Data management plan

A data management plan or DMP is a formal document that outlines how you will handle your data both during your research, and after the project is completed.[1] The goal of a data management plan is to consider the many aspects of data management, metadata generation, data preservation, and analysis before the project begins; this ensures that data are well-managed in the present, and prepared for preservation in the future.

Importance

Preparing a data management plan before data are collected ensures that data are in the correct format, organized well, and better annotated.[2] This saves time in the long term because there is no need to re-organize, re-format, or try to remember details about data. It also increases research efficiency since both the data collector and other researchers will be able to understand and use well-annotated data in the future. One component of a good data management plan is data archiving and preservation. By deciding on an archive ahead of time, the data collector can format data during collection to make its future submission to a database easier. If data are preserved, they are more relevant since they can be re-used by other researchers. It also allows the data collector to direct requests for data to the database, rather than address requests individually. Data that are preserved have the potential to lead to new, unanticipated discoveries, and they prevent duplication of scientific studies that have already been conducted. Data archiving also provides insurance against loss by the data collector.

Funding agencies are beginning to require data management plans as part of the proposal and evaluation process.[3]

Major Components

Information about data & data format

Metadata content and format

Metadata are the contextual details, including any information important for using data. This may include descriptions of temporal and spatial details, instruments, parameters, units, files, etc. Metadata is commonly referred to as “data about data”.[5] Consider the following:

Policies for access, sharing, and re-use

Long-term storage and data management

Budget

Data management and preservation costs may be considerable, depending on the nature of the project. By anticipating costs ahead of time, researchers ensure that the data will be properly managed and archived. Potential expenses that should be considered are

The data management plan should include how these costs will be paid.

NSF Data Management Plan

All grant proposals submitted to NSF must include a Data Management Plan that is no more than two pages.[6] This is a supplement (not part of the 15 page proposal) and should describe how the proposal will conform to the Award and Administration Guide policy (see below). It may include the following:

  1. The types of data
  2. The standards to be used for data and metadata format and content
  3. Policies for access and sharing
  4. Policies and provisions for re-use
  5. Plans for archiving data

Policy summarized from the NSF Award and Administration Guide, Section 4 (Dissemination and Sharing of Research Results):[7]

  1. Promptly publish with appropriate authorship
  2. Share data, samples, physical collections, and supporting materials with others, within a reasonable time frame
  3. Share software and inventions
  4. Investigators can keep their legal rights over their intellectual property, but they still have to make their results, data, and collections available to others
  5. Policies will be implemented via
    1. Proposal review
    2. Award negotiations and conditions
    3. Support/incentives

ESRC Data Management Plan

Since 1995, the UK's Economic and Social Research Council (ESRC) have had a research data policy in place. The current ESRC Research Data Policy states that research data created as a result of ESRC-funded research should be openly available to the scientific community to the maximum extent possible, through long-term preservation and high quality data management.[8]

ESRC requires a data management plan for all research award applications where new data are being created. Such plans are designed to promote a structured approach to data management throughout the data lifecycle, resulting in better quality data that is ready to archive for sharing and re-use. The UK Data Service, the ESRC's flagship data service, provides practical guidance on research data management planning suitable for social science researchers in the UK and around the world.[9][10]

ESRC has a longstanding arrangement with the UK Data Archive, based at the University of Essex, as a place of deposit for research data, with award holders required to offer data resulting from their research grants via the UK Data Service.[11] The Archive enables data re-use by preserving data and making them available to the research and teaching communities.

References

  1. ↑ http://www2.lib.virginia.edu/brown/data/plan.html
  2. ↑ http://libraries.mit.edu/data-management/plan/why/
  3. ↑ http://www.nsf.gov/bfa/dias/policy/dmpfaqs.jsp
  4. ↑ "Elements of a Data Management Plan". www.icpsr.umich.edu. Retrieved 2015-09-30.
  5. ↑ Michener,WK and JW Brunt. 2000. Ecological Data: Design, Management and Processing. Blackwell Science, 180p.
  6. ↑ http://www.nsf.gov/pubs/policydocs/pappguide/nsf11001/gpg_2.jsp#dmp
  7. ↑ http://www.nsf.gov/bfa/dias/policy/dmp.jsp
  8. ↑ ESRC Research Data Policy 2010
  9. ↑ Prepare and manage data: Guidance from the UK Data Service
  10. ↑ SAGE handbook: Managing and Sharing Data: A Guide to Good Practice
  11. ↑ UK Data Archive: Who can deposit data?

Further reading

Pryor, Graham (2014). Delivering research data management services. Facet Publishing. ISBN 9781856049337. 

External links

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