A Data Management plan (DMP) is normally a one- or two-page summary, outlining how data will be handled during a research project, and after it has been completed. The goal of a Data Management plan is to consider the many aspects of Data Management (such as data preservation, metadata generation, and analysis) before the project begins. It helps in managing the data and providing guidelines for the research team. Currently, a Data Management plan is needed to access grant funding. 

A Data Management plan allows grant funding agencies to review the plans and determine the potential value of the project. Many experienced project managers view Data Management plans as an “administrative exercise” needed to access the funding. Because most grant providers have little to do with a project after it has been funded, little energy goes into the plan’s maintenance and evolution after the grant money has been received. However, it continues to be a useful baseline for team members when managing the data, particularly in the early stages of the project. 

Data Management plans serve two purposes: providing team guidance on complex projects and offering funding suppliers with an additional tool for evaluating the potential of a project’s success. 

Originally, Data Management plans began being used in the 1960s to manage the data collection and analysis of large engineering and aeronautical projects. Its overall improvement in efficiency prompted the expanded use of Data Management plans across scientific and engineering disciplines during the 1970s and ’80s. 

Until the early 2000s, Data Management plans were routinely used for technically complicated projects. But in the 2010s, funding agencies began to increasingly require Data Management plans, regardless of the size or complexity of the project. 

Even small, technically simple projects require a Data Management plan to access grant funding.

A Data Management Plan for Funding

In many situations, the funding being sought is in the form of a grant. (Some banks may require a Data Management plan to evaluate the loan request. Some investors may also require a DMP.) 

Normally, part of the deal in accepting grant monies is a requirement that the project’s data be openly available to the public. This, in turn, promotes data sharing and the evolution of data science. Along with the other essential requirements used in grant applications, funders need applicants to submit a DMP to prove the data will be openly and easily available.

For funding purposes, the Data Management plan can be seen as a detailed supplementary document that describes the reasons for selecting certain formats, approaches, and standards for a project. While this is supposed to be a detailed document, a DMP submitted with a grant request cannot be more than two pages long. For funding, the purpose of the Data Management plan is to describe the types of data being produced, how it is managed, and its accessibility to other researchers.

Although considered a supplementary document, a good Data Management plan plays a key role in the acceptance of a grant proposal.

Some funding agencies will not even accept proposals that do not include a DMP. (Grant templates are available.) Data Management plans supporting the reuse of data by researchers beyond the project’s life are considered more valuable than projects supporting limited use of the data. Ideally, a DMP will answer the following questions:

• How will data be gathered or created?
• What types of data will the research generate?
• What formats and standards will be applied to the data and metadata?
• Who is responsible for ownership of the data?
• What are the plans for archiving and preserving the data (and other research products)?
• What policies exist that would restrict access and sharing of the data?

Tips for improving the odds of receiving a grant include:

• The use of popular or widely adopted formats to promote easy sharing and storage.
• Be sure to explain the expected data outputs.
• Describe the volume, format, content, and quality of the final dataset.
• Outline the use of metadata and documentation.
• Describe the methodologies and standards used to organize and manage the data.
• Provide credit to data sources while communicating its relationship to your data.

Grant applicants may need to include the following information in their proposals:

Data Description Section: A brief description of the data that has been gathered. This section should describe the amount of data that will be produced, and the types of data expected to be gathered and generated during the project (types of data text, software, spreadsheets, curriculum materials, images, 3D models, audio files, video files, surveys, assessment records, etc.). This section is also where research sources are cited and given credit.

Metadata and Formatting Section: Includes a description of the format supporting the data, as well as how it will be gathered, created, organized, maintained, and delivered. How will the metadata be made available? This section should also contain the reasons for selecting certain procedures and formats. (For example, “We chose to work with a Microsoft Word format because it is popular and compatible with our computer system.”) This section’s purpose is to establish that other researchers can access the results of your research. (This is also where any experimental procedures are described.)

Archiving and Preservation Section: Communicates the long-term strategy to be used in maintaining, organizing, and archiving the data. Storage methods, backup procedures, and the resources to retrieve data should be explained. Where the research data will be stored (archive, repository, or database names and addresses) should be included. This is also a good place to report on the procedures the long-term storage site uses to preserve the data, and how long the data will be accessible after the project’s completion. 

Security, Sharing, and Access Section: Contains the technical and procedural protections used for the data information, including confidential information. It explains how permissions, restrictions, etc., will be enforced. In addition, how and when the data will be available to access should be included. The following issues should be addressed in this section:

• The resources needed to make the data available
• The process used to gain access to the data
• Whether access to the data will require a fee
• The amount of time the principal investigator will retain usage rights, before the data becomes available to the public
• Details of issues caused by commercial, patent, or political restrictions
• A list of the federal and funding requirements needed for data sharing and its management

Ethics and Privacy: Discusses plans dealing with informed consent and privacy protection. This section should include the safeguards used in protecting the participant’s confidentiality, or any other ethical issues that may arise.

Intellectual Property Rights Section: The information listing individuals or entities holding the intellectual property rights for the data. The steps needed to protect copyright constraints and IP rights should be clearly explained.

Roles and Responsibility Section: Placing responsibility on specifically named individuals for the project is necessary. These individuals should play a meaningful role and be responsible for managing the data throughout the project. Information about naming conventions, version control, etc., should be placed in this section.

Budget Section: The budget section should not be confused with use of the grant monies. Financial support is necessary for conducting research. Applying for research grants, which includes presenting a budget, can be a challenging task. The funders typically feel it is important to know how the grant monies will be used.

A Data Management Plan for Team Communication

Using a Data Management plan for providing team guidance on complex projects does not need the same information or restrictions a DMP for funding requires. When used as a baseline of expectations for other team members, the Data Management plan need not be limited to two pages but can be made up of several pages.

As a communications tool for the team, the Data Management plan should be treated as a living document in a constant state of evolution. 

Developing a Data Management plan for a complicated project helps to organize the project, providing team members with the correct format and procedures, and if organized well, minimizes confusion. The various phases of the project can be described in detail. Goals and procedures can be established, team members selected, and data resources listed. By selecting an archive and storage format ahead of time, data can be formatted during the collection process. 

A good Data Management plan can help to identify the decisions needing to be made about the project’s data, in advance, streamlining the project as it moves toward completion.

Image used under license from Shutterstock.com