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Research Data Management for Health Sciences

Use this checklist to address components required in many data management plans and optimize your research work flow.

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?

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?

Access, sharing, and re-use

  • Who has the right to manage this data? Is it the responsibility of the PI, student, lab, UW, 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?


  • 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 Minds@UW.
  • 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?