Data Management : NSF Data Management Plans


The National Science Foundation, NSF required data management plans starting in January 2011. Since then the White House Office of Science and Technology Policy, OSTP issued a memo to all federal agencies with greater than $100 million in annual research and development expenditures:

“The Administration is committed to ensuring that, to the greatest extent and with the fewest constraints possible . . . the direct results of federally funded scientific research are made available to and useful for the public, industry, and the scientific community.”

The 2013 OSTP memorandum

Agencies have responded. Academic librarians across the nation have been monitoring and compiling the information as it is released by the various agencies. This information is available under the tab OSTP. Basically agencies are requiring any publications or data resulting from federally funded research be openly available to the public. Some agencies have identified repositories for the data and publications, but not all.

Requirements by Funding Agencies


This link leads to the California Digital Library's information on the requirements of funding agencies for writing a data management. It does not yet include all the information from agencies since the 2013 OSTP Memo was released.

Agencies included:

  • NSF: The National Science Foundation
  • NEH: National Endowment for the Humanities, Office of Digital Humanities
  • NIH: National Institutes of Health
  • NOAA: National Oceanic and Atmospheric Administration
  • IMLS: Institute of Museum and Library Services
  • Gordon and Betty Moore Foundation
  • DOE: Office of Science (see tab with DOE data management plan information)


Online Tutorial -Data Management

The University of Utah, Office of the VP for Research has developed a Research Education, ReD. There there is a class being offered in data management.


Research Data Management and Sharing

From our friends across the pond-

The Research Data Management Training, or MANTRA project has produced an open, online training course to help disseminate good practice in research data management at the University of Edinburgh and beyond. 

What is it?

It is a non-credit, free online course which provides guidelines for good practice in research data management. It consists of interactive online units focused on key concepts of data management. They include video clips featuring senior academics talking about data management challenges. In addition there are practical exercises in handling data within four software analysis environments (SPSS, NVivo, R and ArcGIS), which learners can download and work through at their own pace.

Who is it for?

It is for PhD students, early career researchers, and all others who are planning a research project based on digital data. The course is an Open Educational Resource that may be freely used by anyone. It is available through an open license for rejigging, rebranding, and repurposing.

Who produced it?

The Data Library team at EDINA produced the materials as part of the JISC Managing Research Data programme. They worked with the School of Social and Political Studies, the School of GeoSciences and the Doctorate in Clinical Psychology to target the resources towards their doctoral training programmes. The Data Library at the University of Edinburgh has been providing research data services to staff and students for over twenty-five years. The data handling software practicals were written by expert data analysts in each software domain. The online module was created using Xerte Online Toolkits, an open source authoring tool.

Online Data Management Tool

The University of Utah has joined dozens of institutions nationwide in providing researchers access to the DMPTool administered by the University of California Curation Center. Click open the above image and logon on using your UNID. Select the funding agency and answer the questions to build your data management plan. The document will be saved under your UNID. When completed the document will be ready to upload with your grant application.

NSF Data Policy & Requirements

From the NSF Website

NSF Data Sharing Policy

Investigators are expected to share with other researchers, at no more than incremental cost and within a reasonable time, the primary data, samples, physical collections and other supporting materials created or gathered in the course of work under NSF grants. Grantees are expected to encourage and facilitate such sharing. See Award & Administration Guide (AAG) Chapter VI.D.4.

NSF Data Management Plan Requirements

Proposals submitted or due on or after January 18, 2011, must include a supplementary document of no more than two pages labeled “Data Management Plan”. This supplementary document should describe how the proposal will conform to NSF policy on the dissemination and sharing of research results. See Grant Proposal Guide (GPG) Chapter II.C.2.j for full policy implementation.

Plans for data management and sharing of the products of research. Proposals must include a supplementary document of no more than two pages labeled “Data Management Plan”. This supplement should describe how the proposal will conform to NSF policy on the dissemination and sharing of research results (see AAG Chapter VI.D.4), and may include:

  1. the types of data, samples, physical collections, software, curriculum materials, and other materials to be produced in the course of the project;
  2. the standards to be used for data and metadata format and content (where existing standards are absent or deemed inadequate, this should be documented along with any proposed solutions or remedies);
  3. policies for access and sharing including provisions for appropriate protection of privacy, confidentiality, security, intellectual property, or other rights or requirements;
  4. policies and provisions for re-use, re-distribution, and the production of derivatives; and
  5. plans for archiving data, samples, and other research products, and for preservation of access to them.

Data management requirements and plans specific to the Directorate, Office, Division, Program, or other NSF unit, relevant to a proposal are available at: If guidance specific to the program is not available, then the requirements established in this section apply.
Simultaneously submitted collaborative proposals and proposals that include subawards are a single unified project and should include only one supplemental combined Data Management Plan, regardless of the number of non-lead collaborative proposals or subawards included. Fastlane will not permit submission of a proposal that is missing a Data Management Plan. Proposals for supplementary support to an existing award are not required to include a Data Management Plan.
A valid Data Management Plan may include only the statement that no detailed plan is needed, as long as the statement is accompanied by a clear justification. Proposers who feel that the plan cannot fit within the supplement limit of two pages may use part of the 15-page Project Description for additional data management information. Proposers are advised that the Data Management Plan may not be used to circumvent the 15-page Project Description limitation. The Data Management Plan will be reviewed as an integral part of the proposal, coming under Intellectual Merit or Broader Impacts or both, as appropriate for the scientific community of relevance.

Data Management Plan Considerations

NOTE 1:Your NSF Data Management Plan is a 2-page section separate from the body of the grant proposal.  For instance if you have an evaluation plan in your proposal, you should describe all data to be collected within the body of the proposal. Do not only describe the evaluation plan as part of the Data Management Plan.  

NOTE 2: Your plan should include both the management of your data (where it will be stored, backed up, etc.) and how you will share it with the research community. If both points are not addressed, your grant application may be returned.

If you receive any direct comments on your data management plan from your review panel, please email


1. Who is responsible for the data and its management? Yes, the PI is ultimately responsible, but the person(s) responsible for the day-to-day management of the data needs to be identified.

2. What type of data will be produced and how?

  • Will data be digital or in print?
  • How much will there be?
  • What tools/software will be used to create the data?
  • What format is the data in?
  • Is the format non-proprietary?
  • Are there tools/software needed to use the data after it has been archived

3. Where and how will the data be stored while the project is ongoing?

  • Will it be backed up?
  • How often?
  • By whom?

4. How will the data be organized during the research process?

  • File naming conventions
  • Project identifiers
  • Code books, lab diaries
  • Other

5. Will an electronic laboratory notebook, CHPC servers or Ubox be used?

6. How much data are you generating, GB, TP?

7. Are there security or privacy concerns for this data?

  • Are you collecting private information from human subjects?
  • Will the data be used to develop a product? (Have you talked to the Technology Commercialization Office?)
  • Who will have access to the data during the research process?
  • Will you be able to de-identify human subjects after the research has been completed?

8. Where will the data be archived at the end of the project? Uspace, the University of Utah’s official repository is not appropriate for research data. We are presently working on a solution. If you are interested in assisting by providing your datasets, contact  There are over 1000 subject-based data repositories. Check out the tab on Repositories for Research Data.  Two points to consider when seeking a repository, the format and size of your datasets and the subject of your research. You will probably have to contact the repository to determine if your research data is appropriate for their collection AND also ask about costs. Need assistance with this, contact 

Considerations when selecting a data repository:

  • Are you being required by funding agency, journal editors, etc. to deposit your research data in a specific subject repository/database?
  • Does this repository follow established preservation standards?
  • Will the data be freely accessible?
  • How long will the data be kept in the repository after the project has been completed?
  • Does it provide a persistent identifier, DOI?
  • Does it provide a suggested citation for others to use when using your data.
  • How much will it cost? - Funding agencies are now allowing for this cost as part of the grant proposal.

Since there are new repositories being developed all the time, you can list a repository in your data management plan and then state "the data will be deposited here unless a more appropriate data repository is determined at the end of the project".









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