Research Data Management
Research Data Management (RDM)
Research data management (RDM) 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, 2021).
The data produced by research is valuable and steps should be taken for its protection, preservation, and (when appropriate) sharing. RDM has many benefits for researchers, funders, and the public by ensuring research is transparent, ethical, and has greater impact.
Social Sciences and Humanities Research Council. (2021, May 4). Definitions of terms. Government of Canada. https://www.sshrc-crsh.gc.ca/funding-financement/programs-programmes/definitions-eng.aspx#a29
The RDM Lifecycle
Research Data Management occours at every phase of research, including the planning and proposal steps. Below is an illustration of the Research Data Lifecycle, based on the steps outlined in the Portage Research Data Management Primer.
The Research Data Management Lifecycle
This work was licenced under a Creative Commons Attribution Non Commercial 4.0 International license by Portage based on a model developed by the Leadership Council for Digital Research Infrastructure. Graphics and layout have been altered.
Essential RDM Resources
A course from the First Nations Information Governance Centre on the OCAP® principles of Indigenous data.
Lear more about the principles of FAIR (findable, accessible, interoperable, and reusable) data.
Good Enough RDM: A Very Brief Guide
A concise guide to RDM by Eugene Barsky, University of British Columbia
The Digital Alliance of Canada's definition of RDM, list of RDM services, and a brief history of RDM in Canada.
Relevant External Policies
Your project's success may depend on the strength of your RDM practices. Many funding organizations and publishers have policies around RDM, particularly creating data management plans and depositing data. Be sure to carefully check these requirements in the planning phase of your research. Please see below for some examples:
Research Funding
Tri-Agency Research Data Management Policy
A section of this policy is specific to researchers.
Sherpa Juliet: Research Funders' Open Access Policies
This searchable database provides information about the RDM and Open Access polices of a wide range of international research funding agencies.
Research Publications
Nature: Reporting standards and availability of data, materials, code and protocols
SpringerNature: Research Data Policies