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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

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

1. DataONE

2. DMPTool

3. FAIRsharing.org

4. ORCiD