FAIRification of Citizen Science Data

Citizen Science (CS) initiatives encourage citizens to collect local data, contributing to knowledge creation and scientific development. However, these CS initiatives do not follow metadata nor data-sharing standards, which hampers their discoverability and reusability out of the scope of them. To improve this scenario in CS is crucial to consider Findable, Accessible, Interoperable and Reusable (FAIR) guidelines for research data sharing. This work proposes a FAIRification process (i.e. making CS initiatives more FAIR compliant), enhancing data sharing capacities in the CS context. It will be considered the adoption of Web standards, Web application programming interfaces (APIs) and Web augmentation. This approach contributes to the production of FAIR data in CS for data consumers. As preliminary results this paper explains the FAIRification process. The research objectives and plan are also presented.