This information is meant to assist PIs in developing a Data Management Plan, as required by NSF. Much of the information provided is directly from the Grant Proposal Guide.
The National Science Foundation now requires all proposals to include plans for data management and sharing of the products of research. Please note that 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. FastLane will not permit submission of a proposal that is missing a Data Management Plan. The Data Management Plan will be reviewed as part of the intellectual merit or broader impacts of the proposal, or both, as appropriate.
The Data Management Plan is submitted as a supplementary document of no more than two pages labeled "Data Management Plan". The Grant Proposal Guide states that this supplement should describe how the proposal will conform to NSF policy on the dissemination and sharing of research results and may include:
- name of the person(s) responsible for data management within your research project (additional suggestion).
- the types of data, samples, physical collections, software, curriculum materials, and other materials to be produced in the course of the project.
- 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).
- policies for accessing and sharing data including provisions for appropriate protection of privacy, confidentiality, security, intellectual property, or other rights or requirements.
- policies and provisions for re-use, re-distribution, and the production of derivatives.
- plans for archiving data, samples, and other research products, and for preservation of access to them.
- period of data retention (additional suggestion).
What counts as "data"? Research data are formally defined as "the recorded factual material commonly accepted in the scientific community as necessary to validate research findings" by the U.S. Office of Management and Budget (1999).
The basic level of digital data to be archived and made available includes (1) analyzed data and (2) the metadata that define how these data were generated. These are data that are or that should be published in theses, dissertations, refereed journal articles, supplemental data attachments for manuscripts, books and book chapters, and other print or electronic publication formats.
- Analyzed data are (but are not restricted to) digital information that would be published, including digital images, published tables, and tables of the numbers used for making published graphs.
- Necessary metadata are (but are not restricted to) descriptions or suitable citations of experiments, apparatuses, raw materials, computational codes, and computer-calculation input conditions.
What data are not included at the basic level? The Office of Management and Budget statement (1999) specifies that this definition does not include "preliminary analyses, drafts of scientific papers, plans for future research, peer reviews, or communications with colleagues." Raw data fall into this category as "preliminary analyses."
PIs should check for data management requirements and plans specific to the Directorate, Office, Division, Program, or other NSF unit. These are available at: http://www.nsf.gov/bfa/dias/policy/dmp.jsp. If guidance specific to the program is not available, then the requirements described in the Grant Proposal Guide (above) apply. Each of the colleges/departments at MSU have created templates for data plans, so please check with you Department Chair or Administrators.
Data Management Plans for Collaborative Proposals: 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.
For more information and examples of Data Plans at MSU please see: https://www.lib.msu.edu/about/diginfo/ldmp/ and https://lib.msu.edu/rdmg/
MSU Technologies facilitates the processing of Data Use Agreements (DUA) for Michigan State University; as well as related Material Transfer Agreements (MTA) and Confidential Disclosure Agreements (CDA).
Tip: Google "NSF data management plan examples" to find additional resources and examples.