Data management plans usually include the following:

  1. Describe the data that your research will generate/collect.
    In addition to describing the types of data for your research, also describe the formats for the files in which the data will be stored, maintained, and made available. Use non-proprietary formats or convert data converted to more open, shareable formats, whenever possible.
  2. Describe how you will annotate and/or describe the data, including the metadata standards and tools (if any) that will be employed.
    Describe the descriptive information (e.g., lab or field notes, statistical and computational methods and scripts, instrumentation configuration). This metadata can take a variety of forms. Also describe any applicable standards for metadata content and format that you will follow, including the procedures and tools/software you will use to capture and edit the metadata.
  3. How will the data be organized, stored and protected during the research project?
    Describe the storage and backup resources and procedures for the data. For sensitive data, describe what measures will be taken for protection of privacy and confidentiality. Also consider security, intellectual property, and other rights.

  4. How will the data be shared with others, during and after the project?
    When possible, it is to your advantage to deposit your research data in data centers or repositories that facilitate access to (and often, preservation of) the data. This should include a description and rationale for any restrictions on who may access the data and under what conditions, a timeline for providing access, and information on the resources that will be needed to meet anticipated requests.

  5. Where and how will the data be archived/preserved for long-term access?
    Describe your plans for preserving data in accessible form. Include a timeline proposing how long the data are to be preserved, outlining any changes in access anticipated during the preservation timeline, and documenting the resources needed to meet the preservation goals.

  6. Include the costs associated with data management, access and preservation in your budget.
    Your plan does not need to include a budget, per se. However, NIH and NSF allow data management costs to be included in a proposal budget. If those costs can be defined you should budget for them, and consider how the expenditures would be addressed before the grant closes (sometimes, before articles and associated data are published). Examples might include: fees charged by some repositories, and data preservation for large datasets that are too large to be deposited in a repository.