LibGuides: Data Management: Data Management Plans

UNCW DMP Tool

Use the UNCW-affiliated resource DMPTool with funder Data Management Plan templates and guidance.

To receive feedback on your DMP, click the Request Feedback button in your application in DMPTool, or email Lynnee Argabright, Research Data Librarian, at argabrightl@uncw.edu

DMP Tool
DMPTool

Trainings at UNCW:

Data Management Using DMP Tool--Spring 2022 (PPT Slides)
Complying with NIH Data Management and Sharing 2023 Policy--Fall 2022 (PPT Slides / Recording)

What are Data Management Plans?

Data management plans (DMP) document how research data will be collected, organized, stored and maintained. DMPs require some thought and preparation in advance, but increase the long-term utility of the data. The following outline offers guidance on some of the basic questions that a DMP should answer.

Description: What data will be collected? What are the size and format of the data? How will the data be documented to make the data more discoverable and comprehensible to you and your research partners in the future? What metadata standards will be followed? If another researcher generated the data, document the source.
Storage: Where will the data be stored? How will the files be organized and named? What are the back-up procedures?
Preservation: How long should the data be retained? What tools and software are required to read the data?
Policies for Access, Data Sharing, and Re-use: Will others have access to the data, and if so, by whom? Will the entire data set be available or a subset? When will it be accessible? If sharing the data raises privacy or ethical concerns, what is the remediation plan? Will re-use, redistribution, or the creation of derivative works be allowed?
Dissemination: Will you use UNCW's institutional repository, Seahawk DOCKS, to make the data accessible or a discipline-specific repository?
Roles and Responsibilities: Who will be responsible for managing the data? Who holds the intellectual rights to the data?

The websites below provide useful templates, checklists, examples, and other resources for developing a data management plan:

Trainings at UNCW:

Tips for Writing an Effective Data Management Plan--Spring 2022 (Recording link)

NIH Feedback about NIH DMPs
With the one-year anniversary of implementation of the NIH Data Management and Sharing Policy, the NIH shares feedback and clarification about writing a good DMP.
NIH DMP Guidance
NIH DMP support was developed by several U.S. data librarians--including a checklist for NIH DMPs, a catalog of exemplar DMPs, an annotated example of a DMP, NIH-approved data repositories, and a glossary of grant terminology.
NSF DMP Rubric
Based on an analysis of DMP quality in 2017, data librarians put together a rubric with sample language of what makes up a good/poor response for all elements of a NSF DMP.
Examples of Qualitative Data NSF DMPs
Here are 11 outstanding NSF DMPs to use as examples if you are doing a study with qualitative (and often sensitive) research data.
Guidelines for Effective DMPs (funder-generic)
From the Inter-university Consortium for Political and Social Research (ICPSR). Includes how you would be able to utilize ICPSR as the data repository for sharing your (generally social science) data.

Funding Agency Guidelines

Many funding agencies require that grant proposals include a data management plan. While DMPTool (described at the top of this page) can be a convenient "one stop shop" resource of funder DMP guidance and templates for most federal funders, below are links to the agencies' websites themselves that separately provide official language guidance on their own specific requirements.

Department of Education Implementation Guide to Public Access to Research Data
Department of Education Implementation Guide to Public Access to Research Data
Department of Energy Digital Research Data Management: Suggested Elements for a Data Management
Department of Energy Digital Research Data Management: Suggested Elements for a Data Management Plan
National Endowment for the Humanities Data Management Plans for the Office of Digital Humanities
National Endowment for the Humanities Data Management Plans for the Office of Digital Humanities
National Institute of Food and Agriculture Data Management Plan for NIFA-Funded Research Projects
National Institute of Food and Agriculture Data Management Plan for NIFA-Funded Research Projects
National Institutes of Health (NIH) Data Sharing Policy and Implementation Guidance
National Institutes of Health (NIH) Data Sharing Policy and Implementation Guidance
National Science Foundation (NSF) Data Management Plan Requirements and FAQ
National Science Foundation (NSF) Data Management Plan Requirements and FAQ
U.S. Geological Survey Data Management Plans
U.S. Geological Survey Data Management Plans
Funder updates to their Open Access Requirements (all to become enforced by December 31, 2025)
Here is a consolidated list of federal grant funders, linking to their latest Public Access Policy (for funded researchers' articles and data). Funders are required to have an updated Policy by end-2025; one (the NIH) has already enacted their Policy, others (such as USGS and NSF) have finalized their policy but not enacted it yet, and others (such as the DoD) are still in progress of writing their policy.

Budgeting for Research Data in Grants

NIH data budgeting guidance
Includes allowable and unallowable costs
UK Data Service's Data Management Costing Tool
This checklist template helps you determine how much to budget for data management costs based on various common needs related to the preparing the dataset, documentation, metadata, formatting and organizing, transcription, storage and access, and anonymization.
COGR's Cost Considerations for Data Management (based on NIH policy)
COGR (Council on Governmental Relations, an association of research universities) identifies various points for PIs to consider when planning data management-related costs to request in a project budget. Guidance includes spreadsheet template of data management topics by collaborator role and data repository calculators.
NAS's Cost Forecasting Checklist for Biomedical Data
National Academies for Sciences, Engineering, and Medicine developed a checklist template to help researchers estimate costs for short- and long-term needs of data.