A Data Management Plan (DMP)  is a document that outlines best practices in data management and how you will apply these practices in the course of your grant or project.

The following elements must be addressed in your plan:

• Data Type - Include the type of data and estimated amount of data being generated. Use general terms and descriptions about data modality (e.g. imaging, genomic, mobile, survey), how the data is aggregated and processed.

• Related Tools, Software and Code - Indicate if specialized tools are needed to reproduce your research and how they can be accessed.

• Standards - An indication of what standards will be applied to the scientific data and associated metadata (i.e., data formats, data dictionaries, data identifiers, definitions, unique identifiers, and other data documentation).

• Data Preservation - The name of the repository, where scientific data and metadata will be archived. For more information see NIH Repositories for Sharing Scientific Data.

• Access and Timelines - A description of how the data will be made available and what unique persistent identifiers (PID) you will use to support reporting out on your progress and outputs. Provide the timeframe with the expectation that the data should be made available as soon as possible.

• Access, Distribution, or Reuse Considerations - Including informed consent, privacy and confidentiality protections like de-identification and Certificates of Confidentiality, any data use agreements or licensing limitations.

• Oversight of Data Management and Sharing - How and when the data management plan will be monitored and managed, and by whom (e.g. , titles, roles).

Taken from: https://grants.nih.gov/grants/guide/notice-files/NOT-OD-21-014.html

UC San Francisco has created the DMP Template(s). These are based on the NIH format and have sample language to get you started.

• Generic DMS Template

• Clinical Trial DMS Template

• Social Science DMS Template

The following real world examples relate to health data and demonstrate the value of using a direct object identifier for your plan as well as connecting the DOI to your ORCID. Using the DMP tool to create and manage all your DMPs will help you stay organized.

• Damian Yukio Romero Diaz. (2022). "Using natural language processing to determine predictors of healthy diet and physical activity behavior change in ovarian cancer survivors" [Data Management Plan]. DMPHub. https://doi.org/10.48321/D1BK5T

• Andreia Faria. (2022). "FAIR annotated dataset of stroke MRIs, CTs, and metadata" [Data Management Plan]. DMPHub. https://doi.org/10.48321/D1J31B

• Data De-identification for Research Projects - Tip Sheet created by UC Davis Health Data Center of Excellence (DCOE). For questions contact: hs-dcoeresearch@ucdavis.edu

• DMP Tool - The California Digital Library at UCOP has developed a free, open-source, online application that helps researchers create data management plans (DMPs). The DMP Tool provides a click-through wizard for creating a DMP that complies with funder requirements. It also has direct links to funder websites, help text for answering questions, and data management best practices resources.

• DMP Checklist for Researchers.docx - This checklist from the working group on NIH DMSP guidance addresses the required elements in the NIH DMS Policy effective January 25, 2023.

• DMP Self-Assessment Questionnaire - This comprehensive questionnaire from Purdue University can help researchers think about all the different aspects of the research data lifecycle that should be addressed in a data management plan.

• Guidelines for an effective DMP - The ICPSR guideline provides a 21-page document that includes templates, a list of recommended elements to be included in DMP.

• NIH Tool - Repositories for sharing Scientific Data -  In general, NIH does not endorse or require sharing data in any particular repository, although some initiatives and funding opportunities will have individual requirements. Overall, NIH encourages researchers to select the repository that is most appropriate for their data type and discipline.

• Video: ICPSR Introduction to Data Management Plans - 13 minutes

• Video: GREI Collaborative Webinar Series on Data Sharing in Generalist Repositories

• Video: Understanding the New NIH Data Management and Sharing (DMS) Policy - 90 minutes

If you would like additional training (in person or virtual) from a CTSC staff member, complete the Ask the CTSC Concierge form and we will contact you.

Start by viewing this informative list of FAQ's from NIH.