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Ian Horrocks

Bio: Ian Horrocks is an academic researcher from University of Oxford. The author has contributed to research in topics: Ontology (information science) & Description logic. The author has an hindex of 87, co-authored 472 publications receiving 38785 citations. Previous affiliations of Ian Horrocks include The Turing Institute & National and Kapodistrian University of Athens.


Papers
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01 Jan 2004
TL;DR: This document contains a structured informal description of the full set of {owL} language constructs and is meant to serve as a reference for {OWL} users who want to construct {OWl} ontologies.
Abstract: The {W}eb {O}ntology {L}anguage {OWL} is a semantic markup language for publishing and sharing ontologies on the {W}orld {W}ide {W}eb. {OWL} is developed as a vocabulary extension of {RDF} (the {R}esource {D}escription {F}ramework) and is derived from the {DAML}+{OIL} {W}eb {O}ntology {L}anguage. {T}his document contains a structured informal description of the full set of {OWL} language constructs and is meant to serve as a reference for {OWL} users who want to construct {OWL} ontologies.

2,508 citations

Journal ArticleDOI
TL;DR: This paper discusses how the philosophy and features of OWL can be traced back to these older formalisms, with modifications driven by several other constraints on OWL.

1,630 citations

Journal Article
TL;DR: FaCT++ as discussed by the authors implements a tableaux decision procedure for the well known SHOIQ description logic, with additional support for datatypes, including strings and integers, and can be used to provide reasoning services for ontology engineering tools supporting the OWL DL ontology language.
Abstract: This is a system description of the Description Logic reasoner FaCT++. The reasoner implements a tableaux decision procedure for the well known SHOIQ description logic, with additional support for datatypes, including strings and integers. The system employs a wide range of performance enhancing optimisations, including both standard techniques (such as absorption and model merging) and newly developed ones (such as ordering heuristics and taxonomic classification). FaCT++ can, via the standard DIG interface, be used to provide reasoning services for ontology engineering tools supporting the OWL DL ontology language.

1,041 citations

Proceedings Article
02 Jun 2006
TL;DR: A rather elegant tableau-based reasoning algorithm that combines the use of automata to keep track of universal value restrictions with the techniques developed for SHOIQ, which has been adopted as the logical basis for the next iteration of OWL, OWL 1.1.
Abstract: We describe an extension of the description logic underlying OWL-DL, SHOIN, with a number of expressive means that we believe will make it more useful in practice. Roughly speaking, we extend SHOIN with all expressive means that were suggested to us by ontology developers as useful additions to OWL-DL, and which, additionally, do not affect its decidability and practicability. We consider complex role inclusion axioms of the form R o S ⊑ R or S o R ⊑ R to express propagation of one property along another one, which have proven useful in medical terminologies. Furthermore, we extend SHOIN with reflexive, antisymmetric, and irreflexive roles, disjoint roles, a universal role, and constructs ∃R. Self, allowing, for instance, the definition of concepts such as a "narcist". Finally, we consider negated role assertions in Aboxes and qualified number restrictions. The resulting logic is called SROIQ. We present a rather elegant tableau-based reasoning algorithm: it combines the use of automata to keep track of universal value restrictions with the techniques developed for SHOIQ. The logic SROIQ has been adopted as the logical basis for the next iteration of OWL, OWL 1.1.

995 citations

01 Jan 2008
TL;DR: The OWL 2 Web Ontology Language, informally OWL2, is an ontology language for the Semantic Web with formally defined meaning.
Abstract: The OWL 2 Web Ontology Language, informally OWL 2, is an ontology language for the Semantic Web with formally defined meaning. OWL 2 ontologies provide classes, properties, individuals, and data values and are stored as Semantic Web documents. OWL 2 ontologies can be used along with information written in RDF, and OWL 2 ontologies themselves are primarily exchanged as RDF documents. The OWL 2 Document Overview describes the overall state of OWL 2, and should be read before other OWL 2 documents. The meaningful constructs provided by OWL 2 are defined in terms of their structure. As well, a functional-style syntax is defined for these constructs, with examples and informal descriptions. One can reason with OWL 2 ontologies under either the RDF-Based Semantics [OWL 2 RDF-Based Semantics] or the Direct Semantics [OWL 2 Direct Semantics]. If certain restrictions on OWL 2 ontologies are satisfied and the ontology is in OWL 2 DL, reasoning under the Direct Semantics can be implemented using techniques well known in the literature.

957 citations


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Journal ArticleDOI

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08 Dec 2001-BMJ
TL;DR: There is, I think, something ethereal about i —the square root of minus one, which seems an odd beast at that time—an intruder hovering on the edge of reality.
Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality. Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

33,785 citations

01 Jan 2002
TL;DR: An ontology defines a common vocabulary for researchers who need to share information in a domain that includes machine-interpretable definitions of basic concepts in the domain and relations among them.
Abstract: 1 Why develop an ontology? In recent years the development of ontologies—explicit formal specifications of the terms in the domain and relations among them (Gruber 1993)—has been moving from the realm of ArtificialIntelligence laboratories to the desktops of domain experts. Ontologies have become common on the World-Wide Web. The ontologies on the Web range from large taxonomies categorizing Web sites (such as on Yahoo!) to categorizations of products for sale and their features (such as on Amazon.com). The WWW Consortium (W3C) is developing the Resource Description Framework (Brickley and Guha 1999), a language for encoding knowledge on Web pages to make it understandable to electronic agents searching for information. The Defense Advanced Research Projects Agency (DARPA), in conjunction with the W3C, is developing DARPA Agent Markup Language (DAML) by extending RDF with more expressive constructs aimed at facilitating agent interaction on the Web (Hendler and McGuinness 2000). Many disciplines now develop standardized ontologies that domain experts can use to share and annotate information in their fields. Medicine, for example, has produced large, standardized, structured vocabularies such as SNOMED (Price and Spackman 2000) and the semantic network of the Unified Medical Language System (Humphreys and Lindberg 1993). Broad general-purpose ontologies are emerging as well. For example, the United Nations Development Program and Dun & Bradstreet combined their efforts to develop the UNSPSC ontology which provides terminology for products and services (www.unspsc.org). An ontology defines a common vocabulary for researchers who need to share information in a domain. It includes machine-interpretable definitions of basic concepts in the domain and relations among them. Why would someone want to develop an ontology? Some of the reasons are:

4,838 citations

01 Aug 2000
TL;DR: Assessment of medical technology in the context of commercialization with Bioentrepreneur course, which addresses many issues unique to biomedical products.
Abstract: BIOE 402. Medical Technology Assessment. 2 or 3 hours. Bioentrepreneur course. Assessment of medical technology in the context of commercialization. Objectives, competition, market share, funding, pricing, manufacturing, growth, and intellectual property; many issues unique to biomedical products. Course Information: 2 undergraduate hours. 3 graduate hours. Prerequisite(s): Junior standing or above and consent of the instructor.

4,833 citations

Proceedings ArticleDOI
08 May 2007
TL;DR: YAGO as discussed by the authors is a light-weight and extensible ontology with high coverage and quality, which includes the Is-A hierarchy as well as non-taxonomic relations between entities (such as HASONEPRIZE).
Abstract: We present YAGO, a light-weight and extensible ontology with high coverage and quality. YAGO builds on entities and relations and currently contains more than 1 million entities and 5 million facts. This includes the Is-A hierarchy as well as non-taxonomic relations between entities (such as HASONEPRIZE). The facts have been automatically extracted from Wikipedia and unified with WordNet, using a carefully designed combination of rule-based and heuristic methods described in this paper. The resulting knowledge base is a major step beyond WordNet: in quality by adding knowledge about individuals like persons, organizations, products, etc. with their semantic relationships - and in quantity by increasing the number of facts by more than an order of magnitude. Our empirical evaluation of fact correctness shows an accuracy of about 95%. YAGO is based on a logically clean model, which is decidable, extensible, and compatible with RDFS. Finally, we show how YAGO can be further extended by state-of-the-art information extraction techniques.

3,710 citations