Finding explanations for queries to Description Logics (DL) theories is a non-standard reasoning service originally defined for debugging purposes but recently found useful for answering queries to probabilistic theories. In the latter case, besides the axioms that are used to entail the query, it is necessary to record also the individuals to which the axioms are applied. We refer, in this cas...

The Standard for the Exchange of Product model data (STEP) [1] contains product information mainly related to geometry. The modeling language used to develop this standard, EXPRESS, does not have logical formalism that will enable rigorous semantics. In this paper we present an OWL-DL (Web Ontology Language Description Logic) [2] version of STEP (OntoSTEP) that will allow logic reasoning and in...

The standard semantics employed for description logics (DLs) adheres to the open world assumption (OWA). On one hand, such an assumption facilitates a modeler to formally represent problem domains with out explicitly expressing full information, which sometimes is even not possible. This is probably one of the main reasons of founding the Web Ontology Language (OWL) based on DLs. On the other h...

Building domain ontologies such as the SNOMED CT requires a significant amount of effort and expertise. Among supporting tools for building such ontologies are tableaux-based reasoners [21, 19] which can help with detecting inconsistencies or computing implicit statements (i.e. entailments) following from ontologies. They do, however, have a downside: it is difficult to explain their reasoning ...

For debugging OWL-DL ontologies, natural language explanations of inconsistencies and undesirable entailments are of great help. From such explanations, ontology developers can learn why an ontology gives rise to specific entailments. Unfortunately, commonly used tableaux-based reasoning services do not provide a basis for such explanations, since they rely on a refutation proof strategy and no...

The Ontology Web Language (OWL) has received considerable traction recently and is used in a number of industrial and practical applications. While decidable, all basic reasoning tasks for OWL are intractable (most of them are N2ExpTime-complete). Thus, in order to obtain a system capable of solving practically-relevant nontrivial problems, a number of theoretical and practical issues need to b...

Finding the justifications of an entailment (that is, all the minimal set of axioms sufficient to produce an entailment) has emerged as a key inference service for the Web Ontology Language (OWL). Justifications are essential for debugging unsatisfiable classes and contradictions. The availability of justifications as explanations of entailments improves the understandability of large and compl...

After becoming a W3C Recommendation, OWL is becoming increasingly widely accepted and used. However most people still find it difficult to create and use OWL ontologies. On major difficulty is “debugging” the ontologies discovering why a reasoners has inferred that a class is “unsatisfiable” (inconsistent). Even for people who do understand OWL and the logical meaning of the underlining descrip...