Showing papers by "Ian Horrocks published in 2005"

Description Logics as Ontology Languages for the Semantic Web

Abstract: The vision of a Semantic Web has recently drawn considerable attention, both from academia and industry. Description logics are often named as one of the tools that can support the Semantic Web and thus help to make this vision reality.

A tableaux decision procedure for SHOIQ

Abstract: This paper presents a tableaux decision procedure for SHOIQ, the DL underlying OWL DL. To the best of our knowledge, this is the first goal-directed decision procedure for SHOIQ.

Fuzzy OWL: Uncertainty and the Semantic Web.

Abstract: In the Semantic Web context information would be retrieved, processed, shared, reused and aligned in the maximum automatic way possible. Our experience with such applications in the Semantic Web has shown that these are rarely a matter of true or false but rather procedures that require degrees of relatedness, similarity, or ranking. Apart from the wealth of applications that are inherently imprecise, information itself is many times imprecise or vague. For example, the concepts of a “hot” place, an “expensive” item, a “fast” car, a “near” city, are examples of such concepts. Dealing with such type of information would yield more realistic, intelligent and effective applications. In the current paper we extend the OWL web ontology language, with fuzzy set theory, in order to be able to capture, represent and reason with such type of information.

Semantic web architecture: stack or two towers?

Abstract: We discuss language architecture for the Semantic Web, and in particular different proposals for extending this architecture with a rules component. We argue that an architecture that maximises compatibility with existing languages, in particular RDF and OWL, will benefit the development of the Semantic Web, and still allow for forms of closed world assumption and negation as failure.

The fuzzy description logic f-SHIN

Abstract: In the Semantic Web information would be retrieved, processed, combined, shared and reused in the maximum automatic way possible. Obviously, such procedures involve a high degree of uncertainty and imprecision. For example ontology alignment or information retrieval are rarely true or false procedures but usually involve confidence degrees or provide rankings. Furthermore, it is often the case that information itself is imprecise and vague like the concept of a "tall" person, a "hot" place and many more. In order to be able to represent and reason with such type of information in the Semantic Web (SW), as well as, enhance SW applications we present an extension of the Description Logic SHIN with fuzzy set theory. We present the semantics as well as detailed reasoning algorithms for the extended language.

Keys, nominals, and concrete domains

Abstract: Many description logics (DLs) combine knowledge representation on an abstract, logical level with an interface to "concrete" domains like numbers and strings with built-in predicates such as <, +, and prefix-of. These hybrid DLs have turned out to be useful in several application areas, such as reasoning about conceptual database models. We propose to further extend such DLs with key constraints that allow the expression of statements like "US citizens are uniquely identified by their social security number". Based on this idea, we introduce a number of natural description logics and perform a detailed analysis of their decidability and computational complexity. It turns out that naive extensions with key constraints easily lead to undecidability, whereas more careful extensions yield NExp-Time-complete DLs for a variety of useful concrete domains.

OWL: a description logic based ontology language (extended abstract)

Abstract: Description Logics (DLs) are a family of class (concept) based knowledge representation formalisms. They are characterised by the use of various constructors to build complex concepts from simpler ones, an emphasis on the decidability of key reasoning tasks, and by the provision of sound, complete and (empirically) tractable reasoning services. Although they have a range of applications (e.g., reasoning with database schemas and queries [1,2]), DLs are perhaps best known as the basis for ontology languages such as OIL, DAML+OIL and OWL [3]. The decision to base these languages on DLs was motivated by a requirement not only that key inference problems (such as class satis.ability and subsumption) be decidable, but that "practical" decision procedures and "efficient" implemented systems also be available.

OWL: a description logic based ontology language

Abstract: We present a version of the CCP paradigm, which is both distributed and probabilistic. We consider networks with a fixed number of nodes, each of them possessing a local and independent constraint store. While locally the computations evolve asynchronously, following the usual rules of (probabilistic) CCP, the communications among different nodes are synchronous. There are channels, and through them different objects can be exchanged: constraints, agents and channel themselves. In addition, all this activities are embedded in a probabilistic scheme based on a discrete model of time, both locally and globally. Finally we enhance the language with the capability of performing an automatic remote synchronization of variables belonging to different constraint stores.

The OWL instance store: system description

Abstract: We describe the instance store, a system for reasoning about individuals (i.e., instances of classes) in OWL ontologies. By using a hybrid reasoner/database architecture, our system is able to perform efficient reasoning over large volumes of instance data, as required by many real world applications.

A little semantic web goes a long way in biology

Abstract: We show how state-of-the-art Semantic Web technology can be used in e-Science, in particular, to automate the classification of proteins in biology. We show that the resulting classification was of comparable quality to that performed by a human expert, and how investigations using the classified data even resulted in the discovery of significant information that had previously been overlooked, leading to the identification of a possible drug-target.

Applications of description logics: state of the art and research challenges

Abstract: Description Logics (DLs) are a family of class based knowledge representation formalisms characterised by the use of various constructors to build complex classes from simpler ones, and by an emphasis on the provision of sound, complete and (empirically) tractable reasoning services. They have a range of applications, but are mostly widely known as the basis for ontology languages such as OWL. The increasing use of DL based ontologies in areas such as e-Science and the Semantic Web is, however, already stretching the capabilities of existing DL systems, and brings with it a range of challenges for future research.

A Fuzzy Description Logic for Multimedia Knowledge Representation

Abstract: Today quite a lot of multimedia systems and applications use knowledge representation formalisms to encode and reason with knowledge that exists within the multimedia documents. The goal of this direction is to narrow the semantic gab between the content of a multimedia object, as perceived by a human being, and as “viewed” by an information system. Ontologies are quite often used to capture such a knowledge. Ontology languages are based on Description Logics, which though they are expressive enough, they lack the ability to encode and reason with imprecise knowledge. To this end we extend the DL language SI with fuzzy set theory and provide sound and complete reasoning algorithms for the extended language.

The Irresistible SRIQ.

Abstract: Motivated primarily by medical terminology applications, the prominent DL SHIQ has already been extended to a DL with complex role inclusion axioms of the form R ◦ S v R or S ◦ R v R, called RIQ, and the SHIQ tableau algorithm has been extended to handle such inclusions. This paper further extends RIQ and its tableau algorithm with important expressive means that are frequently requested in ontology applications, namely with reflexive, symmetric, transitive, and irreflexive roles, disjoint roles, and the construct ∃R.Self, allowing, for instance, the definition of concepts such as a “narcist”. Furthermore, we extend the algorithm to cover Abox reasoning extended with negated role assertions. The resulting logic is called SRIQ.

Ordering heuristics for description logic reasoning

Abstract: We present a new architecture for Description Logic implementations, a range of new optimisation techniques and an empirical analysis of their effectiveness.

OWL-Eu: adding customised datatypes into OWL

Abstract: Although OWL is rather expressive, it has a very serious limitation on datatypes; i.e., it does not support customised datatypes. It has been pointed out that many potential users will not adopt OWL unless this limitation is overcome. Accordingly, the Semantic Web Best Practices and Development Working Group sets up a task force to address this issue. This paper makes the following two contributions: (i) it provides a brief summary of OWL-related datatype formalisms, and (ii) it provides a decidable extension of OWL DL, called OWL-Eu, that supports customised datatypes.

Description logics in ontology applications

Abstract: Description Logics (DLs) are a family of logic based knowledge representation formalisms. Although they have a range of applications (e.g., configuration and information integration), they are perhaps best known as the basis for widely used ontology languages such as OWL (now a W3C recommendation). This decision was motivated by a requirement that key inference problems be decidable, and that it should be possible to provide reasoning services to support ontology design and deployment. Such reasoning services are typically provided by highly optimised implementations of tableaux decision procedures. In this talk I will introduce both the logics and decision procedures that underpin modern ontology languages, and the implementation techniques that have enabled state of the art systems to be effective in applications in spite of the high worst case complexity of key inference problems.

Optimised classification for taxonomic knowledge bases

Abstract: Many legacy ontologies are now being translated into Description Logic (DL) based ontology languages in order to take advantage of DL based tools and reasoning services. The resulting DL Knowledge Bases (KBs) are typically of large size, but have a very simple structure, i.e., they consist mainly of shallow taxonomies. The classification algorithms used in state-of-the-art DL reasoners may not deal well with such KBs In this paper we propose an optimisation which dramatically speeds-up classification for such KBs.

A Fuzzy Extension of SWRL.

Abstract: Experience in using ontologies and rules in applications has shown that in many cases we would like to extend their representational and reasoning capabilities to deal with vague or imprecise knowledge. For example, multimedia applications have highlighted the need to extend representation languages with capabilities which allow for the treatment of the inherent imprecision in multimedia object representation, matching, detection and retrieval. Unfortunately, neither OWL nor SWRL provides such capabilities. In order to capture imprecision in rules, we propose fuzzy extensions of SWRL (SWRL is proposed by the Joint US/EU ad hoc Agent Markup Language Committee., the reader is referred to [HPSB04] for full details of the model-theoretic semantics and abstract syntax of SWRL.). In this extension OWL facts (axioms relating to individuals) can include a specification of the “degree” (a truth value between 0 and 1) of confidence with which we assert that an individual (resp. pair of individuals) is an instance of a given class (resp. property); and SWRL atoms can include a “weight” (a truth value between 0 and 1) that represents the “importance” of the atom in a rule.The syntax extends the existing abstract syntax for SWRL, while the semantics is based on the theory of fuzzy sets [Zad65]. For example, the following fuzzy rule asserts that if one has a parent that is happy, then one is likely (with the weight 0.8) to be happy:

Description logics in ontology applications

Abstract: Description Logics (DLs) are a family of logic based knowledge representation formalisms. Although they have a range of applications (e.g., configuration and information integration), they are perhaps best known as the basis for widely used ontology languages such as OWL (now a W3C recommendation). This decision was motivated by a requirement that key inference problems be decidable, and that it should be possible to provide reasoning services to support ontology design and deployment. Such reasoning services are typically provided by highly optimised implementations of tableaux decision procedures; these have proved to be effective in applications in spite of the high worst case complexity of key inference problems. The increasing use of DL based ontologies in areas such as e-Science and the Semantic Web is, however, already stretching the capabilities of existing DL systems, and brings with it a range of research challenges.

Handling Cyclic Conjunctive Queries

Abstract: Query containment for conjunctive queries is the problem of checking whether a query q is contained in another query q′ with respect to a given Description Logic schema S. It is known that query containment can also be used to answer queries. Query containment is important in many areas, including information integration, query optimisation, and reasoning about Entity-Relationship diagrams, while query languages that allow the use of variables and individuals in a query, such as conjunctive queries, become a more and more important topic in the area of ontology development and the Semantic Web. We analyse an existing conjunctive query containment algorithm [1] for DLRreg and highlight cases, where cyclic queries are not handled correctly. The suggested improvements for DLR [2] are not enough for DLRreg . The main problem is that the algorithm depends on a strict tree-model property, which can be disturbed by transitivity, inverse roles or the role hierarchy. E.g., consider the boolean query q: 〈〉 ← a: ∃ [$1]s, with a a constant and the cyclic boolean query q′: 〈〉 ← s(〈x, y〉) ∧ t|$2,$1(〈y, x〉) with x and y existentially quantified variables and let S be {s v t} for s, t roles of arity 2. Since x and y are only existentially quantified, K |= q v q′. However, Calvanese et al. argue that cycles cannot be expressed in the schema itself and therefore the variables in q′ have to be replaced by constants or variables from q, i.e., a here. As a result, the algorithms answers K 6|= q v q′. There are more examples, e.g., for transitivity, to support this claim.

D2.5.2 Report on Query Language Design and Standardisation

Abstract: EU-IST Network of Excellence (NoE) IST-2004-507482 KWEB Deliverable D2.5.2 (WP2.5) In the progress of realising the Semantic Web, developing and supporting Semantic Web query languages are among the most useful and important research problems. In [PFT + 04], we have provided a unified framework for OWL-based rule and query lang uages. In this report, we focus on the problems of query answering for Semantic Web query languages (such as RDF, OWL DL and OWL-E) in the OWL-QL specification. Keyword list: description logics, ontology language, query language, RDF, OWL DL, OWL-E

Description logics: OWL and DAML + OIL

Abstract: In this chapter, we introduce Description Logics. These logics have achieved mainstream credibility as ontology languages by forming the basis of the W3C Web Ontology Language OWL, and its predecessor, DAML + OIL. From a case study, we explain how the rich expressivity of OWL can be used to model the complexities of biology and bioinformatics. We discuss automated reasoning technologies and the roles that they can play in supporting the process of building ontologies. Keywords: ontology; description logic; OWL; modelling; oiled; protege

Owl Rules: A Proposal and Prototype Implementation

Abstract: Although the OWL Web Ontology Language adds considerable expressive power to the Semantic Web it does have expressive limitations, particularly with respect to what can be said about properties. We present SWRL (the SemanticWeb Rules Language), a Horn clause rules extension to OWL that overcomes many of these limitations. SWRL extends OWL in a syntactically and semantically coherent manner: the basic syntax for SWRL rules is an extension of the abstract syntax for OWL DL and OWL Lite; SWRL rules are given formal meaning via an extension of the OWL DL model-theoretic semantics; SWRL rules are given an XML syntax based on the OWL XML presentation syntax; and a mapping from SWRL rules to RDF graphs is given based on the OWL RDF/XML exchange syntax. We discuss the expressive power of SWRL, showing that the ontology consistency problem is undecidable, provide several examples of SWRL usage, and discuss a prototype implementation of reasoning support for SWRL.

Methods for Approximate Reasoning

Abstract: EU-IST Network of Excellence (NoE) IST-2004-507482 KWEB Deliverable D2.1.2 (WP2.1) This deliverable shows examples about approximating symbolic inference engines in a Semantic Web environment. Approaches of language weakening, knowledge compilation, and approximated deduction are presented. The last one is evaluated in practical applications with mixed results. Keyword list: state-of-the-art, scalability, approximation, modularisation, distribution, symbolic reasoning Copyright c © 2005 The contributors Document Identifier KWEB/2004/D2.1.2/v1.2 Project KWEB EU-IST-2004-507482 Version v1.2 Date January 30, 2005 State draft Distribution public Knowledge Web Consortium This document is part of a research project funded by the IST Programme of the Commission of the European Communities as project number IST-2004-507482. University of Innsbruck (UIBK) Coordinator Institute of Computer Science Technikerstrasse 13 A-6020 Innsbruck Austria Contact person: Dieter Fensel E-mail address: dieter.fensel@uibk.ac.at Ecole Polytechnique Federale de Lausanne (EPFL) Computer Science Department Swiss Federal Institute of Technology IN (Ecublens), CH-1015 Lausanne Switzerland Contact person: Boi Faltings E-mail address: boi.faltings@epfl.ch France Telecom (FT) 4 Rue du Clos Courtel 35512 Cesson Sevigne France. PO Box 91226 Contact person : Alain Leger E-mail address: alain.leger@rd.francetelecom.com Freie Universitat Berlin (FU Berlin) Takustrasse 9 14195 Berlin Germany Contact person: Robert Tolksdorf E-mail address: tolk@inf.fu-berlin.de Free University of Bozen-Bolzano (FUB) Piazza Domenicani 3 39100 Bolzano Italy Contact person: Enrico Franconi E-mail address: franconi@inf.unibz.it Institut National de Recherche en Informatique et en Automatique (INRIA) ZIRST 655 avenue de l’Europe Montbonnot Saint Martin 38334 Saint-Ismier France Contact person: Jerome Euzenat E-mail address: Jerome.Euzenat@inrialpes.fr Centre for Research and Technology Hellas / Informatics and Telematics Institute (ITI-CERTH) 1st km Thermi Panorama road 57001 Thermi-Thessaloniki Greece. Po Box 361 Contact person: Michael G. Strintzis E-mail address: strintzi@iti.gr Learning Lab Lower Saxony (L3S) Expo Plaza 1 30539 Hannover Germany Contact person: Wolfgang Nejdl E-mail address: nejdl@learninglab.de National University of Ireland Galway (NUIG) National University of Ireland Science and Technology Building University Road Galway Ireland Contact person: Christoph Bussler E-mail address: chris.bussler@deri.ie The Open University (OU) Knowledge Media Institute The Open University Milton Keynes, MK7 6AA United Kingdom Contact person: Enrico Motta E-mail address: e.motta@open.ac.uk Universidad Politecnica de Madrid (UPM) Campus de Montegancedo sn 28660 Boadilla del Monte Spain Contact person: Asuncion Gomez Perez E-mail address: asun@fi.upm.es University of Karlsruhe (UKARL) Institut fur Angewandte Informatik und Formale Beschreibungsverfahren AIFB Universitat Karlsruhe D-76128 Karlsruhe Germany Contact person: Rudi Studer E-mail address: studer@aifb.uni-karlsruhe.de University of Liverpool (UniLiv) Chadwick Building, Peach Street L697ZF Liverpool United Kingdom Contact person: Michael Wooldridge E-mail address: M.J.Wooldridge@csc.liv.ac.uk University of Manchester (UoM) Room 2.32. Kilburn Building, Department of Computer Science, University of Manchester, Oxford Road Manchester, M13 9PL United Kingdom Contact person: Carole Goble E-mail address: carole@cs.man.ac.uk University of Sheffield (USFD) Regent Court, 211 Portobello street S14DP Sheffield United Kingdom Contact person: Hamish Cunningham E-mail address: hamish@dcs.shef.ac.uk University of Trento (UniTn) Via Sommarive 14 38050 Trento Italy Contact person: Fausto Giunchiglia E-mail address: fausto@dit.unitn.it Vrije Universiteit Amsterdam (VUA) De Boelelaan 1081a 1081HV. Amsterdam The Netherlands Contact person: Frank van Harmelen E-mail address: Frank.van.Harmelen@cs.vu.nl Vrije Universiteit Brussel (VUB) Pleinlaan 2, Building G1

Introducing Customised Datatypes and Datatype Predicates into OWL.

Abstract: Although OWL is rather expressive, it has a very serious limitation on datatypes; i.e., it does not support customised datatypes. It has been pointed out that many potential users will not adopt OWL unless this limitation is overcome, and the W3C Semantic Web Best Practices and Deployment Working Group has set up a task force to address this issue. This paper provides a solution for this issue by presenting two decidable datatype extensions of OWL DL, namely OWL-Eu and OWL-E. OWL-Eu provides a minimal extension of OWL DL to support customised datatypes, while OWL-E extends OWL DL with both customised datatypes and customised datatype predicates.

Why to use this L A T E Xfi le

Abstract: In this paper, we will argue that it is reasonable to use the LAT E Xfi le “submission.tex” for submissions to DL2005. Certainly, one can dispense with an abstract since the papers are quite short anyway.