From SHIQ and RDF to OWL: The Making of a Web Ontology Language

Horrocks, Ian; Patel‐Schneider, Peter F.; Harmelen, Frank van

doi:10.2139/ssrn.3199003

Cited by 409 publications

(560 citation statements)

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“…The Web Ontology Language (OWL) [7] is the de-facto ontology language for the Semantic Web. It consists of three increasingly expressive sublanguages: OWL Lite, DL and Full.…”

Section: Semantic Web -Owl and Racermentioning

confidence: 99%

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Validating Semistructured Data Using OWL

Sun

Dobbie

et al. 2006

Advances in Web-Age Information Management

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Abstract. Semistructured data has become prevalent in both web applications and database systems. This rapid growth in use makes the design of good semistructured data essential. Formal semantics and automated reasoning tools enable us to reveal the inconsistencies in a semistructured data model and its instances. The Object Relationship Attribute model for Semistructured data (ORA-SS) is a graphical notation for designing and representing semistructured data. This paper presents a methodology of encoding the semantics of ORA-SS in the Web Ontology Language (OWL) and automatically validating the semistructured data design using the OWL reasoning tool -RACER. Our methodology provides automated consistency checking of an ORA-SS data model at both the schema and instance levels.

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“…The Web Ontology Language (OWL) [7] is the de-facto ontology language for the Semantic Web. It consists of three increasingly expressive sublanguages: OWL Lite, DL and Full.…”

Section: Semantic Web -Owl and Racermentioning

confidence: 99%

“…Classes and individuals can be related by properties. We will be using a synatx similar to that presented in [7].…”

Section: Semantic Web -Owl and Racermentioning

confidence: 99%

Validating Semistructured Data Using OWL

Sun

Dobbie

et al. 2006

Advances in Web-Age Information Management

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“…Ontologies in the Semantic Web are mostly expressed using the OWL (2) Web ontology Language [2,3], which has been standardised by W3C. 3 OWL 2 consists of a family of languages containing namely, OWL 2 DL, OWL 2 QL, OWL 2 EL, and OWL 2 RL.…”

Section: Introductionmentioning

confidence: 99%

A Fuzzy Extension to the OWL 2 RL Ontology Language

Stoilos

Venetis

Stamou

2015

The Computer Journal

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Fuzzy extensions to Description Logics (DLs) have gained considerable attention the last decade. So far most works on fuzzy DLs have focused on either very expressive languages, like fuzzy OWL and OWL 2, or on highly inexpressive ones, like fuzzy OWL 2 QL and fuzzy OWL 2 EL. To the best of our knowledge a fuzzy extension to the language OWL 2 RL has not been thoroughly studied so far. This language is very relevant since it combines both adequate expressive power as well as efficient reasoning algorithms which can be realised using rule-based (Datalog) technologies. In contrast to previous fuzzy extensions, a fuzzy extension of OWL 2 RL is not a straightforward task for the following reason. The main motivation of OWL 2 RL is that its axioms can be equivalently represented as Datalog rules. Hence, to achieve our goal we need to investigate which OWL 2 RL axioms when interpreted under the fuzzy setting can be transformed to equivalent fuzzy Datalog rules. We show that this is not, in general, possible for all axioms but we show that this "issue" can to a large extent be alleviated. Moreover, we have performed an experimental evaluation with many well-known ontologies which showed that such axioms are not used so often in practice.

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“…Besides analyzing the service composition, we also verify the feature relations of the web services. We model the features using semantic web technique OWL-DL [6] and verify the feature composition using Proté gé [7] and RacerPro [8].…”

Section: Introductionmentioning

confidence: 99%