Research Data Management
Best Practices for Research Data Management
Research Data Management (RDM) refers to the processes and actions throughout a project which guide the collection, analysis, storage, sharing, and preservation of research data. Effective RDM supports data quality, security, integrity, and reuse.
Because data types, methodologies, and disciplinary requirements vary, researchers should develop a Data Management Plan (DMP) early in a project to guide decision-making throughout the research lifecycle. Datasets and supporting documentation should be appropriately retained, shared, deposited, and preserved to maximize the value, transparency, and long-term impact of research investments.
Data Management Plans
A Data Management Plan (DMP) is a short, formal document that outline what will be done with research data during and after the project. Many funders require a DMP as part of the application process.
Tri-Agencies
Harmonized guidance and resources for writing data management plans for Canadian Institutes for Health Research (CIHR), Natural Sciences and Engineering Research Council of Canada (NSERC), and Social Sciences and Humanities Research Council of Canada (SSHRC) funding applications.
Digital Research Alliance of Canada
A free bilingual tool for creating, maintaining, and sharing data management plans.
University of Toronto Libraries
A practical guide to writing data management plans, including requirements, examples, and planning tools.
McMaster University
A searchable collection of data management plan examples from funders and institutions around the world.
Finding and Reusing Data
When reusing data, follow applicable access conditions and licensing requirements, and cite the dataset.
University of Toronto Libraries
A collection of datasets available for reuse, including geospatial, quantitative, maps and atlases, and textual and qualitative datasets.
Digital Research Alliance of Canada
A national discovery platform that allows researchers to search for datasets across Canadian institutional, governmental, and disciplinary repositories.
Institutional Research & Data Governance
University of Toronto
Researchers can apply for access to institutional data or data subject contact information for approved academic research purposes.
The Data Sciences Institute
University of Toronto
Grants that help researchers cover the costs of accessing and working with large datasets required for data-intensive research.
Statistics Canada
Research Data Centre
Provides secure access to detailed Statistics Canada microdata and administrative datasets for approved research projects.
Active Data Storage, Data Retention and Data Preservation
Research data requires different storage approaches throughout the research lifecycle. Active data storage supports data that is being regularly collected, accessed, or modified during a project, while data retention involves keeping research data for a defined period after a project ends. Data preservation supports long-term access to research data, but not all data is suitable for long-term preservation.
Enterprise Applications and Solutions Integration
University of Toronto Libraries
A guide to the differences between data retention and preservation, including additional resources for further guidance.
University of Toronto Libraries
Support, training, and consultation services for digital preservation planning, workflows, and recovery strategies.
Data Deposit, Data Sharing and Data Availability
Research data may be deposited, shared, and made available beyond the original research team. These practices support transparency, validation, and the long-term value of research outputs.
Depositing Research Data and Choosing a Data Repository
Data deposit is the process of transferring custodianship of research data to a third-party, such as a research data repository. Data deposit is not the same as sharing. You may choose a repository that allows open sharing, restricted access or one that preserves long-term access.
Repositories are platforms that hold data, organize it in a logical way, and can make it available for reuse. Repositories are typically institutional, generalist, or discipline-specific; selection will depend on the discipline, the data type and size, and the data sensitivity; some data cannot be deposited.
University of Toronto Libraries
A step-by-step guide for preparing research data and documentation for deposit and reuse, including README templates.
University of Toronto Libraries
An overview of repository options and key considerations for selecting an appropriate repository for research data including data licensing, funder or journal requirements, and the ability to update datasets.
A searchable registry of research data repositories that helps researchers identify repositories based on discipline, repository type, and other selection criteria.
University of Toronto Libraries
The institutional data repository accepts all types of research data for research conducted under the auspices of U of T. Provides secure long-term sharing and preservation but is not currently suitable for sensitive data and has file size limitations.
Digital Research Alliance of Canada
A national platform for sharing, discovering, and depositing research datasets produced across Canada.
Data Sharing, Data Availability and Data Availability Statements
Data sharing means making your research data available to others. Data availability focuses on how research data can be discovered and accessed. Researchers should consider how access will be provided and any restrictions that apply. Data availability statements communicate this information by describing whether data are available and how access can be obtained.
Creative Commons
An interactive tool that helps researchers select an appropriate licence for sharing datasets and other research outputs.
Digital Research Alliance of Canada
Guidance on preparing clear and informative data availability statements for publications.
Guidance and Considerations for Research Data Management
Expand for further guidance and resources.
Determine the sensitivity of your research data before selecting storage, sharing, retention, and preservation approaches.
Information Security
University of Toronto
Groups the university’s data into four levels based on importance, sensitivity and potential for misuse. Researchers can use this standard to determine the sensitivity of their data and the safeguards required to protect it.
Information Security
University of Toronto
A tool that helps researchers determine the appropriate data classification level using research-specific examples.
Ensure research data management practices comply with applicable ethics approvals, agreements, and confidentiality obligations.
Division of the Vice-President, Research & Innovation
University of Toronto
Guidance on when research requires Research Ethics Board (REB) approval and how to obtain ethics clearance for studies involving human participants.
Division of the Vice-President, Research & Innovation
University of Toronto
Information on research agreements and contracts that may be required when sharing data or collaborating with external partners.
Division of the Vice-President, Research & Innovation
University of Toronto
Guidance on the retention, protection, and secure destruction of confidential and personally identifiable information used in research.
Consider export control and data transfer requirements before moving research data across international borders.
Division of the Vice-President, Research & Innovation
University of Toronto
Guidance on Canadian export control requirements and when restrictions may apply to research data, technology, materials, or international collaborations.
Review and comply with funder requirements for data management, retention, sharing, and deposit.
Tri-Agencies
Outlines Tri-Agency requirements for institutional research data management strategies, data management plans, and research data sharing and deposit.
Tri-Agencies
Provides proposed guidance on the Tri-Agency data deposit requirement and emerging expectations for research data stewardship, including a proposed 5-year retention period for research data post-award, and when appropriate, to deposit research data that directly supports findings for preprints and peer-reviewed articles. Deposited data should be made as open as possible where ethical, cultural, legal and commercial requirements allow, and a data availability statement should be included in publications. Finalized requirements are expected to be announced in early 2027, with an anticipated implementation date of 2028 (pending approval).
University of Toronto
Outlines the University’s commitment to responsible research data management and the institutional supports available to researchers across the research lifecycle.
Training and Resources on Research Data Management
Explore learning resources and recorded sessions related to research data management.
Workshops & Courses
- What Is a Data Management Plan and Why Do I Need One? (CRIS)
October 20, 2026
Introduces the purpose of DMPs, common components, and available support resources. - Explora (Digital Research Alliance of Canada)
A national portal that aggregates training materials, courses, and events from Digital Research Alliance partner institutions.
Documentation and Guides
- Research Data Management Guide (University of Toronto Libraries)
A comprehensive guide to research data management practices, tools, and resources across the research lifecycle. Includes guidance on organizing research data, and data sharing. - Information Security Handbook (Information Security)
Includes guidance on file naming conventions, data integrity, best practice to secure systems and environments, deleting or destroying data and devices, and developing a backup strategy. - De-identification Guidelines for Structured Data (Information and Privacy Commissioner of Ontario)
Practical guidance on reducing re-identification risks while preserving the usefulness of structured datasets. - De-Identification Guide (University of Toronto Libraries)
Resources and guidance to support the development of data de-identification strategies for research involving human participants.
Recorded Webinars
- What Is a Data Management Plan and Why Do I Need One? (CRIS)
Introduces the purpose of DMPs, common components, and available support resources. - Depositing Research in U of T Dataverse (Borealis) (UTL)
Demonstrates the process of publishing a dataset on U of T Dataverse. - Community Research Data Toolkit (CRIS)
Explores collaborative approaches to research data management and community-engaged research practices.
Get Support for Research Data Management
- DMPs, data retention and deposit, repository selection: rdm@utoronto.ca
- Research cybersecurity consultation: research.infosec@utoronto.ca
- Copyright and licensed data considerations: scco@library.utoronto.ca
- Terms of use for institutionally licensed data: mdl@library.utoronto.ca
- Digital preservation: digipres@library.utoronto.ca