Thank you to Virginia Wilson at the University of Saskatchewan Library for allowing me to copy her excellent Research Data Management guide.
I have changed some of the information to reflect KPU's situation, but most almost all credit goes to Virginia.(Any mistakes are likely mine, though!)
(adapted from: Primer: Research Data Management, Portage Training Expert Group, 2019)
(adapted from Primer: Research Data Management, Portage Training Expert Group, 2019)
The following video from the UK Data Service describes typical data management activities that take place at each stage of the research process. (Note: There is no audio in this video.)
Research data management refers to the storage, access and preservation of data produced from a given research project. RDM practices cover the entire data lifecycle: from planning the project through conducting it and disseminating the results; from collecting the data to analysing, cleaning, sharing, and preserving or destroying it after the project has concluded.
Data management activities and topics include:
(adapted from Research Data Management, CODATA Research Data Management Terminology)
RDM is an integral component of the research process which benefits researchers, the research community, and society at large.
For researchers, good research data management:
For society, RDM:
In 2021, the Canadian Tri-Council funding agencies (CIHR, NSERC, SSHRC) introduced the Tri-Agency Research Data Management Policy, which stipulates:
These requirements follow on best practices established in the 2016 Tri-Agency Statement of Principles for Digital Data Management.