Research Data Management: Why Research Data Management?

"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..." (CASRAI, n.d.)

In other words, research data management is a broad phrase used to describe the structure, organization, maintenance, and overall stewardship of research data throughout the research and data lifecycle.

Research and Data Lifecycle

University of Virginia

In 2016, the Tri-Agencies (CIHR, NSERC & SSHRC) announced that all institutions receiving funding would be required to have an institutional strategy and each funded project would need to have a data management plan.

After a consultation with stakeholders and research institutions, in March 2021 they released their policy.  There are 3 key parts to the policy:

1. Institutional strategy - all institutions eligible for Tri-Agencies funding must provide the Tri-Agencies with and have a published institutional strategy by March 1, 2023.
2. Data management plans - by Spring 2022 selected calls for proposals will have a data management plan requirement and DMPs will be considered in the adjudication process.
3. Data deposit - grant recipients will be required to deposit into a digital repository all digital research data, metadata and code that directly support the research conclusions that arise from agency-supported research.

At its core, RDM is viewed by funding agencies as a mechanism to enhance research excellence. It is important to note the data deposit requirement does not mean the data needs to be open access.

Tri-Agency Policies and Guidelines

• Tri-Agency Research Data Management Policy - Released March 15, 2021
• Tri-Agency Statement of Principles on Digital Data Management - Released June 15, 2016

This 4:40 minute video case study walks through what can go wrong without a plan and standards.

Hanson, K., Read, K. & Surkis, A. (2014, March 16). How to avoid a data management nightmare [Video]. YouTube. https://youtu.be/nNBiCcBlwRA 

This 4:40min video provides a light-hearted look at impediments to data-sharing, and why data-sharing matters.

Hanson, K. Surkis, A. & Yacobucci, K. (2021, December 19). Data sharing and management snafu in 3 short acts [Video]. YouTube. https://youtu.be/N2zK3sAtr-4