Skip to Main Content

Data Management

Information and resources pertaining to research data management.

How to FAIR

How to FAIR ( is a website produced by a collaboration of the Danish Universities and is an essential read for anyone preparing to do research. It has various modules describing the importance of Findable, Accessible, Interoperable and Reusable research data. Included in the cite is a data management planning tool.


MIT Libraries Data Planning Checklist

This checklist was originally written by the MIT Libraries but is no longer hosted on their website. This version of the checklist was prepared by the UCLA Library.

  1. What type of data will be produced? Will it be reproducible? What would happen if it got lost or became unusable later?
  2. How much data will it be, and at what growth rate? How often will it change?
  3. Who will use it now, and later?
  4. Who controls it (PI, student, lab, UCLA, funder)?
  5. How long should it be retained? e.g. 3-5 years, 10-20 years, permanently
  6. Are there tools or software needed to create/process/visualize the data?
  7. Any special privacy or security requirements? e.g., personal data, high-security data
  8. Any sharing requirements? e.g., funder data sharing policy
  9. Any other funder requirements? e.g., data management plan in proposal
  10. Is there good project and data documentation?
  11. What directory and file naming convention will be used?
  12. What project and data identifiers will be assigned?
  13. What file formats? Are they long-lived?
  14. Storage and backup strategy?
  15. When will I publish it and where?
  16. Is there an ontology or other community standard for data sharing/integration?
  17. Who in the research group will be responsible for data management?