Research Data Management Institutional Strategy

Executive summary

In March 2021, the Tri-Agency adopted a policy on research data management (RDM). The policy requires each post-secondary institution and research hospital eligible to administer Tri-Agency funds to create an institutional RDM strategy, publicly post the strategy and notify the agencies when completed. In response to the release of the Tri-Agency Research Data Management Policy (2021), Queen’s University established a working group and created this strategy to support researchers and research staff and promote the use of wise and responsible research data management practices.

To support the adoption of our institutional strategy and enhance the use of wise practices in RDM, Queen’s will engage in awareness-raising activities, hire and train staff, promote RDM wise practices, and provide or support access to RDM tools, resources, and infrastructure.

Queen’s is in compliance with Tri-Agency requirements. The strategy is posted and is a living document that will be updated at regular intervals.

For more information, please visit the main RDM page.

Introduction

Well-managed research data* is recognized as an international best practice, as contributing to the reach and impact of research. In March 2021, the Tri-Agency adopted a policy on RDM. The policy requires each post-secondary institution and research hospital eligible to administer CIHR, NSERC or SSHRC funds to create an institutional RDM strategy and notify the agencies when it has been completed. The strategy must be made publicly available on the institution’s website with appropriate contact information on who is going to administer the strategy. Data management plans (DMPs) and data deposit are two additional elements identified in the policy and are increasingly required for funding applications or journal submissions. In addition, best practices to help safeguard your research according to the National Security Guidelines for Research Partnerships includes ensuring sound research data management practices.

Queen’s created the Research Data Management Implementation Committee (RDMIC) in Spring 2021 to govern development and implementation activities. As a first step, the RDMIC created a shared vision for RDM at Queen’s. The vision is as follows:

Queen’s goal is to provide a range of clear and accessible tools, technologies, and support services to meet the needs of researchers throughout the research data life cycle. Our research-centered approach means we will promote wise practices around data management planning and data deposit, permitted uses, preservation, and disposal. Our aim is to identify pathways to research data management, to build on areas of strength and expertise, and to improve on tools, technologies and service supports that allow Queen's researchers to enhance research excellence and adapt to the research environment.  

Importance of research data and research data management

Queen’s values the safe and secure management of research data. Sound data management is part of best practices to discovery-driven and partner-based research. Queen’s values open communication of research, embracing the exchange of ideas at the local, provincial, national, and international level. Queen’s values the production of Canadian intellectual property for the betterment of society, as well as a safe and secure research environment for their research community. It is these values that form the foundation for our desire to support our researchers in sound data creation, deposit, storage and sharing, when practical and possible, in all forms and in all disciplines.

 

Guiding principles

Queen’s commits to the use of data management practices that enhance the stewardship and ethical use of research funds. According to the Tri-Agency (2021), sound RDM practices support research excellence by “ensuring that research is performed ethically and makes good use of public funds, experiments and studies are replicable, and research results are as accessible as possible. Research data management (RDM) is a necessary part of research excellence” (Tri-agency RDM Policy, Government of Canada). Research excellence is founded on equity and diversity, advances knowledge mobilization and strengthens global impact.

Aligned with Queen’s Strategic Goals 1 and 3

Queen’s supports its researchers in the implementation of good RDM practices through the coordination of existing tools, technologies and service supports and by addressing any areas of need. Queen’s respects the use of diverse approaches reflective of various disciplines, research activities and projects.

Aligned with Queen’s Strategic Goals 5 and 6

Queen’s encourages collaborative ventures in research. The use of wise data management practices supports respectful and mutually beneficial research relations with government, not-for-profits, community-based actors, and the private sector. 

Aligned with Queen’s Strategic Goal 5

Research results should be made as open as possible, and as closed as necessary, to facilitate access and reuse. This requires a commitment to the inclusive use of data management practices, such as the FAIR Guiding Principles for data management and stewardship, which strive to make data Findable, Accessible, Interoperable and Reusable. 

Aligned Queen’s Strategic Goals 1 and 4

Queen’s acknowledges that Indigenous peoples have the right to control the collection, ownership and application of Indigenous data and encourages the use of data management practices, such as the OCAP and CARE Principles to support data sovereignty.

Aligned with Queen’s Strategic Goals 4 and 5

Queen’s respects the privacy, security, ethical considerations, and appropriate confidentiality provisions of its researchers. Queen’s complies with relevant legal and commercial obligations, supporting researchers with legal advice on data management considerations with legal implications.

Aligned with Queen’s Strategic Goal 1

Scope

This strategy applies to all Queen’s researchers, including students, staff, and faculty in all disciplines, at the University. Our initial focus will be to ensure that our Tri-Agency-funded researchers have the tools, technologies and service supports in place to aid their work and demonstrate good research data management as they will lead this transition in RDM best practices.

Oversight and review

Dr. Brian Amsden, Associate Vice-Principal Research, will oversee the implementation of the strategy. Dr. Amsden is supported by a team, including staff in the Vice-Principal Research Portfolio (VPR) and in partnership with the Implementation Committee (see "Stakeholders” section and Appendix B for membership).

The Implementation Committee meets quarterly to discuss progress and for an annual review of the strategy, which will be presented to the VPR executive team.

Stakeholders

Success in research data management at Queen’s requires collaboration across several units on campus. Representation on the RDMIC includes, but is not limited to, the Queen’s University Library, Information Technology Services, the Centre for Advanced Computing, Research Services, Research Legal Services, Kingston Health Sciences Centre (i.e., Kingston General Hospital, Hotel Dieu Hospital and Province Care Hospital), and the Privacy Office.

For a full list of RDMIC members, please see Appendix B. A clear description of institutional and research community responsibilities is provided in the Tri-Agency RDM Policy and is summarized below.

As an institution, we at Queen’s are responsible for:

  • Acknowledging the importance of research data management;
  • Providing guidance to the research community that aligns with Tri-Agency Policies and Statements, including the Tri-Agency Statement of Principles on Digital Data Management;
  • Adhering to wise practices for developing standards, policies, strategies, and documents for data management plans; and
  • Supporting access to, or provide, platforms and services to securely deposit, curate and access research data.

As members of the research community (i.e., researchers and research staff), we are responsible for:

  • Preparing, submitting and maintaining data management plans that align with wise practices for the management of data throughout the project lifecycle; and
  • Depositing into a digital repository, all research data, metadata, and code that directly support research conclusions, providing appropriate access to the data where ethical, cultural, legal, and commercial requirements allow.

Institutional support

To support the adoption of our institutional strategy and enhance the use of wise practices in RDM among researchers, Queen’s will engage in awareness-raising activities, hire and train staff, promote RDM wise practices, and provide or support access to RDM tools, resources, and infrastructure. The RDMIC will oversee and coordinate the following institutional supports:

A communications strategy and a dedicated VPR-based RDM webpage; consultation and engagement sessions (e.g., surveys, focus groups), the Resources for Researchers series (R4R) commits to RDM-specific sessions; an instructional video series will provide information on RDM wise practices (in development); there has been wide dissemination of RDM policy requirements across the University, for example in reports to Senate.

The University has hired staff to support institutional excellence in RDM: a project officer, a member of the VPR staff, was hired in 2021; an application to a Queen’s-based experiential learning program for an under/graduate student intern will be submitted for RDM-specific work, such as facilitating outreach activities. Additional staffing requirements and professional development opportunities to build expertise will be evaluated as needed.

Internal Resources

  • Queen’s University Library in Borealis, the Canadian Dataverse Repository;
  • The Centre for Advanced Computing provides digital research infrastructure tools and services, including secure, highly available and high-performance compute resources and support services, such as storage, data capture, data analytics, application development, consultation, training, and more;
  • In terms of Indigenous research-specific resources, researchers have access to the Indigenous Community Research Partnerships provide researchers with unique and rich opportunities on Indigenous research with sessions on data governance.
  • Queen’s has developed an online resource addressing the integration of EDII in Research. The third module highlights EDII considerations in data management.
  • The Queen's Data Champions, a collaboration of the VPR Portfolio, the Library, the CAC, and Information Technology Services, received funding from the Digital Research Alliance of Canada to support the collaborative development of outreach events, training materials, and a community of practice around RDM. The RDMIC will continue the build on the RDM information and materials produced by the Queen’s Data Champions in response to Queen's researcher needs.

External Resources

  • The Digital Research Alliance of Canada offers the DMP Assistant, a national tool available to all researchers, to facilitate the development of a DMP through a series of questions and best-practice guidance and examples;
  • The Digital Research Alliance of Canada provides Lunaris a discovery tool for Canadian research datasets, including those deposited into Borealis.

Ethical, legal and commercial considerations

The institution supports researchers in adopting and complying with ethical, legal, and commercial obligations through various channels:

Equity, Diversity, Inclusion, and Indigenization in Research

I-EDIAA is an important concept in research, and consideration of I-EDIAA principles supports excellence and impact in research and ensures that all researchers see themselves reflected in the research community.

Queen’s is primed to provide support in the area of I-EDIAA. For example, the joint VPR, Human Rights and Equity Office (2022) provide researchers with important information specific to research design, practice and dissemination.

As a signatory of the Scarborough Charter, Queen’s is committed to anti-Black racism and Black inclusion in higher education. The Scarborough Charter identifies research as one of four broad implementation themes, and the Queen’s research working group works to consider the meaningful inclusion of Black scholars in the research environment with an aim to augment representation in this sphere.

Queen’s recognizes that a distinctions-based approach is needed to ensure that the unique rights, interests and circumstances of the First Nations, Métis and Inuit are acknowledged, affirmed, and implemented (Tri-Agency RDM Policy, Government of Canada 2021). The Office of Indigenous Initiatives.

As a result of this and other work, considerable steps have been taken to advance tenants 18 through 20 of the Yakwanastahentéha Aankenjigemi Extending the Rafters: Truth and Reconciliation Commission Task Force Final Report (2017). 

*Chapter 9 of the Tri-Council Policy Statement: Ethical Conduct for Research Involving Humans (2018) details considerations for research with and by Indigenous Peoples.

** Kirkness, V. J. and R. Barnhardt (2001). First Nations and Higher Education: The Four R's - Respect, Relevance, Reciprocity, Responsibility. Knowledge Across Cultures: A Contribution to Dialogue Among Civilizations. R. Hayoe and J. Pan. Hong Kong, Comparative Education Research Centre, The University of Hong Kong.

Implementation

This document guides the implementation of the RDM Policy at Queen’s. Priorities and specific goals and objectives were co-developed by members of the RDMIC, the research community and the Queen’s Data Champions team, with a goal to enhance service, governance and infrastructure, as necessary and appropriate. As indicated in the Timeline and Activities section below, quarters three and four of 2025 are designated for a formal revision of the set priorities, goals and objectives. Revision activities will consider outcomes and Strategy improvement and will occur under the direction of the RDMIC. A re-engagement of the research community will occur at this time.

 

Timeline and activities

Quarter Description
Q1 Strategy draft V3 – final review (RDMIC, VPR) + publish strategy
Q2 Goals, objectives, assessment metrics co-development
Q3 Campus consultation + engagement
Q4 Campus consultation + engagement

Quarter Description
Q1 Annual assessment + report to RDM governance
Q2 Campus update + RDM survey
Q3 Campus consultation + engagement
Q4 Campus consultation + engagement

Quarter Description
Q1 Annual assessment + report to RDM governance
Q2 Campus update + initiate formal strategy review
Q3 Campus consultation + engagement
Q4 Campus consultation + engagement

Quarter Description
Q1 Publish revised RDM strategy

Resources and standards

Definitions

"Confidential Information" means "knowledge, materials, know-how or any proprietary information, whether in electronic, written, graphic or other tangible form and any such oral information that has been reduced to writing within two weeks of its disclosure" (ArticNet Data Management Policy, ArticNet 2021, 12).

"Data deposit" refers to "when the research data collected as part of a research project are transferred to a research data repository. The repository should have easily accessible policies describing deposit and user licenses, access control, preservation procedures, storage and backup practices, and sustainability and succession plans. The deposit of research data into appropriate repositories supports ongoing data-retention and, where appropriate, access to the data. Ideally, data deposits will include accompanying documentation, source code, software, metadata, and any supplementary materials that provide additional information about the data, including the context in which it was collected and used to inform the research project. This additional information facilitates curation, discoverability, accessibility, and reuse of the data" (Tri-Agency Research Data Management Policy, Frequently Asked Questions, Government of Canada 2021).

A "data management plan" is "a living document, typically associated with an individual research project or program that consists of the practices, processes and strategies that pertain to a set of specified topics related to data management and curation. DMPs should be modified throughout the course of a research project to reflect changes in project design, methods, or other considerations. DMPs guide researchers in articulating their plans for managing data; they do not necessarily compel researchers to manage data differently" (Tri-Agency Research Data Management Policy, Frequently Asked Questions, Government of Canada 2021).

"Indigenous research" is "research in any field or discipline that is conducted by, grounded in or engaged with First Nations, Inuit, Métis or other Indigenous nations, communities, societies or individuals, and their wisdom, cultures, experiences or knowledge systems, as expressed in their dynamic forms, past and present" (Social Sciences and Humanities Research Council Definition of Terms, Government of Canada 2021).

"Intellectual property" means "all materials, concepts, know-how, formulae, inventions, improvements, industrial designs, processes, patterns, machines, manufactures, compositions of matter, compilations of information, patents and patent applications, copyrights, trade secrets, technology, technical information, software, prototypes and specifications, including any rights to apply for protections under statutory proceedings available for those purposes, provided they are capable of protection at law" (ArticNet Data Management Policy, ArticNet 2021, 12).

A "researcher" can include any individual who worked on the research project that could legitimately claim academic authorship of the research project if the results of the research project were to be published in a scholarly work (Queen’s University RDM Survey, Queen’s University Library 2015).

"Research data" are "data that are used as primary sources to support technical or scientific enquiry, research, scholarship, or creative practice, and that are used as evidence in the research process and/or are commonly accepted in the research community as necessary to validate research findings and results. Research data may be experimental data, observational data, operational data, third party data, public sector data, monitoring data, processed data, or repurposed data. What is considered relevant research data is often highly contextual, and determining what counts as such should be guided by disciplinary norms." (Tri-Agency Research Data Management Policy, Frequently Asked Questions, Government of Canada 2021).

"Research data management" is “the storage of, access to and preservation of data produced from one or more investigations, or from a program of research. Research data management practices cover the entire lifecycle of the data, from planning the investigation to conducting it, and from backing up data as it is created and used to preserving data for the long term after the research has concluded. It also includes data-sharing, where applicable” (Social Sciences and Humanities Research Council Definition of Terms, Government of Canada 2021).

A "research project" can be defined as the "research associated with investigating a hypothesis or group of hypotheses (and applicable set of predictions) aimed at answering a distinct or specific research question." A single research grant may support one research project or multiple research projects. In the context of this survey, a research project is associated with a distinct set of research data and is a subset of a research program, research activity or research area you may investigate (Queen’s University RDM Survey, Queen’s University Library 2015).

Looking ahead

Currently we are resourced to assist Tri-Agency funded researchers with the first round of applications requiring DMPs in late 2022/early 2023. The institutional strategy is a living document and the RDMIC will revisit the strategy as per the Timeline and Activities section above. As indicated, we plan for an annual review of Queen’s Institutional Strategy by the RDMIC and the VPR Executive team.

For more information, please contact:
Brian Amsden, Associate Vice-Principal Research

In response to the release of the Tri-Agency Data Management Policy (2021), Queen’s University will develop an institutional strategy to govern research data management at Queen’s. According to the Tri-Agency Policy, “research data collected through the use of public funds should be responsibly and securely managed and be, where ethical, legal and commercial obligations allow, available for reuse by others. To this end, the agencies support the FAIR (Findable, Accessible, Interoperable, and Reusable) guiding principles for research data management and stewardship.” 

Access the RDMIC TOR to learn how Queen’s is shaping a culture of FAIR (Findable, Accessible, Interoperable, and Reusable) data and supporting researchers in responsible data management.

The 2025 RDM Implementation committee (RDMIC) consists of:

  • Aleksandra Bergier, Research Advisor, Equity, Diversity, Inclusion and Indigenization (EDII), VPR
  • Alexandra Cooper, Data Services Coordinator, Queen’s University Library 
  • Alyssa Conlon, RDM Librarian, Queen’s University Library 
  • Ashley Theis, Associate Director, Research Compliance and Training (on-leave)
  • Brian Amsden, Associate Vice-Principal Research, VPR (Chair)
  • Diane Davies, Research Project Advisor, Social Sciences and Humanities, VPR
  • Heather Merla, Academic Affairs and Special Projects Officer, School of Graduate Students and Postdoctoral Affairs
  • Lisa McAvoy, Associate Director, Health Sciences Research, Kingston Health Sciences Centre Research Institute
  • Margo Langford, Director, Legal Counsel, Research Legal Services, VPR
  • Meghan Goodchild, Interim Head, Digital Initiatives and Open Scholarship, Queen’s University Library 
  • Nevil Joseph Silverius, Systems Engineer, CAC
  • Paige Beddoe, Associate Director, Research Engagement and Administration, Centre for Advanced Computing
  • Paul Muir, Information Security Officer, Information Technology Services
  • Rebecca Pero, Research Data Management Advisor, VPR (Administrator)
  • Ricardo Smalling, Senior Legal Counsel, Chief Privacy Officer and Director, Research Security
  • Ruslan Kain, Postdoctoral Researcher, School of Computing
  • Sarah Gauthier, Research Contracts Associate / Legal Advisor, Research Legal Services, VPR (on-leave)
  • Tracie Hanna, Associate Director, Research Compliance and Training (interim)