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Research Data Management: Home

Data Planning Checklist

Data Planning Questions:

Data description

  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 there be? How quickly will it grow? How often will it change? Once archives/stored, what kind of access will be needed to use it?
  3. Who will use the data now, and in the future?
  4. Who controls the data (PI, student, lab, Caltech, funding agency)? What intellectual property considerations might apply?
  5. How long should the data be retained? How long would you expect it to be useful, e.g. through the end of grant/experiment, 3-5 years, 10-20 years, permanently?


  1. Is there good project and data documentation?
  2. What directory and file naming conventions will be used?
  3. What project and data identifiers will be assigned?
  4. What file formats are used? Are they standards-based or proprietary?
  5. Are there tools or software needed to create/process/visualize the data? Are the tools or software proprietary?
  6. Is there an ontology or other community standard for data sharing/integration?

Access, Sharing, and Re-use

  1. Any special privacy or security requirements? e.g., personal data, high-security data
  2. Any sharing requirements? e.g., funder data sharing policy
  3. Any other funder requirements? e.g., data management plan in grant proposals
  4. What is your storage and backup strategy?
  5. When will it be shared and where? How broadly will it be shared? Are there I/O throughput issues with respect to the size of the datasets?
  6. Who in the research group will be responsible for data management?

Guides to Data Management

The following guides cover general principles for managing your data, plus select information related to particular formats or disciplines.

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