Data Management Policy


From a funding perspective, a data management policy is a directive providing language that encourages or requires researchers to provide a data management plan in order to fulfill institutional, grant or other types of funding expectations. The National Science Foundation is one example of an institute that has a data management policy in place requiring researchers to submit a data management plan as a stipulation to receive funding.

From an institutional viewpoint, academic institutions such as the University of Edinburgh have also instituted a data management policy that includes specific requirements as they pertain to research data. Data management policies are implemented in order to ensure that research data remains available and reusable over time. Currently there is no standard framework for implementing institutional data management policies, as these policies are applied to the specific needs of an institution rather than to a general audience overall. Programs such as JISC (formerly Joint Information Systems Committee) and the Digital Curation Centre have taken strides to assist institutions develop a data policy framework to address these challenges.

Implementing a data sharing or management policy may require a number of steps, depending on the scope of the policy being implemented. The institution issuing the policy is responsible for putting in place the systems and procedures necessary for ensuring compliance to that policy from a member of the institution. To better explain the concept of implementing this type of policy, it is useful to provide a case study from the University of Edinburgh in Scotland. The process of implementing a data management policy involved the following activities:

  • First creating an implementation committee that included members from across the Information Services at the University. This committee was charged with delivering services to meet policy objectives and to report to the academic Steering Group whose goal it was to ensure that the services proposed would be relevant and applicable.
  • The subsequent component of the policy implementation focused on providing tailored data management planning for Principal Investigators (PIs) submitting research proposals and evaluating the Data Management Planning Online Tool for specific uses at Edinburgh.
  • The third component involved creating an active data infrastructure for facilities to store data from current research activities at the University. This infrastructure includes providing researchers with access to the data storage and helpful tools to assist in working with their data.
  • The fourth component focused on the concept of Data Stewardship, which can be described as providing the tools and services needed to aid in the description, deposit and ongoing management of completed research data.
  • Data management support is the fifth component and it is designed to provide consultation programs and support services to researchers throughout their research process.
  • The final component of implementing a policy that focuses on data sharing and data management is to create awareness within the institution. This task involves reaching out to all communities within the University who are working with data to ensure that they are aware of the requirements placed upon them as well as the host of services they can use such as the data management support and data infrastructure.

Further Resources

Bohémier KA, Atwood T, Kuehn A, & Qin J. (2011). A content analysis of institutional data policies(link is external). Proceedings of the 11th annual international ACM/IEEE joint conference on Digital libraries. New York, New York, USA. p. 409–10.

Briney K, Goben A, & Zilinski L. (2015). (link is external)Do You Have an Institutional Data Policy? A Review of the Current Landscape of Library Data Services and Institutional Data Policies(link is external). Journal of Librarianship and Scholarly Communication, 3(2), eP1232.

Creamer A. (2013). A seat at the table: Involving the library in the planning of institutional research data management policies and responsibilities – A conversation with the iridium project team at Newcastle University (UK). From EScience portal for New England Librarians.

Dallmeier-Tiessen S, Guercio M, Helin H, Herterich P, Kaur K, Lavasa A, … Salmivalli R. (2014). Exemplar Good Governance Structures and Data Policies(link is external). Dorset, UK.

Dietrich D, Adamus T, Miner A, Steinhart G. (2012). De-Mystifying the Data Management Requirements of Research Funders(link is external). Issues in Science and Technology Librarianship, 70.

Erway R. (2013). Starting the Conversation : University-wide Research Data Management Policy(link is external). Dublin, OH: OCLC Research.

Ganley E. (2014). PLOS(link is external) Data Policy: Catalyst for a Better Research Process(link is external). College & Research Libraries News, 75(6), 305–308.

Goben A, Salo D. (2013). Federal Research Data Requirements Set to Change(link is external). College & Research Libraries News, 74(8), 421–425.  

Hey A, Tansley S, & Tolle K, editors. (2009). The fourth paradigm: data-intensive scientific discovery(link is external). Redmond, WA: Microsoft Research.

Mannheimer AY, Greenberg J, Feinstein E, & Scherle R. (2014). A Balancing Act: The Ideal and the Realistic in Developing Dryad’s Preservation Policy(link is external). First Monday, 19(8).

Pink C. (2013). Meeting the Data Management Compliance Challenge: Funder Expectations and Institutional Reality(link is external). International Journal of Digital Curation, 8(2), 157–171.

Rice R., Ekmekcioglu Ç, Haywood J, Jones S, Lewis S, Macdonald S, & Weir T. (2013). Implementing the Research Data Management Policy: University of Edinburgh Roadmap(link is external). International Journal of Digital Curation, 8(2), 194–204.

SPARC. (2013). Implementing an Open Data Policy: A Primer for Research Funders(link is external).

Tananbaum G. (2013). Implementing an Open Data Policy: A Primer for Research Funders(link is external). Washington, DC.

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