Data curation is the process of making data findable and usable to others, now and in the future. In 2016, the FAIR Guiding Principles for scientific data management and stewardship were developed to provide guidance for data producers and publishers to enhance the reusability of scientific data. The principles emphasize machine-actionability (i.e., the capacity of computational systems to find, access, interoperate, and reuse data with none or minimal human intervention.
Visit GoFAIR to learn more about the FAIR principles.
The Data Curation Centre has developed a standardized set of steps and checklists for data curation. See the CURATE(D) steps, checklists and primers below. Their primers can also be found on github.