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Learn more about managing your research data and resources to collect data

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