The Systematic Dataset Review Process: from Linked Dataset Discoverability to their FAIRness

This work presents the Systematic Dataset Review process, a systematic, cyclic, and FAIR-aligned process for dataset discovery, curation, and quality assessment, inspired by Systematic Literature Review methodologies. The process consists of three phases: (i) a (multivocal) literature review to identify and document references about datasets; (ii) a Linked Dataset Discoverability phase to curate, filter, and publish datasets as domain-specific Linked Open Data sub-clouds; and (iii) a Quality Assessment phase that enables FAIRness evaluations through automated tools. The framework is adaptable across different use cases: monitoring the quality of existing sub-clouds, enriching current sub-clouds with new datasets, or constructing entirely new thematic sub-clouds. By ensuring transparency, reproducibility, and ongoing quality monitoring, this approach supports the creation of accessible and sustainable dataset ecosystems.