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The NSF requirement

Big purple cloud in space
Stellar Debris in Large Magellanic Cloud/Smithsonian Institute

Data Planning

The National Science Foundation is requiring that grant proposals to the agency be supplemented by data management plans. Plans are not to exceed two pages and should address basics such as the following:

  • Types of data, samples, physical collections
  • Standards (for data and metadata)
  • Access and sharing policies
  • Policies for re-use and re-distribution
  • Archiving data and maintaining their access

Alternatively, a data management plan may consist of a statement that no plan is needed for the project, but the applicant must justify clearly why no plan will be forthcoming.

>> Consult NSF's Dissemination and Sharing of Research Results and FAQ for more guidance.

>> Several directorates and divisions with NSF offer more specific guidelines:

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data plan checklist

Pittsburgh quadrangle, Pennsylvania : 15 minute series (topographic)
Pittsburgh quadrangle, PA : 15 minute series / PSU Libraries

>> This checklist of questions can help you get started on managing data: 

  • What type of data will be produced?
  • How much, at what growth rate & will it change frequently?
  • Who is the contact for the data? Ownership issues?
  • Who is the audience?
  • How long should the data be retained?
  • What format is it in?
  • What tools or software are needed to work with the data?
  • Are there any sharing and/or privacy requirements from funders or research community?
  • What are the plans for data collection transition after project completion?
  • What are the key metadata elements?

>> See these resources for additional guidance:

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Elements of a data plan and links to examples

Periodic table of elements
Periodic table/Travürsa; Wikimedia Commons, GNU FDL

Use the framework below, adapted from one developed by the Inter-University Consortium for Political and Social Research (ICPSR), to orient further your thinking on, and approach to, drafting data management plans.

 

In addition, here are some examples of data management plans/templates:

 

 

Data Planning and Examples
Element Description
Data Description What are your data about? What do they look like? Who is the audience of users, or community types, for the data? Survey the existing data. What other existing data are relevant to what you have collected? These questions may help in deciding where to archive your data set.
Access and Sharing How will you archive and share your data and why have you chosen this method? What are the terms of use, if any? Indicate the timeliness of dissemination.
Metadata Describe the metadata that will go with the data. Discuss the metadata standards used.
Intellectual Property Rights Be clear in who owns the data and how intellectual property will be protected if needed. Who is responsible for personnel with access to data? Any copyright restrictions must be noted. Are there any legal requirements? If so, provide a list of all relevant federal and funder requirements.
Ethics and Privacy Describe how informed consent is handled and privacy protected. How are the data being protected during the project?
Format Describe how the data were generated, how they will be maintained and shared - including a rationale for process and archiving of suggested formats.
Archiving and Preservation What are the procedures in place, or envisioned, for long-term archiving and preservation including succession plans if transfer is needed? Include budget costs of preparing data and documentation. Requests for funding may be included as well.
Storage and Backup Consider storage methods and backup procedures - both cyber and physical resources for effective preservation and storage (several copies are recommended). What are the different levels of data retention from short-term to long-term preservation depending on the types of data? Another aspect is data organization, particularly for dynamic data. How will data be managed during the project? Provide information about version control and naming conventions.
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