We present a novel reasoning procedure for Horn SHIQ ontologies—SHIQ ontologies that can be translated to the Horn fragment of first-order logic. In contrast to traditional reasoning procedures for ontologies, our procedure does not build models or model representations, but works by deriving new consequent axioms. The procedure is closely related to the so-called completion-based procedure for EL++ ontologies, and can be regarded as an extension thereof. In fact, our procedure is theoretically optimal for Horn SHIQ ontologies as well as for the common fragment of EL++ and SHIQ. A preliminary empirical evaluation of our procedure on large medical ontologies demonstrates a dramatic improvement over existing ontology reasoners. Specifically, our implementation allows the classification of the largest available OWL version of Galen. To the best of our knowledge no other reasoner is able to classify this ontology.

Conjunctive queries (CQ) are fundamental for accessing description logic (DL) knowledge bases. We study CQ answering in (extensions of) the DL EL, which is popular for large-scale ontologies and underlies the designated OWL2-EL profile of OWL2. Our main contribution is a novel approach to CQ answering that enables the use of standard relational database systems as the basis for query execution. We evaluate our approach using the IBM DB2 system, with encouraging results.

Open-ended language communication remains an enormous challenge for autonomous robots. This paper argues that the notion of a language strategy is the appropriate vehicle for addressing this challenge. A language strategy packages all the procedures that are necessary for playing a language game. We present a specific example of a language strategy for playing an Action Game  in which one robot asks another robot to take on a body posture (such as stand or sit), and show how it effectively allows a population of agents to self-organise a perceptually grounded ontology and a lexicon from scratch, without any human intervention. Next, we show how a new language strategy can arise by exaptation from an existing one, concretely, how the body posture strategy can be exapted to a strategy for playing language games about the spatial position of objects (as in "the bottle stands on the table").

We review and extend earlier work on the logic CFD, a description logic that allows terminological cycles with universal restrictions over functional roles. In particular, we consider the problem of reasoning about concept subsumption and the problem of computing certain answers for a family of attribute-connected conjunctive queries, showing that both problems are in PTIME. We then consider the effect on the complexity of these problems after adding a concept constructor that expresses concept union, or after adding a concept constructor for the bottom class. Finally, we show that adding both constructors makes both problems EXPTIME-complete.

We consider query answering on Description Logic (DL) ontologies with DBoxes, where a DBox is a set of assertions on individuals involving atomic concepts and roles called DBox predicates. The extension of a DBox predicate is exactly defined in every interpretation by the contents of the DBox, i.e., a DBox faithfully represents a database whose table names are the DBox predicates and the tuples are the DBox assertions. Our goals are (i) to find out whether the answers to a given query are solely determined by the DBox predicates and, if so, (ii) to find a rewriting of the query in terms of them. The resulting query can then be efficiently evaluated using standard database technology. We have that (i) can be reduced to entailment checking and (ii) can be reduced to finding an interpolant. We present a procedure for computing interpolants in the DL ALC with general TBoxes. We extend the procedure with standard tableau optimisations, and we discuss abduction as a technique for amending ontologies to gain definability of queries of interest.

Reasoning over complex queries in the DLs underlying OWL 2 is of  importance in several application domains.  We provide decidability and (tight) upper bounds for the problem of checking entailment and containment of positive regular path queries under various combinations of constructs used in such expressive DLs; specifically: regular expressions and (safe) Booleans over roles, and allowing for the combination of any two constructs among inverse roles, qualified number restrictions, and nominals.  Our results carry over also to the DLs of the SR family, and thus have a direct impact on OWL 2.

Effective communication in open environments relies on the ability of agents to reach a mutual understanding of the exchanged message by reconciling the vocabulary (ontology) used. Various approaches have considered how mutually acceptable mappings between corresponding concepts in the agents' own ontologies may be determined dynamically through argumentation-based negotiation (such as Meaning-based Argumentation). However, the complexity of this process is high, approaching π 2 (p) -complete in some cases. As reducing this complexity is non-trivial, we propose the use of ontology modularization as a means of reducing the space over which possible concepts are negotiated. The suitability of different modularization approaches as filtering mechanisms for reducing the negotiation search space is investigated, and a framework that integrates modularization with Meaning-based Argumentation is proposed. We empirically demonstrate that some modularization approaches not only reduce the number of alignments required to reach consensus, but also predict those cases where a service provider is unable to satisfy a request, without the need for negotiation.

We develop a framework for forgetting concepts and roles (aka uniform interpolation) in terminologies in the lightweight description logic EL extended with role inclusions and domain and range restrictions. Three different notions of forgetting, preserving, respectively, concept inclusions, concept instances, and answers to conjunctive queries, with corresponding languages for uniform interpolants are investigated. Experiments based on SNOMED CT (Systematised Nomenclature of Medicine Clinical Terms) and NCI (National Cancer Institute Ontology) demonstrate that forgetting is often feasible in practice for large-scale terminologies.

This paper provides a decentralized data model and associated algorithms for peer data management systems (PDMS) based on the DL-liteR description logic. Our approach relies on reducing query reformulation and consistency checking for DL-liteR into reasoning in propositional logic. This enables a straightforward deployment of DL-liteR PDMSs on top of SomeWhere, a scalable propositional peer-to-peer inference system. We also show how to use the state-of-the-art Minicon algorithm for rewriting queries using views in DL-liteR in the centralized and decentralized cases.

To enable ontology reuse, the Web Ontology Language (OWL) allows an ontology Kv to import an ontology Kh. To reason with such a Kv, a reasoner needs physical access to the axioms of Kh. For copyright and/or privacy reasons, however, the authors of Kh might not want to publish the axioms of Kh; instead, they might prefer to provide an oracle that can answer a (limited) set of queries over Kh, thus allowing Kv to import Kh "by query." In this paper, we study import-by-query algorithms, which can answer questions about Kv U Kh by accessing only Kv and the oracle. We show that no such algorithm exists in general, and present restrictions under which importing by query becomes feasible.