Research Data Management 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.

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.

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. 

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. 

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.

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.