2. Bruce Herbert, Texas A&M
Laurel Haak, ORCID
Andrea Michalek, Plum Analytics
This panel will explore how Texas A&M, selected and implemented a
technology stack and is using it to achieve their strategic plan, “Vision
2020: Creating a Culture of Excellence.” Their stack includes VIVO,
ORCID, Vireo & DSpace repositories, and PlumX.
The panel will discuss the components and the interactions between
them.
Hosted by: Plum Analytics
Presenters and Panel
2
3. A Brief History:
Initial Implementationq
•Currently, we are on our second ramp up of a
VIVO installation.
•We were introduced to VIVO a few years ago and
immediately saw the potential for its use.
• So like anyone with a new toy. We started
digging up any dataset we could find and load
them into VIVO.
VIVO Implementation at Texas
A&M
4. Original VIVO project
focused on representing
biomedical research
VIVO at TAMU has more
complex use cases.
Sociotechnical systems are understood and improved if both ‘social’
and ‘technical’ aspects are brought together and treated as
interdependent parts of a complex system
http://lubswww.leeds.ac.uk/stc/what-we-do/stc-logo/ 4
VIVO as a Sociotechnical
System
6. Faculty Reputation
Discovery of expertise when
building collaborative teams
Organizational practices for
faculty, departments and
colleges
VPR and TEES Proposal
development
Research funding compliance
Informing Society
TAMU Use Cases
7. HR: people and their positions
Symplectic Elements Harvester: Faculty Publications
Registrar: courses
Faculty reporting: awards, professional service,
education, research areas, research blurb
Institutional Repository: ETDs, publications, grey
literature
Events calendar
MARCOMM: internal and external news
Extension: outreach, technology transfer
Research administration: grants & contracts 7
TAMU Data Sources
8. Representing faculty reputations
Dirty data
Lack of common definitions of organizational
structure or who’s “faculty”
Data ownership and use by Colleges
Many dimensions of privacy beyond simple “opt-in
vs. opt-out”
Short-term “go it alone” vs. common good
Institutional risk
8
Policy Issues
9. TAMU Researcher Profile Information Ecosystem
TAMU Data
Profile Editor
Faculty Data
SQL
Database
Harvest
Reports
Manual
Input
Curator
QC
Harvest
Crosswalk
Harvest
Widgets
HarvestWidgets
10. Scholarly Impact Metrics
Faculty
Profiles in
PlumX
Identity
Control
Evaluations
Strategic
Decision Making
Alternative metrics critical for many different types of scholarly work
23. 23
ORCID’s vision is a world where
all who participate in research, scholarship, and
innovation are uniquely identified
and connected to their contributions and
affiliations across time, disciplines, and borders.
ORCID
24. 24
ORCID provides PIDs
Persistent digital identifiers to distinguish
researchers from each other
Member-built integrations that connect
researchers and their activities/affiliations
A hub for synchronizing machine-readable
connections between identifiers for people,
organizations, and research activities
✔ Plumbing for research information
✔ Tools to build trust in digital information
25. 25
Organizations are
using ORCID APIs to
authenticate,
collect, display, and
connect persistent
identifiers for
people, places, and
things in research
workflows
Enabling assertions
28. Manage data at its appropriate source with
appropriate privacy
HR, grants management, registrar, graduate school, colleges
and schools, research centers, extension
Department/agency/division/geographic location/research
unit
Consciously derive public data for exchange
Engage stakeholders and build relationships
Recruit power users for training and local knowledge
Data that are visible get corrected!
Data Stewardship
28
30. Faculty want control of
their narrative
An integrated VIVO
system supports the
complex variety of
narratives at TAMU.
http://www.aaup.org/reports-and-
publications/academe
(Re)Claiming Faculty Narratives
30
Multiple sources
Systems of record
Faculty activity reporting
External sources (e.g., Scopus, PubMed, NIH RePORTER)
Single sign-on for self-editing or by proxy
The text in blue represents complexity in implementing VIVO because of the heterogeneity across TAMU.
Faculty reputations has two levels of complexity – there are differences across the disciplines and by the way faculty contribute to TAMU – not all faculty are scholars.
College want to use data on faculty work that has integrated measures of scholarly impact.
Value Proposition
Disambiguation
Discoverability
Business Practices
Value Proposition
Disambiguation
Discoverability
Business Practices