Research Data Management (Health Sciences)

A Data Management Plan (DMP) is a document that describes how you will handle your data during the course of your research and how you plan to disseminate your data at the conclusion of your study or project. It may also be called a Data Management & Sharing Plan (DMS Plan) or a Data Sharing Plan (DSP).

Many funding agencies require data management or data sharing plans to be submitted with new grant applications. Each funding agency has specific requirements, so it is important to check the guidelines for your specific grant.

In addition to meeting funder requirements, many data management issues can be handled easily or avoided entirely by planning ahead. A good DMP will:

• save you time
• simplify your research
• safeguard against data loss
• extend the life of your research
• make your research more findable and reusable

The templates below provide a framework for writing a data management plan. They are generic plans, not connected to a specific funder. Please see the additional links on the left to navigate to resources for writing a DMP for a specific funder. The templates are also available in DMPTool:

• Sign into DMPTool and select "Create Plan"
• Check the box "No funder associated with this plan or my funder is not listed"
• Under "Which DMP template would you like to use?" find the U-M templates

Although DMP requirements vary by funding agency, your plan will typically need to address the following topics:

Data Description:

• What type of data is it - numeric, text, images? What format is it in?
• How much data will there be?
• How will the data be collected or generated, and for how long? What tools and methodologies will be used?
• Will you be using secondary data? What is the source of the data?
• Who is responsible for managing the data and implementing the data management plan?

Data and Metadata Standards:

• What data and metadata standards will be used? If there are no existing standards, how will this be addressed?
• What file formats and naming conventions will be used? How will the data be organized?
• How will the metadata be managed and stored?

Data Access, Sharing, and Re-Use:

• Does the project involve human subject data? If so, what are your plans to protect and anonymize the data?
• Are there any intellectual property considerations that need to be addressed?
• Are there any patent or licensing restrictions to be considered?
• How should the data be attributed?

Archiving and Preservation:

• Where will the data be archived, and for how long?
• Is there a discipline-specific repository available?
• What software or tools should be archived with the data to facilitate re-use?

For a more comprehensive list of items that could be included in a data management plan, visit:

Many journals now require a data sharing statement or data availability statement to accompany a publication. This is different than a data management or sharing plan which a funder might require when applying for a grant, prior to beginning a research project. The purpose of this requirement is to facilitate transparency in the scientific process at the point of publication, connecting a manuscript with the data that supports its conclusions. A data sharing statement should include the following information:

• Information about the data that has been shared (e.g. data supporting publication or anonymized individual participant data);
• How someone can access that data, including a URL or email address;

OR

• Justification for why no data is available;

For more information about data sharing, please see the Share Data page on this guide.