FAIR 2.0: Extending the FAIR Guiding Principles to Address Semantic Interoperability
Lars Vogt, Philip Str\"omert, Nicolas Matentzoglu, Naouel Karam,, Marcel Konrad, Manuel Prinz, Roman Baum

TL;DR
This paper extends the FAIR data principles to FAIR 2.0 by emphasizing semantic interoperability through ontological, referential, schema, and logical mappings, and proposes additional FAIR services for enhanced data sharing.
Contribution
It introduces FAIR 2.0, expanding FAIR principles to better address semantic interoperability with new mappings and services, inspired by linguistic structures.
Findings
Proposes extensions to FAIR principles for semantic interoperability.
Defines four types of interoperability: ontological, referential, schema, and logical.
Suggests FAIR services including terminology, schema, and operations.
Abstract
FAIR data presupposes their successful communication between machines and humans while preserving their meaning and reference, requiring all parties involved to share the same background knowledge. Inspired by English as a natural language, we investigate the linguistic structure that ensures reliable communication of information and draw parallels with data structures, understanding both as models of systems of interest. We conceptualize semantic interoperability as comprising terminological and propositional interoperability. The former includes ontological (i.e., same meaning) and referential (i.e., same referent/extension) interoperability and the latter schema (i.e., same data schema) and logical (i.e., same logical framework) interoperability. Since no best ontology and no best data schema exists, establishing semantic interoperability and FAIRness of data and metadata requires…
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Taxonomy
TopicsResearch Data Management Practices · Scientific Computing and Data Management · Semantic Web and Ontologies
