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What is Data Management? Why is it useful?
Research data management (RDM) is a concept used to describe the managing, sharing, and archiving of research data to make it more accessible to the broader research community. Research data management provides an opportunity for a researcher to create a plan that will ensure that their data will be organized so that it can be shared with other researchers and archived for long term preservation.
- Makes data more findable and usable, and reproducible
- Ensures an ethical, responsible research environment
- Meets funder and journal data-sharing requirements
Best Practices of Data Management
Consider these goals for your data -
1. Organization -
- Assign RDM responsibilities (or take responsibility)
- Use clear, descriptive file names
- Be thoughtful about how you structure your folders
- Use disciplinary standards and sustainable data formats Be consistent and document
2. Storage and backup -
Follow the 3 – 2 – 1 rule :
- Keep one original, uncompressed version
- Document versioning (with a standard naming convention)
- Consider security ○ During data collection: who can access it and what can they do with it?
- When storing: restrictions versus embargoes
3. Preservation -
- Software and hardware change
- Store data where it will be backed up, discoverable, and accessible (as appropriate)
- Document clearly and thoughtfully
4. Distribution and sharing - Consider :
- What data should be kept
- Ownership, privacy, and intellectual property concerns
- What data will be shared
- What is the best home(s) for it
Tools for Data Management