The National Science Foundation (NSF) has published a revised version of their Proposal and Award Policies and Procedures Guide (PAPPG) that requires, in all proposals submitted or due on or after January 18, 2011, a supplementary document of no more than two pages describing a Data Management Plan for the proposed research. As a supplementary document, the data management plan is not included in the 15-page limit for proposal bodies. Fastlane will not permit submission of a proposal that is missing the Data Management Plan. 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; the plan may not be used to circumvent the 15-page Project Description limitation.
The Data Management Plan will be reviewed as part of the intellectual merit or broader impacts of the proposal, or both, as appropriate. The goal is to provide clear, effective, and transparent implementation of the long-standing NSF Policy on Dissemination and Sharing of Research Results, which may be found in the Award Administration Guide, Section VI.D.4. After an award is made, compliance with the data management plan will be monitored through the Annual and Final Report process and through evaluation of subsequent proposals. Data management activities must be reported in subsequent proposals by the PI and Co-PIs under “Results of prior NSF support.”
This page is intended to assist researchers, principal investigators, grant administrators, support staff, and other members of the University of Michigan community who need to prepare a data management plan in compliance with the new NSF requirements.
- What Data Are Included?
- What Data Are Not Included?
- Which Guidelines Apply to My Proposal?
- NSF Guidance
- Directorate-Level Guidance
- University-Level Guidance
- DMP How-To
- Getting Help With Your Plan
What Data Are Included?
Beyond mentioning a few basic categories (samples, physical collections, software and curriculum materials), the PAPPG does not attempt to define data; it is expected that norms for what are and are not considered data, and thus candidates for inclusion in the DMP, will be developed by members of research communities where they do not already exist. The best way to determine what data to include in your plan is to consult the guidelines offered by the appropriate NSF directorate and/or division, as well as any special requirements laid out in the solicitation. However, the federal government does provide a baseline definition of research data which may be useful when thinking about what to include in your plan.
Research data are formally defined by the U.S. Office of Management and Budget as “the recorded factual material commonly accepted in the scientific community as necessary to validate research findings.” This definition includes both analyzed data and the metadata that describe how those data were generated. "Analyzed data" include, but are not limited to, digital information that would be included in scientific publications, including digital images, published tables, and tables of the numbers used to create charts and graphs. "Necessary metadata" include, but are not limited to, descriptions or suitable citations of experiments, apparatuses, raw materials, computational codes, model parameters and input conditions. In general, research data are anything an investigator would need to reproduce published results.
What Data Are Not Included?
The Office of Management and Budget's definition of research data does not include “preliminary analyses, drafts of scientific papers, plans for future research, peer reviews, or communications with colleagues.” For some NSF directorates, raw data fall into the category of “preliminary analyses” and are thus excluded from the DMP; others may require a DMP for raw data. Again, check the guidelines from NSF directorates and divisions if you are unsure.
Which Guidelines Apply to My Proposal?
Before reviewing the information below it's important to note the precedence relationships that exist between guidelines from various NSF units. In addition to the guidelines published in the NSF's Proposal and Award Policies and Procedures Guide (PAPPG) and recommendations from NSF directorates and divisions, some NSF solicitations may impose their own data management requirements (see NSF 09-514 for one example.) This page attempts to summarize what is growing to be a potentially confusing array of documentation.
In general, researchers should give preference to the more specific solicitation- and directorate- or division-level guidelines, falling back on the PAPPG as necessary. However, most of the existing directorate-level guidelines state that the PAPPG is to take precedence if there is a conflict. In other words, guidelines should be followed in this order:
- First, follow the requirements laid out in the specific solicitation, if any. These can generally be found in a section entitled "Proposal Preparation Instructions." Contact the program officer with any questions.
- Second, follow the guidelines published by the appropriate NSF directorate and/or division. Not all directorates and divisions have published data management guidelines; check the NSF's page on Dissemination and Sharing of Research Results for updates. If there is a conflict with the PAPPG, the latter takes precedence.
- Third, follow the more general guidelines in the PAPPG and the Award and Administration Guide. You may also want to refer to the NSF FAQ on data sharing if the documentation on this page does not answer your question.
Data Sharing Policy
The NSF Policy on Dissemination and Sharing of Research Results (Award Administration Guide, Section VI.D.4) states:
- Investigators are expected to promptly prepare and submit for publication, with authorship that accurately reflects the contributions of those involved, all significant findings from work conducted under NSF grants. Grantees are expected to permit and encourage such publication by those actually performing that work, unless a grantee intends to publish or disseminate such findings itself.
- 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. Privileged or confidential information should be released only in a form that protects the privacy of individuals and subjects involved. General adjustments and, where essential, exceptions to this sharing expectation may be specified by the funding NSF Program or Division/Office for a particular field or discipline to safeguard the rights of individuals and subjects, the validity of results, or the integrity of collections or to accommodate the legitimate interest of investigators. A grantee or investigator also may request a particular adjustment or exception from the cognizant NSF Program Officer.
- Investigators and grantees are encouraged to share software and inventions created under the grant or otherwise make them or their products widely available and usable.
- NSF normally allows grantees to retain principal legal rights to intellectual property developed under NSF grants to provide incentives for development and dissemination of inventions, software and publications that can enhance their usefulness, accessibility and upkeep. Such incentives do not, however, reduce the responsibility that investigators and organizations have as members of the scientific and engineering community, to make results, data and collections available to other researchers.
- NSF program management will implement these policies for dissemination and sharing of research results, in ways appropriate to field and circumstances, through the proposal review process; through award negotiations and conditions; and through appropriate support and incentives for data cleanup, documentation, dissemination, storage and the like.
Contents of a Data Management Plan
As stated in the Proposal and Award Policies and Procedures Guide, the Data Management Plan should include the following information:
- Products of the Research: The types of data, samples, physical collections, software, curriculum materials, and other materials to be produced in the course of the project.
- Data Formats: 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).
- Access to Data and Data Sharing Practices and Policies: Policies for access and sharing including provisions for appropriate protection of privacy, confidentiality, security, intellectual property, or other rights or requirements.
- Policies for Re-Use, Re-Distribution, and Production of Derivatives.
- Archiving of Data: Plans for archiving data, samples, and other research products, and for preservation of access to them.
Some NSF directorates have issued their own guidelines for the preparation of the data management plan. These guidelines are not intended to replace the guidance given in the PAPPG; if there is a conflict, the PAPPG takes precedence.
The table below summarizes directorate- and division-specific guidelines (where they exist) with links to full documentation. This table will be updated with guidelines from the remaining directorates as they are issued; also check the NSF's page on Dissemination and Sharing of Research Results.
|NSF Unit||Summary of Guidelines|
|Directorate for Biological Sciences (BIO)||
Since DMPs will be considered during the merit review process, to help reviewers, and as appropriate, please organize the DMP as follows:
|Division of Molecular & Cellular Biosciences||Use BIO guidance|
|Division of Biological Infrastructure||Use BIO guidance|
|Division of Integrative Organismal Systems||Use BIO guidance|
|Division of Environmental Biology||Use BIO guidance|
|Emerging Frontiers Office||Use BIO guidance|
|Directorate for Computer & Information Science & Engineering (CISE)||See link for details|
|Division of Computing & Communication Foundations||Not yet available|
|Division of Computer & Network Systems||Not yet available|
|Division of Information & Intelligent Systems||Not yet available|
|Directorate for Education & Human Resources (EHR)||
The DMP should reflect best practices in the PI’s area of research and should be appropriate to the data generated. For proposals submitted to EHR, the plan should address two main questions: What data are generated by your project? What is your plan for managing the data?... [more]
|Division of Research on Learning in Formal & Informal Settings||Not yet available|
|Division of Graduate Education||Not yet available|
|Division of Human Resource Development||Not yet available|
|Division of Undergraduate Education||Not yet available|
|Directorate for Engineering (ENG)||
|Division of Chemical, Bioengineering, Environmental & Transport Systems||Not yet available|
|Division of Civil, Mechanical & Manufacturing Innovation||Not yet available|
|Division of Electrical, Communications & Cyber Systems||Not yet available|
|Division of Engineering Education & Centers||Not yet available|
|Office of Emerging Frontiers in Research & Innovation||Not yet available|
|Division of Industrial Innovation & Partnerships||Not yet available|
|Directorate for Geosciences (GEO)||See link for a summary of GEO data policies, with links to divisional DMP guidelines.|
|Division of Atmospheric & Geospace Sciences||
|Division of Earth Sciences||
|Division of Ocean Sciences||No specific guidance on preparing the DMP, but see link for detailed policies on data sharing and archiving (including a list of appropriate data centers) which will be useful when preparing your plan.|
|Integrated Ocean Drilling Program||No specific guidance on preparing the DMP, but see link for IODP-specific policies on data sharing and archiving, which will be useful when preparing your plan.|
|Directorate for Mathematical & Physical Sciences (MPS)||Use the appropriate divisional guidance|
|Division of Astronomical Sciences||
|Division of Chemistry||
|Division of Materials Research||
|Division of Mathematical Sciences||
|Division of Physics||
|Directorate for Social, Behavioral & Economic Sciences (SBE)||
PIs should use the opportunity of the DMP to give thought to matters such as:
|Division of Social & Economic Sciences||Use SBE guidance; SES contact for DMP questions: Rachel Croson|
|Division of Behavioral & Cognitive Sciences||Use SBE guidance; BCS contact for DMP questions: Mark Weiss and Amber Story|
|National Center for Science & Engineering Statistics||Use SBE guidance; NCSES contact for DMP questions: Steve Cohen|
|Office of Multidisciplinary Activities||Use SBE guidance|
- LSA Joint IT Research Committee Data Management Plan Webpage
- SPG 601.12: Institutional Data Resource Management Policy
- Data Administration Guidelines for Institutional Data Resources
- Data Stewards/Data Managers List
- Policy information from the Office of Tech Transfer
Departmental Data Management Policies
Does your department have a data management policy? Please let us know and we will include it here.
Here you will find examples of actual submitted plans, as well as a number of templates and DMP tutorials to aid you in writing your plan. Please note that some of these documents were developed for funding agencies other than NSF and may not address all of the required components of the NSF plan. Be sure to consult the NSF guidelines, as well as any applicable directorate-level guidelines and any special requirements that have been provided in the solicitation.
- ICPSR has a large collection of data management plans and associated resources.
- Example Data Management Plans from NSF proposals submitted by researchers at UC San Diego.
- Sample data management plans written by members of the Faculty Senate's Research Committee at Rice University (based on actual proposals).
- Sample Data Management Plans from the University of Virginia's Odum Institute for Research in Social Science.
- DMP Examples from DataONE:
- DMP examples from the UK Rural Economy and Land Use Programme.
- The NSF ENG Data Management Plan Template for the University of Michigan College of Engineering contains many examples taken from actual U-M proposals (all from the College of Engineering).
Templates, Outlines, Worksheets
- NSF ENG Data Management Plan Template for the University of Michigan College of Engineering.
- DMP Self-Assessment Tool from Purdue University Libraries.
- NSF Data Management Plan Guidance and Template from the Research Office at the University of Michigan's College of Literature, Science, and the Arts.
NSF Data Management Plan templates from the University of Virginia:
- NSF GENERIC (Use for Directorates and/or Divisions with no specific guidance)
- NSF Division of Astronomical Sciences (AST)
- NSF Division of Atmospheric & Geospace Sciences (AGS)
- NSF Directorate for Biological Sciences (BIO)
- NSF Division of Chemistry (CHE)
- NSF Directorate for Computer & Information Sciences & Engineering (CISE)
- NSF Division of Earth Sciences (EAR)
- NSF Engineering Directorate (ENG)
- NSF Education & Human Resources Directorate (EHR)
- NSF Division of Materials Research (DMR)
- NSF Division of Mathematical Sciences (DMS) (Guidance Only)
- NSF Social, Behavioral and Economic Sciences Directorate (SBE)
- NSF Division of Physics (PHY)
- DMP generator form from Integrated Earth Data Applications. Tailored to earth and ocean sciences.
- DMP template and data worksheet from UC San Diego.
- Checklist for a Data Management Plan from the Digital Curation Centre (UK).
- Plan template from the UK Rural Economy and Land Use Programme.
- Research Data Management Plan Template from the University of Melbourne.
Guides and Tutorials
- ICPSR's Framework for Creating a Data Management Plan.
- How to Write a Data Management Plan for a National Science Foundation (NSF) Proposal from James Brunt at Long Term Ecological Research Network (LTER).
- Guide to Developing a Data Management and Sharing Plan from the Digital Curation Centre (UK).
Getting Help With Your Plan
There are a number of resources available to U-M researchers who need help writing a data management plan. ORSP's Data Sharing Resource Center is available for consultations. ICPSR is a locus of expertise on data management and may be able to offer advice, even to researchers outside the social sciences. Your science subject librarian may be able to help you identify resources to use in your plan, such as discipline-specific data repositories.
The library's Copyright Office can help with questions about data licensing issues, and the Office of Technology Transfer can advise on intellectual property and patent questions. If your research involves human subject data, the caBIG Knowledge Center has developed a framework to help you determine how the data can be shared. Also see the other pages in this guide for links to preferred disciplinary repositories, on-campus storage and data archiving solutions, and other relevant resources.