Data Management and Publishing

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.

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, MIT, 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?

Faculty Successes:

"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 Economics, MIT