FAIRification: A necessary practice for research data management - Batista, Dianelis Olivera; Mederos, Amed Abel Leiva; González, María Josefa Peralta (Advanced Notes in Information Science, 2024)
The term FAIRification has become widespread among professionals whose work is related to research data management. However, little is known about FAIRification practices. This paper aims to examine FAIRification practices applied to research data from all areas of knowledge. The research is an exploratory study, using documentary analysis and content analysis methods. The results show that the literature on the subject is recent and generally in English. The papers, projects, and scientific articles analyzed show the development of infrastructures and tools but also the need for a culture of research data management. It is concluded that most of the experiences in FAIRification have been directed to the development of workflows, infrastructures, and tools to comply with FAIR principles. There is a predominance of FAIRification of data in the health research domain, with a greater boom after COVID-19.