Data curators collaborate with researchers to make data more Findable, Accessible, Interoperable and Reusable by aligning with the FAIR Principles.
The curation process involves a review of a researcher’s data and documentation to ensure the data are as complete, understandable, and accessible as possible. These reviews do not judge the core scientific analysis, methodologies, or conclusions behind the data. Instead, the purpose of review is to ensure metadata completeness, and data usability and discoverability. The checklist below is useful for data curation, whether reviewing your own work or that of your colleagues or students.