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Research Data Management: Data Management Plans

Why DMPs?

Why create a Data Management Plan?

  • Meet funding requirements
  • Ensure your data is complete and documented
  • Ensure your data is accessible to researcheres in the future
  • To save you time and frustration
  • To raise the profile of your research

Data Management Plans

Data Management Plans (DMPs) are brief documents that outline the important information about how your data will be created, organized, stored, managed and preserved. In addition, DMPs outline how existing datasets may be used in your research and what new data will be created. They ensure that issues are thought of and planned for prior to the implementation of a new research project. 

Many funding agencies now require that data management plans be included in grant applications, and those that do not yet require the use of DMPs, strongly encourage them. 

Data Management Plans promote excellence in data management and stewardship. 

Elements of DMPs

There are many things to think about when you begin a research project. Data should be one of those things. If you plan ahead and try to anticipate issues with the collection, organization and storage of your data, you will save a great deal of time and frustration. You will not always be required to have a data management plan, but they need not be complicated or long and it is a good idea to have at least a basic plan. Here are the elements normally included in a data management plan and some questions to think about when planning for data management.

 

Data Production

  • What type(s) of data will be produced?
  • What file format(s) will the data be saved as? Are they proprietary? Will they degrade?
  • Will the data be reproducible?
  • Do you need tools or software to create, process, or visualize the data?

Data Size

  • How much data will it be, and at what growth?
  • How often will it change?

Data Usage

  • Who will potentially be using your data both now and later?

Data Retention

  • How long should it be retained? (e.g. 3-5 years, 10-20 years, permanently)

Privacy and Security

  • Any special privacy or security requirements? e.g., personal data, high-security data

Data Sharing

  • Any sharing requirements? e.g., funder data sharing policy
  • Have you chosen a repository in which to archive your data?

DMP required?

  • Does your funding agency require a data management plan in the grant proposal?

Data Documentation

  • How will you be documenting your data and project?
  • What directory and file naming convention will be used?
  • What project and data identifiers will be assigned?
  • Is there a schema, ontological, or other metadata standard in your field for sharing data with others?

Storage and Backup

  • What are the strategies for storage and backup of the data?

Publication

  • When and where will the work be published?

Responsibility

  • Who in the research group will be responsible for data management?
  • Who controls the data (PI, student, lab, funder)?

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