Research Data Management (RDM) is the intentional and methodical process, throughout an entire research project, of keeping your collected data organized. This goes from planning what data you will collect, considering if there are privacy or security issues to be careful of, determining how you will store it during the project, documenting all your decisions about your data collection and data curation, and ensuring your data's long term preservation for secondary analysis.
Proper data management helps:
- ensure your data is complete, documented, and accessible to you and/or to future researchers
- satisfy grant, journal, or funder requirements.
- raise the profile of your research
- meet the data sharing expectations of your research community
A valuable tool for ensuring your data management practices are thorough is to create a Data Management Plan, discussed in more detail elsewhere in this guide
Guiding principles for data management
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FAIR - Findable, Accessible, Interoperable, Re-usable
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OCAP - First Nations principles of Ownership, Control, Access, Possession
- CARE - Indigenous data governance principles of Collective benefit, Authority to control, Responsibility, and Ethics
