In the presence of an ever growing amount of information, organizations and human users need to be able to focus on certain key pieces of information and to intentionally ignore all other possibly relevant parts. Knowledge about complex systems that is represented in ontologies yields collections of axioms that are too large for human users to browse, let alone to comprehend or reason about it. We introduce the notion of an ontology excerpt as being a fixed-size subset of an ontology, consisting of the most relevant axioms for a given set of terms. These axioms preserve as much as possible the knowledge about the considered terms described in the ontology. We consider different extraction techniques for ontology excerpts based on methods from the area of information retrieval. To evaluate these techniques, we propose to measure the degree of incompleteness of the resulting excerpts using the notion of logical difference.

We propose a novel approach for detecting semantic differences between ontologies. In this paper we investigate the logical difference for ℰℒ-terminologies extended with role inclusions, and domain & range restrictions of roles. Three types of queries are covered: concept subsumption, instance and conjunctive queries. Using a hypergraph representation of such ontologies, we show that logical differences can be detected by checking for the existence of simulations between the corresponding hypergraphs. A minor adaptation of the simulation notions allows us to capture different types of queries. We also evaluate our hypergraph approach by applying a prototype implementation on large ontologies.

We study a logic-based approach to versioning of ontologies. Under this view, ontologies provide answers to queries about some vocabulary of interest. The difference between two versions of an ontology is given by the set of queries that receive different answers. We investigate this approach for terminologies given in the description logic EL extended with role inclusions and domain and range restrictions for three distinct types of queries: subsumption, instance, and conjunctive queries. In all three cases, we present polynomial-time algorithms that decide whether two terminologies give the same answers to queries over a given vocabulary and compute a succinct representation of the difference if it is non- empty. We present an implementation, CEX2, of the developed algorithms for subsumption and instance queries and apply it to distinct versions of Snomed CT and the NCI ontology.

The OWL 2 profile OWL 2 QL, based on the DL-Lite family of description logics, is emerging as a major language for developing new ontologies and approximating the existing ones. Its main application is ontology-based data access, where ontologies are used to provide background knowledge for answering queries over data. We investigate the corresponding notion of query inseparability (or equivalence) for OWL 2 QL ontologies and show that deciding query inseparability is PSPACE-hard and in EXPTIME. We give polynomial time (incomplete) algorithms and demonstrate by experiments that they can be used for practical module extraction.

With tableaux-based reasoning approaches or model checking techniques for propositional linear-time temporal logics, PLTL, it is easily possible to construct counter examples for formulae that are not valid. In contrast, only the information that a formula is satisfiable is usually available in resolution-based inference systems. In this paper we present a resolution-based approach for constructing models for satisfiable PLTL formulae. Our approach is based on using the standard model construction for sets of propositional clauses saturated under ordered resolution in the different time points of a temporal model. The temporal model construction procedure is also designed in such a way that it can be easily implemented in existing theorem rovers for PLTL.