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Recording and documenting human and AI-driven normative decision-making processes has so far been highly challenging. We focus on the challenge of normative coordination: the process by which stakeholders in a community understand and agree what norms they abide by. Our aim is to develop and formalize the FLINT language, which allows a high-level description of normative systems. FLINT enables legal experts to agree on norms, while also serving as a basis for technical implementation.

Our contribution consists of the development of an ontology for FLINT and its RDF/OWL implementation which we have made openly accessible. We designed the ontology on the basis of competency questions. Additionally, we validated the ontology by modeling example cases and using the ontology’s data model in software tooling.