Share & Reuse Data

Data Sharing Policies and Practices in Canada

Funding agencies and governments around the world have recognized the need for national RDM policies to support access to publicly funded data. The Canadian Tri-Agency RDM Policy (2021) is driving a culture change for data deposit and sharing, as it outlines requirements for researchers to “deposit into a digital repository all research data, metadata and code that directly support the research conclusions in journal publications and pre-prints that arise from agency-supported research” (Government of Canada, 2021). Grant recipients are expected to provide access to their data in accordance with the FAIR principles and disciplinary standards while respecting ethical, cultural, legal, and commercial requirements. Indigenous data sovereignty recognizes the inherent rights of Indigenous communities to govern the collection, ownership, and use of their data and may result in distinct practices regarding the sharing of research data.

Tri-Agency RDM Policy (2021)

  • Grant applicants must include a Data Management Plan for certain funding applications (phased implementation beginning in spring 2022)
  • Grant recipients should deposit into a digital repository all research data, metadata, and code that directly support the research conclusions in journal publications and pre-prints that arise from agency-supported research. Deposit will be expected at the time of publication (implementation forthcoming).
  • Although sharing data is not required, the Agencies expect researchers to provide appropriate access to the data where ethical, cultural, legal, and commercial requirements allow and in accordance with the FAIR principles and the standards of their disciplines.​ Whenever possible, these data, metadata, and code should be linked to the publication with a persistent identifier (PID).

Tri-Agency Statement of Principles on Digital Data Management (2016)

  • Data should be collected and stored using software and formats that ensure secure storage, preservation of, and access to the data beyond the duration of the research project.

Tri-Agency Open Access Policy on Publications (2015)

  • Researchers funded by the Canadian Institute of Health Research (CIHR) should deposit specific types of data (e.g., bioinformatics) into an appropriate public database.

SSHRC Research Data Archiving Policy (1990)

  • Research data must be preserved and made available for use within two years of project completion (Government of Canada, 2016).

Considerations for Data Sharing

Data sharing requires planning. At the project outset, as part of a Data Management Plan, researchers must consider software and tools needed to collect, analyze, and document data; appropriate storage and backup procedures; how data will be deposited and (if possible) shared; and how they will manage data to ensure ethical and legal requirements are met.

Disciplinary differences, including attitude and culture, can influence data sharing and reuse. Certain research fields have traditions of data sharing and reuse and have adopted standards and tools to support this work. Especially within the humanities, where outputs do not always fit within traditional definitions for research data, researchers may consider different approaches to encourage sharing. Services and tools are often developed with disciplinary needs in mind and may be difficult to adopt or repurpose for other disciplines or contexts. Although general tools and services can help, they often lack disciplinary context that would make reuse and adoption possible. Other disciplinary considerations include the following:

  • file formats (open vs. proprietary, standard tools and software within the discipline)
  • metadata standards for documentation and dataset discovery
  • active data storage, data transfer tools, and repository storage to support disciplinary needs (e.g., big data, sensitive data)
  • repository selection based on features and user community
  • availability of data curation support:
  • data quality review
  • data documentation for reuse
  • data transformation (e.g., cleanup, anonymization, de-identification)
  • terms of access and licensing for reuse
  • data exploration and visualization tools
  • the benefits of sharing different types of data

Adapted from Research Data Management in the Canadian Context edited by Kristi Thompson; Elizabeth Hill; Emily Carlisle-Johnston; Danielle Dennie; and Émilie Fortin, which is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.