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Plan and Refine Project
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Devising the data strategy
Subtopic

Develop the data management plan

Need assistance with data management planning?

A data management plan (DMP) is a document that describes the data governance policies within each group or project (i.e. how data are documented, organized, stored, and shared). This ensures that the appropriate researcher(s) will be able to safely and securely access and analyze the data across the activities of a research group or at each project phase.

This page provides guidance and resources for developing a DMP. NIH-specific guidance is available on the NIH Data Management and Sharing Policy page:

Data Management Online Learning

Please see some selected Online Training Modules concerning Data Management from the Duke University Libraries. Additional videos can be found in the “Related Resources” section of this page under “Training and Job Aides.”

Creating a data management plan

Data management plans:

  • are highly useful to ensure there are appropriate resources available,
  • function as a reference guide for the entire research team throughout the project duration, and,
  • are required by several funders as a component of the funding proposal. 

Developing sound strategies for storing and organizing data prior to beginning the project also supports study reproducibility and end-of project goals, such as publication and data sharing.

Plans can either be “General” to cover all research activities that a research group engages in or “Project specific” which describes in greater detail the data management expectations of a specific research inquiry. Funders often require Project Specific DMPs as part of the funding proposal.

Data Management Plan Examples

Example DMPs are provided below with permission. Please note that these are “general” DMPs.

Considerations for developing a data management plan

Using the DMP tool

Duke participates in a program to allow researchers access to the DMPTool to develop data management plans. Research teams can access the integrated guidance resources, funder templates, and access Duke specific templates and consultation through Duke Libraries.

  • Within the DMPTool, select the “Get Started” button.
  • Select “Your institution” under sign-in option 1.
  • Select Duke University from the institutions list to log-in with a Duke NetID and password.
  • Select "Create a Plan" and check "No funder associated with this plan" and Duke’s data management guidance suggestions and best practices will automatically populate the tabs. 

Each tab walks the user through sub-sections of developing a data management plan. On the right-hand side for each section, discover best practices and considerations for what should be included in that section of the plan.

The “Request Feedback” tab can be used to send a request to Duke Libraries to review and provide feedback on a plan during any point of development. There is usually a three-day turnaround to receive feedback.

Roles and responsibilities

Who will be involved in the research project during each stage of the data life cycle?

  • Collecting or obtaining the data
  • Performing quality assurance checks of the data
  • Cleaning and curating the data
  • Analyzing the data
  • Archiving and sharing the data

What is each team member’s role within each stage and will they need additional training to carry out those responsibilities?

Research methods and data description

What data are essential to the aims of the research project? How is this data being obtained and what are the data collection methods?

If secondary data is being used, data classification should be understood.

How will the data be analyzed?

Storage and organization workflow

What storage solution(s) will be used? Is the solution appropriate for the type and size of data?

Does the storage solution provide an automatic backup, or will a backup storage method be needed?

How will version control of data and files be maintained?

Documentation and metadata

How will files be structured and labeled so the data may be easily reused or reproduced?

What metadata standards are commonly used in the project's discipline? How will these be applied to the project?

Data sharing and archiving

Are there any data sharing requirements or limitations from the funder, or stated within collaborative agreements?

For human subjects data, how will de-identification be ensured for all data?

How will the data be archived and is the archival solution appropriate for the types of data sets?

Funder specific data management plans

At Duke University there are a number of private and federal funders who provide support to research activities across the university. Increasingly, both federal funders and private funders are requiring Data Management Planning in some form or another as a required part of their research project funding.

The DMPTool can provide funder specific templates for use when creating plans. Otherwise, the Duke Office of Scientific Integrity or the Center for Data and Visualization Sciences (CDVS) can help with funder specific data management plans (see “Related Resources” section on this page). In addition, the DMPTool has a page listing out links to the individual funder requirements.