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Research Data Management

What is Research Data Management?

  • Research data management (RDM) is a set of practices that guide the storage, access, and preservation of research data throughout a research project. It covers the entire research project lifecycle, from drafting the research plan, to implementing it and sharing research data after a project finishes. 
  • This webpage provides information and resources on RDM, including York University’s RDM strategy, data management plans, and depositing research data into trusted repositories, such as York University’s Dataverse, York’s institutional research data repository.

Getting Help

  • Email yul_rdm@yorku.ca to book a consultation or receive email support from the Libraries’ research data management team. 

Research Data Management Strategy Development at York 

In March 2021, Canada’s federal granting agencies launched the Tri-Agency Research Data Management (RDM) Policy. The Tri-Agency policy includes requirements related to institutional research data management (RDM) strategies, data management plans (DMPs), and data deposit. The Open Access Open Data Steering Committee conducted university-wide consultations in 2022-2023 to develop an RDM strategy for York University. The committee also created an FAQ about the university’s RDM strategy.  

Creating a Research Data Management Plan   

In 2023, the Tri-Agency began requiring specific grant applications include a data management plan (DMP) in their application packages. The list of Tri-Agency grants requiring a DMP during the application stage is available on the Tri-Agency's website.  

Do you need to create a data management plan for your grant application or research project? Consult the following resources: 

  • Check out our webpage on creating DMPs 
  • Create an account with the DMP Assistant Tool: a nationally-endorsed tool for effective data stewardship. It assists researchers in developing a DMP by providing access to templates that include key data management questions, supported by best-practice guidance, and examples. 

Share your Research Data 

York University Dataverse is our institutional research data repository and is part of Borealis: The Canadian Dataverse Repository. Borealis is a bilingual, multidisciplinary, secure, Canadian research data repository, supported by academic libraries and research institutions across Canada. 

To deposit data in York University Dataverse, please review the instructions listed in the following guides: 

To learn more about York University Dataverse, please consult our data deposit guidelines and collections policy: 

To learn more about discipline-specific and other data repositories, the Libraries have curated the following list of suggestions.  

Please contact the Libraries’ RDM team (yul_rdm@yorku.ca) if you have any questions about RDM, creating a DMP, or depositing research data. 

Upcoming Workshops 

  • Register for York University Libraries’ workshops: RDM workshops typically take place in the Fall and Winter semesters. 
  • Use the Explora platform to find Digital Research Alliance of Canada-supported training opportunities covering essential topics such as advanced research computing (ARC), research data management (RDM), and research software (RS). 

Frequently Asked Questions  

CODATA’s Research Data Management Glossary defines “Research Data” as sources and evidence that are needed to support and validate findings of scientific enquiry, research scholarship, and artistic activities. There are many different types of research data: experimental data, observational data, operational data, third party data, public sector data, monitoring data, processed data, or repurposed data. 

Research data management (RDM) provides guidelines on the storage, access, and preservation of research data throughout a research project. It covers the entire research project lifecycle, from drafting the research plan, to implementing it and beyond. RDM outlines terms regarding the subsequent deposit of the data with a data repository for sharing long-term management and preservation. 

Want to learn more about the basics of research data management? Consult the Introduction to Research Data Management textbook and the Research Data Management in the Canadian Context: A Guide for Practitioners and Learners textbook. 

A data management plan (DMP) is a formal statement describing how research data will be managed, documented, and preserved during the research process and once the project is completed. Data management planning is an international best practice which supports the responsible conduct of research and respects the disciplinary norms inherent in how research is conducted in various fields. Planning early for each stage of the data life cycle will help researchers identify opportunities and anticipate issues earlier, and it will prepare researchers for addressing potential challenges in a holistic and systematic fashion. 

To begin drafting a DMP, researchers should: 

Need help getting started on your data management plan? Contact the libraries at yul_rdm@yorku.ca to schedule a consultation. 

Research data are often shared: 

  • to meet funding agency requirements; 
  • to meet journal data policy requirements; 
  • to publish data as a scholarly product according to the FAIR principles; or 
  • to adopt open science practices: increasing research accountability, reproducibility, open engagement and reducing duplication. 

Balancing data sharing requirements with common directives for research ethics and confidentiality can be achieved through careful data management planning. To consider your options for sharing data, consult the following resources: 

Risk and Security Guidelines:

Once it is determined that research data can be shared, researchers need to choose a trusted repository for data sharing and preservation. A number of commercial and not-for-profit generalist repositories exist for research data. 

A disciplinary data repository can be the best option for data to be properly catalogued and discovered by users in your discipline. You can consult the re3data directory and browse by discipline to generate a potential data repository list for your project. 

Canadian researchers also have two national research data repositories they can use to deposit their data: 

Borealis, the Canadian Dataverse Repository, is a bilingual, multidisciplinary, secure, Canadian research data repository, supported by academic libraries and research institutions across Canada. Borealis supports open discovery, management, sharing, and preservation of Canadian research data. Users can create robust metadata, track changes across versions of their datasets, mint Digital Object Identifiers (DOIs), and make data open or restricted. 

The Federated Research Data Repository (FRDR) is a platform for sharing open and large data sets as well as a national data discovery engine. 

Researchers can learn more about repository choices using the following guides: 

Have questions about your data repository options? Contact us at yul_rdm@yorku.ca.

York University Dataverse is the main institutional data repository supported by the Libraries. 

To deposit data with Dataverse, please follow the instructions listed in this guide: 
Depositing Data in the York University Dataverse: A Quick Guide (PDF) 

For more information on best practices for depositing research data, consult the below guides:

Research communities and research data stewards are developing principles to guide the practices of RDM. The FAIR (Findable, Accessible, Interoperable, Reusable) Principle has been adopted by many research data stakeholders across research domains. Researchers can assess the FAIRness of their research data using tools such as FAIR-Aware. More recently, the Global Indigenous Data Alliance has also developed the CARE Principles for Indigenous Data Governance in order to reinforce Indigenous Peoples’ rights to engage in RDM decision-making in accordance with Indigenous values and collective interests. 

To explore active storage options for your research data, you can consult the below resources: