Good data management is the foundation for good research. Today, more and more publishers and funding agencies are requiring researchers to share their data. Having a data management plan fulfills agency requirements and makes your data easier to share.
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.
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, 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 sharing/integration?
Who in the research group will be responsible for data management?
Thank you to MIT Libraries and the University of Virginia Library's Scientific Data Consulting Group for providing guidance and allowing us to repurpose content found on their guides.