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Research Data Management


A Data Management Plan (DMP) is a living document that outlines how you plan to manage your data from the beginning to end of your research project.

Funding Agency Requirements

In March 2021, Canada’s federal granting agencies — the Canadian Institutes of Health Research (CIHR), the Natural Sciences and Engineering Research Council of Canada (NSERC) and the Social Sciences and Humanities Research Council of Canada (SSHRC) — launched the Tri-Agency Research Data Management (RDM) Policy.

In Spring 2022 the Agencies announced the initial funding opportunities that will require applicants to submit Data Management Plans (DMPs):


  • Network Grants in Skin Health and Muscular Dystrophy (Anticipated launch fall 2022 or early winter 2023)
  • Virtual Care/Digital Health Team Grants (Anticipated launch fall 2022 or early winter 2023)
  • Data Science for Equity (Anticipated launch fall 2022 or early winter 2023)


  • Subatomic Physics Discovery Grants - Individual and Project (Anticipated launch summer 2023)


  • Partnership Grants Stage 2 (Anticipated launch summer 2023)

The agencies are collaborating with stakeholders to co-develop resources to support applicants in preparing DMPs. Information about these resources will be provided when the funding opportunities are launched. The agencies are also exploring approaches to DMP assessment. Details on how DMPs will be considered in the adjudication process, as well as resources to support assessment of DMPs, will be provided when the funding opportunities are launched.

Update from the Tri-Agencies:

Data Management Checklist

Data Management Checklist*

Reviewing the questions and concepts outlined below will help you think about important issues related to data management.

  • Data Collection
    • What type(s) of data will be produced?
    • What file format(s) will the data be saved as? Are those file formats proprietary? Will they degrade?
    • Will the data be reproducible?
    • Do you need tools or software to create/process/visualize the data?
    • How much data? 
    • Will it grow?
    • How often will it change?
  • Documentation & Metadata
    • Think about what is needed to make your data 'independently understandable'
    • How will you capture this information over the life of the project?
    • What directory and file naming conventions will be used?
    • Is there a descriptive schema or metadata standard commonly used in your field?
  • Storage & Backup
    • What are the strategies for storage and backup of the data?
    • Use the '3-2-1 Rule': 3 copies, 2 formats, and at least 1 off-site copy
    • Are you aware of backup options at TMU?
  • Preservation
    • Think about preservation-friendly, non-proprietary formats.
    • Where will you deposit your data for long-term preservation and access?
  • Sharing & Reuse
    • Think about what data you'll be sharing (raw data, processed data...)
    • Consider what end-user license you might use.
    • How will others learn about your data?
  • Responsibilities & Resources
    • Who in your research group will be responsible for data management?
    • Who controls the data (PI, student, lab, funder)?
    • What resources are required to manage your data?
  • Ethics & Legal Compliance
    • Consider how you'll store and transfer sensitive data securely.
    • Consider how you'll manage secondary use of sensitive data.
    • Can a 'public' (anonymized, de-identified) version of your data be created?
    • How will you manage legal, ethical, and intellectual property issues?

*Copied with permission from Queen's University Library's RDM Libguide.

Data Collection

What file formats will your data be collected in? Will these formats allow for data re-use, sharing and long-term access to the data?

What conventions and procedures will you use to structure, name and version-control your files to help you and others better understand how your data are organized?

Storage and Backup

How and where will your data be stored and backed up during your research project?

Sharing and Reuse

Have you considered what type of end-user license to include with your data?

What steps will be taken to help the research community know that your data exists?

Ethics and Legal Compliance

If your research project includes sensitive data, how will you ensure that it is securely managed and accessible only to approved members of the project?

If applicable, what strategies will you undertake to address secondary uses of sensitive data?

How will you manage legal, ethical, and intellectual property issues?