Possibilistic testing of OWL axioms against RDF data.

We develop the theory of a possibilistic framework for OWL 2 axiom testing against RDF datasets, as an alternative to statistics-based heuristics. The intuition behind it is to evaluate the credibility of OWL 2 axioms based on the evidence available in the form of a set of facts contained in a chosen RDF dataset. To achieve it, we first define the notions of development, content, support, confirmation and counterexample of an axiom. Then we use these notions to define the possibility and necessity of an axiom and its acceptance/rejection index combining both of them. Finally, we report a practical application of the proposed framework to test SubClassOf axioms against the DBpedia RDF dataset.