Several initiatives proposed maturity indicators definitions ranging from textual description to semantically annotated files. For example, the Research Data Alliance (RDA) developed a data maturity model in textual format . The work developed a standard set of core assessment criteria for FAIRness as an RDA Recommendation. FairPlus, a project aims to develop tools and guidelines for making life science data FAIR, also used textual descriptions for maturity indicators and developed the FAIR cookbook to guide researchers and data stewards of the life science in their data FAIRification tasks . defined maturity indicators using Markdown and Nanopublication RDF formats. However, that work excluded from the MI set the subprinciples R1.2 and R1.3 concerning providing rich metadata associated with detailed provenance and meeting domain-relevant community standards, respectively. A common notice of the published literature on FAIR maturity assessment is that evaluating if metadata follows community standards (R1.3) is always absent , as community standards are not formally established yet from the FAIR maturity model perspective.