Abstract. We present a novel combination of disjunctive logic programs under the answer set semantics with description logics for the Semantic Web. The combination is based on a well-balanced interface between disjunctive logic programs and description logics, which guarantees the decidability of the resulting formalism without assuming syntactic restrictions. We show that the new formalism has very nice semantic properties. In particular, it faithfully extends both disjunctive programs and description logics. Furthermore, we describe algorithms for reasoning in the new formalism, and we give a precise picture of its computational complexity. We also provide a special case with polynomial data complexity. 1

Abstract. We propose a new family of Description Logics (DLs), called DL-Lite, specifically tailored to capture basic ontology languages, while keeping low complexity of reasoning. Reasoning here means not only computing subsumption between concepts, and checking satisfiability of the whole knowledge base, but also answering complex queries (in particular, unions of conjunctive queries) over the instance level (ABox) of the DL knowledge base. We show that, for the DLs of the DL-Lite family, the usual DL reasoning tasks are polynomial in the size of the TBox, and query answering is LogSpace in the size of the ABox (i.e., in data complexity). To the best of our knowledge, this is the first result of polynomial time data complexity for query answering over DL knowledge bases. Notably our logics allow for a separation between TBox and ABox reasoning during query evaluation: the part of the process requiring TBox reasoning is independent of the ABox, and the part of the process requiring access to the ABox can be carried out by an SQL engine, thus taking advantage of the query optimization strategies provided by current Data Base Management Systems. Since it can be shown that even slight extensions to the logics of the DL-Lite family make query answering at least NLogSpace in data complexity, thus ruling out the possibility of using on-the-shelf relational technology for query processing, we can conclude that the logics of the DL-Lite family are the maximal DLs supporting efficient query answering over large amounts of instances. 1.

Ontologies play a key role in the Semantic Web [4], data modeling, and information integration [16]. Recent trends in ontological reasoning have shifted from decidability issues to tractability ones, as e.g. reflected by the work on the DL-Lite family of tractable description logics (DLs) [11, 19]. An important result of these works is that the main

Abstract. In Ontology Based Data Access (OBDA), the aim is to use an ontology to mediate access to data. The main contribution of this work is to demonstrate two key components of an OBDA system, whose combination allows ontology practitioners to finally realize end-to-end OBDA systems. The first component is an OBDA-enabled reasoner, named DIG-MASTRO. The second component is the OBDA Plugin for Protégé, that in conjunction with the ontology editing features of Protégé, functions as an OBDA system designer. 1

In spite of the importance of identification mechanisms in ontology engineering, the Description Logics at the basis of current reasoners do not include modeling features for expressing identification constraints. In this paper, we consider a powerful class of identification constraints, which allow for using roles, inverses, and paths, thus capturing sophisticated forms of identifications often needed in real-world applications. We show that, when used with no limitations, such path-based identification constraints are problematic with respect to effectiveness/efficiency of reasoning. We then propose a restricted form of these constraints, called local, requiring that at least one of the component paths of the concept identifier is a direct property of the concept. We argue that such a restriction is not a severe limitation in practice, and we show that local path-based identification constraints do not increase the complexity of reasoning both in very expressive Description Logics and in the tractable DL-Lite family.

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In this talk, we survey the results of two recent works [1, 2] on a family of expressive extensions of Datalog, called Datalog ± , towards query answering over ontologies. Ontologies are fundamental to the Semantic Web. They also proved to be useful, due to their flexibility and expressive power, in databases, especially in data modeling and data integration. Among ontology formalisms, description logics (DLs) have been playing a prominent role in the last decade, especially in the Semantic Web. Currently, much research on DLs is directed towards scalable and efficient query answering over ontologies. In particular, the DLs of the DL-Lite family [5, 7] are the most common DLs in the Semantic Web and databases that allow for tractable query answering. Rules in Datalog ± are rules in Datalog that additionally admit existentially quantified variables in the head, but on which restrictions are enforced on the body to guarantee desirable decidability and tractability properties. More concretely, Datalog ± rules are tuple-generating dependencies (TGDs) for which the chase [6] does not terminate, but for which query answering is nonetheless decidable in general and tractable in many cases in the data complexity. Datalog ± is divided into the sublanguages of guarded,

Abstract. Ontologies provide a conceptualization of a domain of interest. Nowadays, they are typically represented in terms of Description Logics (DLs), and are seen as the key technology used to describe the semantics of information at various sites. The idea of using ontologies as a conceptual view over data repositories is becoming more and more popular, but for it to become widespread in standard applications, it is fundamental that the conceptual layer through which the underlying data layer is accessed does not introduce a significant overhead in dealing with the data. Based on these observations, in recent years a family of DLs, called DL-Lite, has been proposed, which is specifically tailored to capture basic ontology and conceptual data modeling languages, while keeping low complexity of reasoning and of answering complex queries, in particular when the complexity is measured w.r.t. the size of the data. In this article, we present a detailed account of the major results that have been achieved for the DL-Lite family. Specifically, we concentrate on DL-LiteA,id, an expressive member of this family, present algorithms for reasoning and query answering over DL-LiteA,id ontologies,

In this paper we present Mastro, a Java tool for ontology-based data access (OBDA) developed at the

Abstract. Web portal software is relatively easy to set up and populate from the perspective of the end-user, but it leaves the back-end database devoid of subject domain semantics due to the requirement for a generic implementation. This approach seriously hampers effective search capabilities to retrieve relevant information. Ontology-based data access (OBDA) could, in theory, solve this problem through adding a semantic ‘layer ’ over such web portal implementations. To this end, we provide and demonstrate the proof-of-concept methodology by enhancing the operational National Accessibility Portal of South Africa. We developed the adolena ontology, which is based on both the semantics in the database and augmented with notions from foundational and related domain ontologies. adolena was then made compliant with the OWL2 profile DL-LiteA and mapped to the relational database using the OBDA Plugin for Protégé. Experimentation with OBDA queries unequivocally demonstrates its advantages compared to the portal’s keyword-based search. 1