collaborations formed BECAUSE
of Experts@Minnesota
• (But we hope so)
8. What DO we know?
• We’ve collected bibliographic information on
almost 230,000 research outputs for 6770
researchers (current and former)
9. What DO we know?
• We’ve collected bibliographic information on
almost 230,000 research outputs for 6770
researchers (current and former)
• UMTC has never had such a rich set of
bibliographic data about its research before
14. Psychology Computer Science Statistics Computer Science Otolaryngology-
Head & Neck Surgery
Researcher-Centric:
One copy of the citation on each person’s CV and each person’s online profile(s)
15. Researcher-Centric Challenges
• Easy to answer
– How many publications did Helwig have?
• Harder to answer
– How many publications did Computer Science
have?
– How many publications did the University have?
– With what other departments did CS collaborate?
– What research has relied on data collected at the
Driven to Discover tent?
16. Research Information-Centric:
One copy of record -> Many reuse possibilities
Title AuthorAuthorAuthorAuthorAuthor
AuthorAuthorAuthorAuthorAffiliations
Journal
Volume
Issue
etc.
17.
18.
19. Making the Data Available
• Image from http://www.aunalytics.com/why-data-warehouse/
20.
21. Wierschem, D., McMillen, J., & McBroom, R. (2003). What
Academia Can Gain from Building a Data Warehouse. Educause
Quarterly, 26(1), 41-46.
22. HR Tables
(source is PeopleSoft)
Financials
Tables
(source is PeopleSoft)
DW-Experts
Tables
(source is PeopleSoft +
Experts Logic + Pure API)
Pure
(source is Experts Tables + user entry + Profile
Refinement Service)
DW-Experts
Logic
Goal: Minimize manual entry
Pure Import process
Pure API to import
research outputs and
user-entered information
to Experts tables
“Experts Data
Warehouse”
23. Timeline
Phase 1: Oracle
Database built and
maintained by
University Libraries
Phase 2:
Documentation and
training for
interested
consumers
Phase 3: Integration
with Office of
Information
Technology next-
generation data
warehouse
24. Near-Term Consumers
• Faculty Activity Reporting systems (Promotion
and Tenure)
• Academic Program Reviews
• UMN Websites
– Link to person’s or organization’s profile
– List of recent publications for individual,
department, college, research center