Research Data Management Strategy

Background

In March 2021, the Government of Canada released the Tri-Agency Research Data Management Policy which requires institutions that receive funding through the Tri-Agency (SSHRC, NSERC, CIHR), to create an institutional Research Data Management (RDM) strategy. RDM refers to the processes applied throughout the lifecycle of a research project that guide the collection, documentation, storage, sharing and preservation of research data. RDM supports the effective and responsible conduct of research and increases the ability to store, find, and reuse research data.

The purpose of this document is to provide RDM support to 91��ɫ�� employees and students who engage in research. 91��ɫ�� continues to work toward recognizing and integrating Indigenous awareness and ways of knowing, acknowledging accommodation and accessibility issues, and promoting and demonstrating equity, diversity, and inclusion in our research efforts.

In 2022, 91��ɫ�� established a RDM working group to create the initial draft of the strategy. The RDM working group is made up of key stakeholder departments from the College including:

Applied Research & Innovation
Library Services
Planning & Institutional Research

In addition, the RDM Working Group has been working in consultation with other stakeholders from the College including:

Information Technology (IT)
Research Ethics Committee
Indigenous Studies

As 91��ɫ��’s RDM strategy progresses, a representative from the College’s IT department will work with the RDM working group to assist in the selection and commissioning of digital technologies that meet privacy and data requirements before installing the digital tools.

Most of the research undertaken at 91��ɫ�� could be classified as applied research, which is broadly focused on using the latest knowledge and technologies to create new products and processes, or to improve existing ones. As 91��ɫ�� continues to add degree programs - which include research as part of the accreditation process - and hires more faculty with PhDs and research backgrounds, the RDM strategy will become an increasingly valuable resource for academic research and scholarship of teaching and learning activities.

Importance of Research Data Management

RDM practices expose researchers, faculty, students, and administrators to a range of potential benefits including:

Increased competitiveness in research grant implications applications
Impact on academic research (prestige of publishing) and scholarship of teaching and learning
Impact on curriculum
Increased accountability and safety measures
Increased accuracy and validity of data
Ensured long-term preservation of data when applicable
Ensured consistency in data depositing and sharing requirements
Clarity in guidelines
Increased credit and impact of the data

Part of the RDM process includes the creation of a Data Management Plan (DMP). A DMP is a formal document that details the strategies and tools that will be implemented to effectively manage data during the active phase of ongoing research, and the mechanisms that will be used for preserving and appropriately sharing data at the end of the project. A DMP is “a “living” document that can be modified throughout your project to reflect any changes that have occurred” (Digital Research Alliance of Canada).

A DMP helps to:

Meet grant application requirements and/or adhere to institutional data mandates
Make it easier for all team members to document, understand, find, and use data
Plan the resources, tools, and expertise needed for data management
Identify challenges for storing, handling, and managing the types and volume of data
Ensure reliability, authenticity, accuracy, and reproducibility of data
Have a detailed account of data collection, handling, and stewardship practices
Plan how to make data FAIR (findable, accessible, interoperable, and reusable) to maximize the research potential and impact of data (Digital Research Alliance of Canada)

Purpose

The purpose of this strategy is to foster a culture of excellence in RDM at 91��ɫ�� with consistent requirements and standards for the collection, storage and sharing of research data both within and outside of the organization.

Scope and Objective

This strategy applies to all 91��ɫ�� researchers conducting Tri-Agency-funded research activities, including students, staff, and faculty in all disciplines. As leaders in this transition towards RDM best practices, our initial focus will be to demonstrate strong data management practices and to ensure that our Tri-Agency-funded researchers have the tools, technologies, and service supports in place to aid their work. For awareness building, we have assumed a broad application of RDM best practices, given the diverse nature of 91��ɫ��’s research and innovation ecosystem.

91��ɫ��’s Research Data Management Plan

To support the adoption of 91��ɫ��’s RDM strategy and the ongoing implementation and expansion of RDM practices among researchers, 91��ɫ�� will continue to build on the work already completed or in process.

Over the next three years (until March 2026) we have committed to focusing on the following priorities and activities:

1) Review current state of RDM at 91��ɫ��:

Identify and review the data landscape at 91��ɫ�� and assess existing capacity for RDM
Evaluate existing RDM services and data management plans and provide institutional support and training

2) Build/expand institutional RDM supports/resources at 91��ɫ��:

Develop and disseminate RDM educational tools to 91��ɫ�� community who oversee research activities or are directly engaged in research
Audit existing resources with a willingness to adopt external resources as appropriate and required

3) Promote and foster a culture of RDM at 91��ɫ��:

Promote a culture of sound RDM
Develop and provide access to training resources and plan workshops or other events for faculty, staff, and students to increase their RDM knowledge

4) Support and encourage appropriate Indigenous RDM process and activities:

Consult with the 91��ɫ�� Indigenous Studies department in all matters that involve or could potentially involve members of our Indigenous communities, both internally and externally, to ensure we are adhering to cultural practices and ways of knowing
Comply with the OCAP principles (Ownership, Control, Access, Possession). The First Nations principles of OCAP establish how First Nations’ data and information will be collected, protected, used, or shared.
Engage in ongoing conversations with Indigenous partners (internal and external)
Liaise with appropriate partners to further develop RDM capacity for Indigenous research within 91��ɫ��

5) Strengthen RDM governance:

Evolve current RDM working group to formalize the implementation of 91��ɫ��’s RDM strategy, including engagement of other stakeholders across the College
Work toward updating intersecting/supporting 91��ɫ�� policies as required to reflect RDM practices
Establish more streamlined RDM communications and processes with external research partners as required

Ethics Consideration

Research projects involving human participants are reviewed by the 91��ɫ��’s Research Ethics Board (REB). The REB is comprised of community volunteers and knowledgeable faculty and staff trained and experienced in ensuring that research conducted at the College adheres to the guidelines and data management requirements set out by the Tri-Agency’s Tri-Council Policy Statement: Ethical Conduct for Research Involving Humans - TCPS2 (2018). As part of 91��ɫ��’s REB requirements, researchers are also required to complete the TCPS2 training module to conduct research involving human participants at 91��ɫ��.

Next Steps

This strategy outlines planned activities over the next three years to continue 91��ɫ��’s journey to foster a culture of excellence in RDM. Moving forward, 91��ɫ�� and its RDM working group will work on developing a Research Data Management Work Plan that will help to move the identified goals forward. 91��ɫ�� will continue to build and expand on RDM practices as this process is iterative and ever evolving. While this strategy identified the beginning components of our work as a College, it serves as the basis of our work moving forward and will be a living document. We will determine future areas to address based on evolving requirements from the Tri-Agency, the needs of 91��ɫ�� researchers, and the type of research that is undertaken at the College.

Responsibilities and Accountability

This strategy will be monitored regularly by the RDM working group and updated on an annual basis.

All members of the 91��ɫ�� community are responsible for ensuring compliance and adherence to the RDM strategy, particularly those who are involved in the College’s research enterprise. Faculty, staff, and all researchers must comply with appropriate Tri-Council RDM requirements, particularly when it comes to ethical and data considerations. Beyond the collective obligations, the Vice President, Academic will uphold and champion the principles of RDM to all faculty engaged in research and scholarship of teaching and learning.

Definitions

Research data: Data that are used as primary sources to support technical or scientific enquiry, research, scholarship, or artistic activity, 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. All other digital and non-digital content have the potential of becoming research data. Research data may be experimental data, observational data, operational data, third party data, public sector data, monitoring data, processed data, repurposed data, and may include stories that are told (images, recordings, artifacts) that are collected through the process of storytelling. Raw data that is not necessarily published but needs to be managed and/or organized also falls under the umbrella of research data.

Research data lifecycle: The points throughout the research process where data is conceived, created, collected, manipulated, stored, shared, archived, and destroyed where RDM practices must be considered and implemented.

Research Data Management (RDM): Data management refers to the storage, access and preservation of data produced from a given investigation. 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 long-term preservation of data deliverables after the research investigation has concluded. Specific activities and issues that fall within the category of data management include file naming conventions, data quality control and quality.

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