Description logics are a family of knowledge representation formalisms that are descended from semantic networks and frames via the system Kl-one. During the last decade, it has been shown that the important reasoning problems (like subsumption and satisfiability) in a great variety of description logics can be decided using tableau-like algorithms. This is not very surprising since description logics have turned out to be closely related to propositional modal logics and logics of programs (such as propositional dynamic logic), for which tableau procedures have been quite successful. Nevertheless, due to different underlying intuitions and applications, most description logics differ significantly from run-of-the-mill modal and program logics. Consequently, the research on tableau algorithms in description logics led to new techniques and results, which are, however, also of interest for modal logicians. In this article, we will focus on three features that play an important role in description logics (number restrictions, terminological axioms, and role constructors), and show how they can be taken into account by tableau algorithms.

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Taxonomies are an important part of conceptual modeling. They provide substantial structural information, and are typically the key elements in integration efforts, however there has been little guidance as to what makes a proper taxonomy. We have adopted several notions from the philosophical practice of formal ontology, and adapted them for use in information systems. These tools, identity, essence, unity, and dependence, provide a solid logical framework within which the properties that form a taxonomy can be analyzed. This analysis helps make intended meaning more explicit, improving human understanding and reducing the cost of integration.

The notion of class is ubiquitous in computer science and is central in many formalisms for the representation of structured knowledge used both in knowledge representation and in databases. In this paper we study the basic issues underlying such representation formalisms and single out both their common characteristics and their distinguishing features. Such investigation leads us to propose a unifying framework in which we are able to capture the fundamental aspects of several representation languages used in different contexts. The proposed formalism is expressed in the style of description logics, which have been introduced in knowledge representation as a means to provide a semantically well-founded basis for the structural aspects of knowledge representation systems. The description logic considered in this paper is a subset of first order logic with nice computational characteristics. It is quite expressive and features a novel combination of constructs that has not been studied before. The distinguishing constructs are number restrictions, which generalize existence and functional dependencies, inverse roles, which allow one to refer to the inverse of a relationship, and possibly cyclic assertions, which are necessary for capturing real world

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Ontologies are set to play a key role in the Semantic Web, and several web ontology languages, like DAML+OIL, are based on DLs.

UML is the de-facto standard formalism for software design and analysis. To support the design of large-scale industrial applications, sophisticated CASE tools are available on the market, that provide a user-friendly environment for editing, storing, and accessing multiple UML diagrams. It would be highly desirable to equip such CASE tools with automated reasoning capabilities in order to detect relevant formal properties of UML diagrams, such as inconsistencies or redundancies. With regard to this issue, we consider UML class diagrams, which are one of the most important components of UML, and we address the problem of reasoning on such diagrams. We resort to several results developed in the eld of Description Logics (DLs), a family of logics that admit decidable reasoning procedures.

In this paper we present i.com, a tool for intelligent conceptual modelling. i.com allows for the specification of multiple EER diagrams and inter- and intra-schema constraints. Complete

Answering queries using views amounts to computing the answer to a query having information only on the extension of a set of precomputed queries (views). This problem is relevant in several fields, such as information integration, query optimization, and data warehousing, and has been studied recently in different settings. In this paper we address answering queries using views in a setting where intensional knowledge about the domain is represented using a very expressive Description Logic equipped with n-ary relations, and queries are nonrecursive datalog queries whose predicates are the concepts and relations that appear in the Description Logic knowledge base. We study the problem under different assumptions, namely, closed and open domain, and sound, complete, and exact information on view extensions. We show that under the closed domain assumption, in which the set of all objects in the knowledge base coincides with the set of objects stored in the views, answering queries using views is already intractable. We show also that under the open domain assumption the problem is decidable in double exponential time.

The recently introduced series of description logics under the common moniker ‘DL-Lite ’ has attracted attention of the description logic and semantic web communities due to the low computational complexity of inference, on the one hand, and the ability to represent conceptual modeling formalisms, on the other. The main aim of this article is to carry out a thorough and systematic investigation of inference in extensions of the original DL-Lite logics along five axes: by (i) adding the Boolean connectives and (ii) number restrictions to concept constructs, (iii) allowing role hierarchies, (iv) allowing role disjointness, symmetry, asymmetry, reflexivity, irreflexivity and transitivity constraints, and (v) adopting or dropping the unique name assumption. We analyze the combined complexity of satisfiability for the resulting logics, as well as the data complexity of instance checking and answering positive existential queries. Our approach is based on embedding DL-Lite logics in suitable fragments of the one-variable first-order logic, which provides useful insights into their properties and, in particular, computational behavior.