A Data Planning Checklist
Managing your data before you begin your research and throughout its life
cycle is essential to ensure its current usability and long-run preservation
and access. To do so, begin with a planning process. See also our page on data management plans.
- What type of data will be produced? Will it be reproducible? What would happen if it got lost or became unusable later?
- How much data will it be, and at what growth rate? How often will it change?
- Who will use it now, and later?
- Who controls it (PI, student, lab, MIT, funder)?
- How long should it be retained? e.g. 3-5 years, 10-20 years, permanently
- Are there tools or software needed to create/process/visualize the data?
- Any special privacy or security requirements? e.g., personal data, high-security data
- Any sharing requirements? e.g., funder data sharing policy
- Any other funder requirements? e.g., data management plan in proposal
- Is there good project and data documentation?
- What directory and file naming convention will be used?
- What project and data identifiers will be assigned?
- What file formats? Are they long-lived?
- Storage and backup strategy?
- When will I publish it and where?
- Is there an ontology or other community standard for data
- Who in the research group will be responsible for data management?
"I've had thousands of downloads of my published data--I am impressed
that it's been so useful to others!"
Esther Duflo, Abdul Latif Jameel Professor of Poverty Alleviation and Development