As well as journals, funders (NIH, STFC, NERC, Wellcome Trust, et al.) are also starting to implement mandatory data sharing policies [1], with applicants being asked to disclose their data management plans (with obvious implications if they have no such plan [or a weak plan] in place).

In 2013, it was announced that all US Federal funding institutions must implement plans to expand public access to research datasets, whereby researchers receiving Federal grants must develop a data management plan, “describing how they will provide for long-term preservation of, and access to, scientific data in digital formats resulting from federally funded research, or explaining why long-term preservation and access cannot be justified” [2].

The National Science Foundation (NSF) requires a (no more than) two-page data management plan as part of their application process [3]. With the establishment of such data sharing standards, it is inevitable that the long-term maintenance and archiving of datasets will soon be a common feature in a researcher’s (already overloaded) work schedule.

While tedious initially, establishing an effective data management plan can save you time in the long run. By choosing a data repository beforehand, you can avoid having to re-organize or reformat your data files later. You can also save time by directing individual requests for data to the necessary repository. Effectively managing your data will also increase your research impact, ensure the preservation of your data, promote new discoveries, support the open access movement, and of course meet grant requirements [4].

Data management plans

For detailed descriptions on writing data management plans see here. Plans should include:  data description (e.g., data formats, software to view data etc.); personnel (who will be responsible for managing the data); documentation to help make the data understandable (e.g., read-me files); storage (repository? for how long?); access (will data be published in journal, embargoes on data?); a budget etc. [5] here.

Need help?

DMPtool is a free online tool, providing templates and guidance designed to help researchers create data management plans. You can create an account yourself or log in as a user from your institution if available (which will provide institution-specific guidance) [6].

The advent of open access and data sharing policies is still in its infancy, is fast-changing and will soon be an essential part of the research process. Get ahead of the game and start thinking about your data management strategy sooner rather than later.

References

1. Uzwyshyn, R. (2016) Research Data Repositories: The What, When, Why, and How. Information Today, Inc. Weblog. Retrieved from  http://www.infotoday.com/cilmag/apr16/Uzwyshyn–Research-Data-Repositories.shtml on 15 November 2016.
2. Holdren, J.P. (2013) Increasing Access to the Results of Federally Funded Scientific Research. Office of Science and Technology Policy. Memorandum. Retrieved from https://www.whitehouse.gov/sites/default/files/microsites/ostp/ostp_public_access_memo_2013.pdf on 15 November 2016.
3. National Science Foundation. (2011) Chapter II – Proposal Preparation Instructions. National Science Foundation. Retrieved from https://www.nsf.gov/pubs/policydocs/pappguide/nsf11001/gpg_2.jsp#dmp on 15 November 2016.
4. MITLibraries. (2016) Data Management. MITLibraries. Retrieved from http://libraries.mit.edu/data-management/plan/why/ on 16 November 2016.
5. ICPSR. (2016). Elements of a Data Management Plan. ICPSR. Retrieved from http://www.icpsr.umich.edu/icpsrweb/content/datamanagement/dmp/elements.html on 16 November 2016.
6. DMPTool. (2016). FAQ. DMPTool. Retrieved from https://github.com/CDLUC3/dmptool/wiki/FAQ on 16 November 2016.