Skip to Main Content
It looks like you're using Internet Explorer 11 or older. This website works best with modern browsers such as the latest versions of Chrome, Firefox, Safari, and Edge. If you continue with this browser, you may see unexpected results.
Research Data Management Libguide
For all the information about Research Data Management, please see the
What is Research data management (RDM)?
RDM can be defined as a process which consists of two components:
Planning for the manner in which research data will be managed during and after the research process; and
Controlling the collection, processing, analysis, sharing, dissemination, curation and reuse of research data
This guide will assist with the processes of both these components.
Why Research Data Management is needed
The benefits of publicly-funded research should flow back to the public
Management of research projects in a more efficient manner
Compliance with research funder mandate
Compliance with legal and ethical requirements
In order to facilitate the reproducibility and re-usability of research findings
Duplication of research efforts can be reduced – along with the associated costs
Validation of previously published research
Goals of RDM
Researchers should take cognisance of the following goals of research data management:
Assurance that research data are capable of supporting analysis.
Assurance that all operations performed on research data are traceable.
Facilitating use of research data by people other than those involved in their original collection, generation, management and analyse.
Zozus, M. 2017. The Data Book : Collection and Management of Research Data. Boca Raton: CRC Press, Taylor & Francis Group.