Research Data Management

Research data are:

• used as primary sources to support technical or scientific enquiry, research, scholarship, or artistic activity;
• used as evidence in the research process; and/or
• commonly accepted in the research community as necessary to validate research findings and results.

All other digital and nondigital content have the potential to become research data.

Research data may be experimental, observational, operational, third-party, public sector, monitoring, processed or repurposed data.

In explaining how they plan to manage a project’s research data, applicants should describe:

• how data will be collected, documented, formatted, protected and preserved;
• how existing datasets will be used, and what new data will be created over the course of the research project;
• whether and how data will be shared;
• where data will be deposited for long-term preservation;
• the research team’s data-related roles and responsibilities;
• the ethical, legal and commercial constraints to which the data are subject; and
• methodological considerations that support or preclude data sharing.

Those doing research by and with First Nations, Métis and Inuit communities, collectives and organizations must co-develop their research data management with those parties in accordance with research data management principles or approaches the parties accept.

Projects undertaken in the context of research by and with First Nations, Métis and Inuit communities, collectives and organizations should recognize Indigenous data sovereignty, and should include options for revising how data will be managed.

NFRF grant recipients are not required to openly share their project’s research data. However, the federal research granting agencies believe research data should, to the fullest extent possible, be managed following the FAIR Principles. The FAIR Principles provide guidelines to improve the findability, accessibility, interoperability and reuse of digital assets as follows:

• Findable: Data and supplementary materials are described with sufficiently rich metadata and assigned a unique and persistent identifier.
• Accessible: Metadata and data are understandable to humans and machines. Data is deposited in a trusted repository.
• Interoperable: Metadata use formal, accessible, shared and broadly applicable language to represent knowledge.
• Reusable: Data and collections have clear usage licenses, and provide accurate information about their provenance.

For more information on research data management, see the Tri-Agency Statement of Principles on Digital Data Management.