O'FAIRe, the Ontology FAIRness Evaluator, is a methodology to automatically assess to which level a semantic resource or ontology respects the FAIR Principles. This paper describes the online tool implementing O'FAIRe within the AgroPortal ontology repository, through 61 questions/tests, among 80% are based on the ontology metadata description. For a specific ontology or a group of semantic resources, O'FAIRe web service outputs both global and detailed scores (normalized) against the 15 FAIR Principles. O'FAIRe results are visualized and explained with new specific user-friendly interfaces (such as the FAIRness wheel) in order to help AgroPortal users improve the FAIRness of their resources. O'FAIRe is currently implemented in three different public ontology repositories as they offer the required metadata descriptions. In the future, we will deploy the service in other OntoPortal repositories.
We have not yet seen a clear methodology implemented and tooled to automatically assess the level of FAIRness of semantic resources. We propose a metadata-based automatic FAIRness assessment methodology for ontologies and semantic resources called Ontology FAIRness Evaluator (O'FAIRe). It is based on the projection of the 15 foundational FAIR principles for ontologies, and it is aligned and nourished with relevant state-of-the-art initiatives for FAIRness assessment. We propose 61 questions of which 80% are based on the resource metadata descriptions and we review the standard metadata properties (taken from the MOD 1.4 ontology metadata model) that could be used to implement these metadata. We also demonstrate the importance of relying on ontology libraries or repositories to harmonise and harness unified metadata and thus allow FAIRness assessment. Moreover, we have implemented O'FAIRe in the AgroPortal semantic resource repository and produced a preliminary FAIRness analysis over 149 semantic resources in the agri-food/environment domain.
We have not yet seen a clear methodology implemented and tooled to automatically assess the level of FAIRness of semantic resources. We propose a metadata-based automatic FAIRness assessment methodology for ontologies and semantic resources called Ontology FAIRness Evaluator (O'FAIRe). It is based on the projection of the 15 foundational FAIR principles for ontologies, and it is aligned and nourished with relevant state-of-the-art initiatives for FAIRness assessment. We propose 61 questions of which 80% are based on the resource metadata descriptions and we review the standard metadata properties (taken from the MOD 1.4 ontology metadata model) that could be used to implement these metadata. We also demonstrate the importance of relying on ontology libraries or repositories to harmonise and harness unified metadata and thus allow FAIRness assessment. Moreover, we have implemented O'FAIRe in the AgroPortal semantic resource repository and produced a preliminary FAIRness analysis over 149 semantic resources in the agri-food/environment domain.
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