This document provides an overview of data management plans (DMPs), including their purpose, origins, requirements by major funders, and benefits. It discusses key components of DMPs such as the data types and standards, access and sharing policies, and long-term preservation. The document also examines researchers' attitudes toward DMPs and data sharing, which can include fears about misuse or losing competitive advantage. Finally, it poses questions about developing research data management services at Villanova University through collaboration between libraries, support services, and researchers.

1. Data Management Plans
Services Needed?

2. What is a DMP?
A data management plan is a formal
document describing how a researcher
intends to handle data throughout the
lifecycle of a particular project.

3. Where does DMP fit into the Data Lifecycle?
Source: http://www.data-archive.ac.uk/create-manage/life-cycle

4. Where Did DMP’s Come From?
Source: Moses Receives the Tablets of the Law, Marc Chagall,1960-66

5. Funding Providers in the US
• National Institute of Health (2003)
• National Science Foundation (2011)
• National Oceanic & Atmospheric Administration
(2011)
• National Endowment for the Humanities (2013)
• Institute of Education Sciences (2012)
• Federal Agencies >$100M in R&D (2013)
• Wellcome Trust in the UK…
• US private funders to follow?

6. Why are DMP’s Needed?
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Ensure integrity
Accelerate scientific advances
Government accountability
Economic development
Replicate results

7. Context

8. Researcher attitudes toward data management &
plans
“Data sharing is a bit like going to
the dentist. We can all agree that
it is a good thing to do and
intrinsic to good scientific practice.
In reality, however, researchers
tend to view data sharing with a
mix of fear, contempt, and dread.”
LeClere, F. (2010, Aug. 3). Too many
researchers are reluctant to share their data.
Chronicle of Higher Education. Retrieved from
http://chronicle.com/article/Too-ManyResearchers-Are/123749/
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Fear of data misuse
Competitive advantage loss
Lack of time, too much work
No place to put the data
Contribution to Open Access
Facilitate knowledge creation
via mashups, diversity of
analysis
• Enhance research profile &
prominence

9. DMP Features (NSF)
• 2 page addendum to application
• Sections in NSF Grant Application
– Data types & size generated
• What & How generated
– Data & Metadata
• File formats, file naming, data about data or metadata
– Access/sharing & Privacy/security
• Who’s responsible, how stored, where stored, backups, constraints on
sharing, duration available
– Reuse/Redistribution
• Potential audience, licensing restrictions
– Archiving/Preservation
• Where kept and how long, resources needed, policies &
procedures

10. Institutional Support: Links
Source: http://library.villanova.edu/research/topic-guides/research-data/

11. Institutional Support: Tools
Source: https://dmp.cdlib.org/my_plans
Source: http://n2t.net/ezid

12. Institutional Support: Consulting
Source: https://confluence.cornell.edu/display/rdmsgweb/Home
Source: http://www.lib.purdue.edu/research

13. Institutional Support: Training
Source: http://datalib.edina.ac.uk/mantra/
Source: https://www.lib.umn.edu/datamanagement/workshops/dataplan

14. Institutional Support: Repositories & Archives
Source: http://dspace.mit.edu/
Source: http://researchdata.wisc.edu/manage-your-data/data-backup-andintegrity/

15. Research Data at Villanova
• What will research data management services look like
at Villanova?
• Who are the key stakeholders at Villanova and who can
best champion the effort?
• How shall University leadership, support services and
researchers come together to plan and implement
services?

16. Additional Resources
Jones, S. Pryor, G. & Whyte, A. (2013). How to develop research data
management services: A guide for HEIs’ Retrieved from
http://www.dcc.ac.uk/resources/how-guides/how-develop-rdm-services
Pryor, G. (Ed.) (2012). Managing research Data. London: Facet Publishing.
Steinhart, G. Chen, E. Arguillas, F. Dietrich, D. & Kramer, S. (2012). Prepared
to plan? A snapshot of researcher readiness to address data management
planning requirement. Journal of eScience Librarianship 1(2) 63-78.
Scaramozzino, J.M., Ramirez, M.L. & McGaughey, K.J. (2012). A study of
faculty data curation behaviors and attitudes at a teaching-centered university.
College & Research Libraries 73 (7) 349-365.