Research Data Management in Academic Libraries: Meeting the Challenge

Research Data
Management in
Academic Libraries
Meeting the Challenge
Spencer D. C. Keralis
Director for Digital Scholarship,
Research Associate Professor
@hauntologist | spencer.keralis@unt.edu
#TXLA13 | #DMLib
@

• What we talk about when we talk about Data
• The Problem of Data
• Research in Data Curation Education
• Research in Data Management Policy &
Practice
• Why Open Data?
• Why Libraries?

Research Data Management
• NIH Data Management Plan Mandate (2003)
– >$500K requires Data Sharing Plan
– Public Access Policy for publications (2008)
• NSF Data Management Plan Mandate (2010)
• CDC, DoE, DoD, EPA, NASA, NEH-ODH, NIST,
DoAg, DoEd all have DM Plan Requirements
• White House OSTP Memo, February 22, 2013
– digitally formatted scientific data resulting from
unclassified research supported wholly or in part by
Federal funding should be stored and publicly
accessible to search, retrieve, and analyze.

everything
Data is:
necessary for reproducible science.
Woods Hole Oceanographic Institute

DCC Data Life Cycle Model
http://www.dcc.ac.uk/resources/curation-lifecycle-model

http://epicgraphic.com/data-cake/

Technology/InfrastructurePlan
Prepare
Preserve
Publish

Scholarly Communications
• Project to Publication vector well known in
Libraries – Open Access Repositories, SC
Librarians, IP, Citations, etc.
• What about the data?
• Competing interests: Must ensure
IP, citation, access, embargoes, human
subjects privacy, etc. etc.
• Who pays?

The Problem of Data
• U.S. LIS & iSchools
curricula woefully
inadequate for training
data professionals.
• Lowest-ranking members
of research teams
responsible for data
curation, without training
or material support.
http://www.clir.org/pubs/reports/pub154

Few researchers are aware of the
data services that the library might
be able to provide and seem to
regard the library as a dispensary of
goods (e.g., books, articles) rather
than a locus for real-time
research/professional support.
Jahnke, Lori, and Andrew Asher. 2012. The Problem of Data: Data
Management and Curation Practices Among University Researchers. The
Problem of Data, pp. 3–31. Washington, DC: Council on Library and
Information Resources.

Less than 8% of the [LIS] courses
qualified as data centric. Based on
course codes assigned by the
schools, these courses tended to be
new, and some did not yet appear
in course catalogs [,] being added
by institutions during the
verification process. Data centric
courses were rarely required for LIS
degrees, certificates, or other
credentials.
Virgil E. Jr., Elin J. Bammerlin, and Carole L. Palmer. 2012. Education for Data
Professionals: A Study of Current Courses and Programs. Proceedings of the
2012 iConference, 527–529. New York: Association for Computing Machinery.

Given the improbability that
students will encounter a data-
centric course in their line of study,
students must be committed to
constructing a data-intensive
education for themselves in order
to come out of most existing U.S.
LIS programs with the skills and
knowledge necessary to support
the needs of data-intensive
research.
Spencer D. C. Keralis, 2012 Data Curation Education: A Snapshot The
Problem of Data, pp. 32–36. Washington, DC: Council on Library and
Information Resources.

How can LIS education be changed and enhanced
to result in well-prepared information professionals,
scientists, and scholars
that can take on the challenges and problems of
digital curation, data management, and digital
preservation,
incorporating extensive training and practical
experience
in the context of contemporary distributed learning
and web-based courses?
http://icamp.unt.edu/

The DataRes Project, funded by a Laura Bush 21st
Century Librarians grant from the IMLS, investigates
how the library and information science (LIS) profession
can best respond to emerging needs of research data
management in universities.
DataRes is a collaboration between the University of
North Texas Libraries, the UNT College of Information,
and the Council on Library and Information Resources.

Project Aims
Governmental funding agency requirement
NSF
NEH
NIH
IMLS
Goals:
• Research consistent policies or programmatic
implementation from research institutions
• Emerging patterns in data management (DM)
policies
• Research libraries and LIS responses
• Curriculum and training development
• Expectations of major stakeholders in the research cycle

Digging Deeper:
Text Analysis of Agency Guidance

Preliminary Findings:
Institutional Policy Scan

Text Analysis:
Institutional Policy Scan
38 institutional policies
Example language:
“The University recognizes the importance of data
sharing in the advancement of knowledge and
education.”
(University of New Hampshire “UNH.VII.C.9”)
An index of known policies, with links to the project data set will be available in
February 2013 at http://datamanagement.unt.edu/policies

Survey Findings
Individual
Departments
8%
Library
48%
Office of
Research
24%
LIS School
3%
IT Department
17%
Where does your institution offer Data Management Plan
Support?

University Interventions
• University of Minnesota – Workshops & CE
Credit
• UIUC – Liaison Librarians
• Purdue & SDSU – Infrastructure &
Supercomputing
• California Digital Library – Repository and
DMPTool

Secondary Survey
• Intended participants: VPs of
Research, Deans, High-level Administrators
– We feel we got a very clear picture from the
librarian perspective with the initial survey
– Questions were raised through the course of our
survey analysis and research that we feel only
institutional administrators will be able to answer.

Key Takeaways
• Institution-level policies are last response to
occur, if at all.
• Research Data Management is not a single
department issue, nor is it the purview of a single
discipline.
• Collaboration, domain knowledge, and
infrastructure are all key to the success of any DM
response.
• Prescriptive guidance from agencies will be
necessary to encourage disciplines to take DM
Plan requirements seriously in evaluating funding
applications.

Aaron Swarz
1986-2013
#pdftribute

The Denton Declaration
May 22, 2012 at the University of North Texas
• Open access to research data is critical for advancing
science, scholarship, and society.
• Research data, when repurposed, has an accretive value.
• Publicly funded research should be publicly available for
public good.
• Transparency in research is essential to sustain the public
trust.
• The validation of research data by the peer community is
an essential function of the responsible conduct of
research.
• Managing research data is the responsibility of a broad
community of stakeholders including
researchers, funders, institutions, libraries, archivists, and
the public.

http://openaccess.unt.edu/denton_declaration

Library + Data = __________
The domain of Information Sciences:
• Metadata
• Controlled Vocabularies
• Long-term preservation
• Infrastructure
• Discoverability
• Accessibility
• Reuse
• Sustainability
• Centrality/Neutrality

Scholarly Communications
• Open Access Repositories include Data associated
with Publications
• SC Librarians trained in Data IP
• Develop protocols for Data
Publication, Citations, etc.
• Develop models for sustainable support of Data
Publication and long term preservation and
access
• Buy in from OR, indirect costs
• Invest in infrastructure

The Fun Stuff
• Data Visualization
• GIS
• Apps
• STEAM in STEM
• New Media Art
• Games
Joy Division, Unknown Pleasures (1979)
Graphic designer Peter Saville used signal data
from a pulsar for this iconic image.

LIS will need to develop stronger
partnerships with domain
researchers, informaticists, and
other stakeholders in the research
enterprise, to succeed at making
research data an integral and
enduring part of the information
assets retained for science and
scholarship over the long term.
Weber, Nicholas, Tiffany Chao, Carole L. Palmer, and Virgil E. Varvel Jr. 2011. Report
on the Data Curation Research Summit. Paper presented during the 6th
International Digital Curation Conference, December 6, 2010, Chicago.
Champaign, IL: Center for Informatics Research in Science & Scholarship, University
of Illinois

Keynote:
Kathleen Fitzpatrick
Director of Scholarly
Communication, Modern
Language Association
Author of Planned Obsolescence:
Publishing, Technology, and the
Future of the Academy (2011)
May 30th & 31st 2013
DallAs, Texas
Futures of
Academic
Publishing

http://www.library.unt.edu/datamanagement
http://disco.unt.edu
@UNTDiSCo
@OASymposium
@DataRes

Research Data Management in Academic Libraries: Meeting the Challenge

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