AIOct 27, 2017

Enhancements of linked data expressiveness for ontologies

arXiv:1710.09952v11 citations
Originality Synthesis-oriented
AI Analysis

This work addresses the problem of insufficient expressiveness in ontologies for researchers, government, and civil society, but it is incremental as it builds on existing standards like OWL and RDF.

The authors tackled the limited expressiveness of existing ontology languages like OWL by proposing four new techniques for linked data ontologies, including stating property uses without axioms, assigning priority levels, improving diagram depictions, and associating OWL classes with SKOS concepts, and they developed specific rules and examples to demonstrate their application and challenges.

The semantic web has received many contributions of researchers as ontologies which, in this context, i.e. within RDF linked data, are formalized conceptualizations that might use different protocols, such as RDFS, OWL DL and OWL FULL. In this article, we describe new expressive techniques which were found necessary after elaborating dozens of OWL ontologies for the scientific academy, the State and the civil society. They consist in: 1) stating possible uses a property might have without incurring into axioms or restrictions; 2) assigning a level of priority for an element (class, property, triple); 3) correct depiction in diagrams of relations between classes, between individuals which are imperative, and between individuals which are optional; 4) a convenient association between OWL classes and SKOS concepts. We propose specific rules to accomplish these enhancements and exemplify both its use and the difficulties that arise because these techniques are currently not established as standards to the ontology designer.

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The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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