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Research Data Management

This guide contains information about research data management and best practices for faculty, researchers and graduate students

Data Management Plans

Before beginning a research project, it is critical to have a clearly written data management plan (DMP). Most funding agencies require grant proposals to include a DMP that clearly outlines how the researcher will collect, manage, organize, preserve and distribute the research data that they will be generating during the study. Each funding agency has its own set of requirements for DMPs, so identify all elements that need to be addressed for a DMP for that specific agency before writing the plan. You may use free, web-based tools such as DMPTool that helps you construct data management plans using templates that address specific funder requirements.

Core elements of a Data Management Plan will include answers to the following questions:

  1.  Project, experiment, and data description
    • What’s the purpose of the research?
    • What is the data? How and in what format will the data be collected? Is it numerical data, image data, text sequences, or modeling data?
    • How much data will be generated for this research?
    • How long will the data be collected and how often will it change?
    • Are you using data that someone else produced? If so, where is it from?
    • Who is responsible for managing the data? Who will ensure that the data management plan is carried out?
  2. Documentation, organization, and storage
    • What documentation will you be creating in order to make the data understandable by other researchers?
    • Are you using metadata that is standard to your field? How will the metadata be managed and stored?
    • What file formats will be used? Do these formats conform to an open standard and/or are they proprietary?
    • Are you using a file format that is standard to your field? If not, how will you document the alternative you are using?
    • What directory and file naming convention will be used?
    • What are your local storage and backup procedures? Will this data require secure storage?
    • What tools or software are required to read or view the data?
  3. Access, sharing, and re-use
    • Who has the right to manage this data? Is it the responsibility of the PI, student, lab, MIT, or funding agency?
    • What data will be shared, when, and how?
    • Does sharing the data raise privacy, ethical, or confidentiality concerns?  Do you have a plan to protect or anonymize data, if needed?
    • Who holds intellectual property rights for the data and other information created by the project? Will any copyrighted or licensed material be used? Do you have permission to use/disseminate this material?
    • Are there any patent- or technology-licensing-related restrictions on data sharing associated with this grant?
    • Will this research be published in a journal that requires the underlying data to accompany articles?
    • Will there be any embargoes on the data?
    • Will you permit re-use, redistribution, or the creation of new tools, services, data sets, or products (derivatives)? Will commercial use be allowed?
  4. Archiving
    • How will you be archiving the data? Will you be storing it in an archive or repository for long-term access? If not, how will you preserve access to the data?
    • Is a discipline-specific repository available? If not, you could consider depositing your data into Rowan Digital Works (RDW). Email the Library's Institutional Repository team at for more information.
    • How will you prepare data for preservation or data sharing? Will the data need to be anonymized or converted to more stable file formats?
    • Are software or tools needed to use the data? Will these be archived?
    • How long should the data be retained? 3-5 years, 10 years, or forever?

[Credit: Text for questions for DMP from MIT Libraries]

DMP Resources and Guides