Research Data Management Strategy
Drafted February 2023
Introduction and Background
In March 2021, the Tri-Agency released its Research Data Management (RDM) Policy. The policy requires institutions to develop a robust research data management infrastructure in-line with best practices, such as:
- The Findable, Accessible, Interoperable, and Reusable (FAIR) guiding principles;
- Collective Benefit, Authority to Control, Responsibility, and Ethics (CARE) Principles for Indigenous Data Management;
- Tri-Council Policy Statement: Ethical Conduct for Research Involving Humans – TCPS 2 (2018).
The policy states: "The Agencies believe that 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." The policy is a three-pronged approach to RDM that requires institutions to implement:
- An institutional RDM strategy;
- Data management plans for research projects; and
- Data deposit options.
CMU Process
CMU formed a Research Data Management Strategy Ad hoc Committee in 2022 to lead the institution's RDM strategy planning. This committee consists of representatives from IT, the Library, the Research Office, the Research Ethics Board, and the Vice President Academic and Academic Dean.
Members of the Committee educated themselves using the RDM resources provided by the Digital Resource Alliance of Canada and the ARMIN (Alberta Research-Data Management Information Network) housed at Concordia University of Edmonton. The Committee conducted a preliminary assessment of institutional services and data management capacity assets guided by the RDM Maturity Assessment Model in Canada (MAMIC) adapted from the Digital Research Alliance of Canada. Faculty data champions were identified, and the committee gathered their input on CMU's RDM strengths and gaps. CMU's RDM Strategy is a result of these consultations.
CMU Research Data Management Strategy
I. Enhance Awareness of RDM across Canadian Mennonite University
- Explore building discipline-specific communities of practice to support our diverse research communities understand and embrace RDM
- Develop a targeted faculty and student engagement strategy
- Build data management literacy (incorporate into internal grants)
- Create a community of practice (online resources, RDM advisory committee est., identify champions)
II. Provide RDM Training and Capacity-building for Faculty and Staff
- Internal training and education:
- Workshops, Lunch and Learns and other training for faculty, students and staff on aspects of RDM (e.g. DMP Assistant training; data sharing deposit and preservation, etc.)
- Utilize existing data management knowledge in the Archives for the benefit of CMU as a whole
- Access to external Professional Development
- OCAP training to enhance understanding and competency for participation in research and data collection with Indigenous peoples.
- Build capacity of library staff to support good data management practices, discoverability, and access among faculty and support staff.
III. Strengthen RDM Governance
- Evolve current RDM Advisory Committee to formalize implementation of CMU's RDM Strategy, including engaging other stakeholders across the institution
- Update other CMU policies as required to reflect RDM practices (e.g., Research Ethics Board policies)
- Membership in organizations supporting Digital Research Infrastructure in Canada (eg. Digital Research Alliance)
- Dovetail internal processes that work to collaboratively and more efficiently strengthen Research Data Management, Institutional Data Management, and Archives Data Management
IV. Provide and Support Access to RDM Tools, Resources, and Infrastructure
- Identify off-site physical repository storage options for data deposit by CMU faculty and staff.
- Investigate new tools for data deposit, discovery and access
- Work with CMU's Research Ethics Board to update application form and other tools to capture RDM practice details.
- Pursue and secure funding for enhanced data management processes across campus (RDM, institutional data, Archives data)
Definitions
Data Management Plan: A 'data management plan' (DMP) 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" (Tri-Agency Research Data Management Policy, Frequently Asked Questions, Government of Canada 2021).
Metadata: Metadata is data about data and is the information needed to make a dataset discoverable, citable, and usable by others.
Research: Research is creative and systematic work that is undertaken to increase knowledge in a particular area or discipline. It involves the collection, organization, and analysis of information to increase understanding of a topic or issue.
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, or repurposed data" (Committee on Data, International Science Council).
Research Data Management: "Research 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 (the proper way to name computer files); data quality control and quality assurance; data access; data documentation (including levels of uncertainty); metadata creation and controlled vocabularies; data storage; data archiving and preservation; data sharing and reuse; data integrity; data Canadore College Research Data Management Strategy security; data privacy; data rights; notebook protocols (lab or field)" (Committee on Data, International Science Council).
Resources
- ARMIN: https://concordia.ab.ca/research/research-at-concordia/armin/
- Brandon University Research Data Management Strategy: https://www.brandonu.ca/research/files/Research-Data-Strategy.pdf
- Canadore College Research Data Management Strategy: https://cdn.agilitycms.com/canadore-college/Attachments/about-us/ace-research/Canadore%20RDM%20Strategy%20Final.pdf
- Digital Research Alliance of Canada: https://alliancecan.ca/en
- MAMIC: https://zenodo.org/record/5745493#.Y-0VDXbMKUk
- Sheridan College Research Data Management Strategy: https://sheridancollege.libguides.com/ld.php?content_id=36519578
- VIU Research Data Management Strategy: https://specproj.web.viu.ca/VIU_RDMStrategy_2022-2025.pdf
Printed from: www.cmu.ca/research-office/data-management-strategy