Ian Horrocks | |
---|---|
Born | Ian Robert Horrocks 11 March 1958 [1] |
Nationality | British |
Alma mater | University of Manchester (BSc, MSc, PhD) |
Known for | |
Awards | BCS Lovelace Medal (2020). [3] Roger Needham Award (2005) [4] |
Scientific career | |
Fields | |
Institutions | |
Thesis | Optimising tableaux decision procedures for description logics (1997) |
Website | www |
Ian Robert Horrocks FRS [6] is a professor of computer science at the University of Oxford in the UK and a Fellow of Oriel College, Oxford. [7] His research [5] [8] [9] focuses on knowledge representation and reasoning, particularly ontology languages, [10] description logic and optimised tableaux decision procedures. [11] [12] [13]
Horrocks completed his Bachelor of Science (BSc), Master of Science (MSc) [14] and PhD [15] degrees in the Department of Computer Science at the University of Manchester. [1]
After several years as a lecturer, senior lecturer, reader then Professor in Manchester, Horrocks moved to the University of Oxford in 2008. His work on tableau reasoning for very expressive description logics has formed the basis of most description logic reasoning systems in use today, including Racer, FaCT++, [16] HermiT [17] [18] [19] and Pellet. [20]
Horrocks was jointly responsible for development of the OIL and DAML+OIL ontology languages, and he played a central role in the development of the Web Ontology Language (OWL). These languages and associated tools have been used by Open Biomedical Ontologies (OBO) [21] Consortium, the National Cancer Institute (NCI) in America, the United Nations (UN) Food and Agriculture Organization (FAO), the World Wide Web Consortium (W3C) [22] and a range of major corporations and government agencies. [6]
His research is partly funded by the Engineering and Physical Sciences Research Council (EPSRC). [23]
Horrocks served as editor-in-chief of Journal of Web Semantics from 2012 [24] until late 2022. Together with the other editors-in-chief at the time, he resigned from his position at the Elsevier journal, and became editor-in-chief of the newly founded diamond open access journal Transactions on Graph Data and Knowledge. [25] Horrocks also served as program chair of the 1st International Semantic Web Conference (ISWC) in 2002 [26] and as the general chair of ISWC 2010. [27]
In 2020 Horrocks was awarded the BCS Lovelace Medal in recognition of his significant contribution to the advancement of reasoning systems. [3]
Horrocks was elected a Fellow of the Royal Society (FRS) in 2011 [6] and won the Roger Needham Award of the British Computer Society (BCS) in 2005. [4]
In 2017 Horrocks co-founded the University spin-off Oxford Semantic Technologies Limited [28] with two of his colleagues; Bernardo Cuenca Grau and Boris Motik. [29]
The Semantic Web, sometimes known as Web 3.0, is an extension of the World Wide Web through standards set by the World Wide Web Consortium (W3C). The goal of the Semantic Web is to make Internet data machine-readable.
In information science, an ontology encompasses a representation, formal naming, and definitions of the categories, properties, and relations between the concepts, data, or entities that pertain to one, many, or all domains of discourse. More simply, an ontology is a way of showing the properties of a subject area and how they are related, by defining a set of terms and relational expressions that represent the entities in that subject area. The field which studies ontologies so conceived is sometimes referred to as applied ontology.
Description logics (DL) are a family of formal knowledge representation languages. Many DLs are more expressive than propositional logic but less expressive than first-order logic. In contrast to the latter, the core reasoning problems for DLs are (usually) decidable, and efficient decision procedures have been designed and implemented for these problems. There are general, spatial, temporal, spatiotemporal, and fuzzy description logics, and each description logic features a different balance between expressive power and reasoning complexity by supporting different sets of mathematical constructors.
The Web Ontology Language (OWL) is a family of knowledge representation languages for authoring ontologies. Ontologies are a formal way to describe taxonomies and classification networks, essentially defining the structure of knowledge for various domains: the nouns representing classes of objects and the verbs representing relations between the objects.
Patrick John Hayes is a British computer scientist who lives and works in the United States. He is a Senior Research Scientist Emeritus at the Institute for Human and Machine Cognition (IHMC) in Pensacola, Florida.
The ultimate goal of semantic technology is to help machines understand data. To enable the encoding of semantics with the data, well-known technologies are RDF and OWL. These technologies formally represent the meaning involved in information. For example, ontology can describe concepts, relationships between things, and categories of things. These embedded semantics with the data offer significant advantages such as reasoning over data and dealing with heterogeneous data sources.
In computer science, the expressive power of a language is the breadth of ideas that can be represented and communicated in that language. The more expressive a language is, the greater the variety and quantity of ideas it can be used to represent.
The Semantic Web Rule Language (SWRL) is a proposed language for the Semantic Web that can be used to express rules as well as logic, combining OWL DL or OWL Lite with a subset of the Rule Markup Language.
Carole Anne Goble, is a British academic who is Professor of Computer Science at the University of Manchester. She is principal investigator (PI) of the myGrid, BioCatalogue and myExperiment projects and co-leads the Information Management Group (IMG) with Norman Paton.
Alan L. Rector is a retired Professor (emeritus) of Medical Informatics in the Department of Computer Science at the University of Manchester in the UK.
Frank van Harmelen is a Dutch computer scientist and professor in Knowledge Representation & Reasoning in the AI department at the Vrije Universiteit Amsterdam. He was scientific director of the LarKC project (2008-2011), "aiming to develop the Large Knowledge Collider, a platform for very large scale semantic web reasoning."
A semantic reasoner, reasoning engine, rules engine, or simply a reasoner, is a piece of software able to infer logical consequences from a set of asserted facts or axioms. The notion of a semantic reasoner generalizes that of an inference engine, by providing a richer set of mechanisms to work with. The inference rules are commonly specified by means of an ontology language, and often a description logic language. Many reasoners use first-order predicate logic to perform reasoning; inference commonly proceeds by forward chaining and backward chaining. There are also examples of probabilistic reasoners, including non-axiomatic reasoning systems, and probabilistic logic networks.
In computer science, information science and systems engineering, ontology engineering is a field which studies the methods and methodologies for building ontologies, which encompasses a representation, formal naming and definition of the categories, properties and relations between the concepts, data and entities of a given domain of interest. In a broader sense, this field also includes a knowledge construction of the domain using formal ontology representations such as OWL/RDF. A large-scale representation of abstract concepts such as actions, time, physical objects and beliefs would be an example of ontological engineering. Ontology engineering is one of the areas of applied ontology, and can be seen as an application of philosophical ontology. Core ideas and objectives of ontology engineering are also central in conceptual modeling.
Ontology engineering aims at making explicit the knowledge contained within software applications, and within enterprises and business procedures for a particular domain. Ontology engineering offers a direction towards solving the inter-operability problems brought about by semantic obstacles, i.e. the obstacles related to the definitions of business terms and software classes. Ontology engineering is a set of tasks related to the development of ontologies for a particular domain.
The Semantic Sensor Web (SSW) is a marriage of sensor web and semantic Web technologies. The encoding of sensor descriptions and sensor observation data with Semantic Web languages enables more expressive representation, advanced access, and formal analysis of sensor resources. The SSW annotates sensor data with spatial, temporal, and thematic semantic metadata. This technique builds on current standardization efforts within the Open Geospatial Consortium's Sensor Web Enablement (SWE) and extends them with Semantic Web technologies to provide enhanced descriptions and access to sensor data.
The International Semantic Web Conference (ISWC) is a series of academic conferences and the premier international forum for the Semantic Web, Linked Data and Knowledge Graph Community. Here, scientists, industry specialists, and practitioners meet to discuss the future of practical, scalable, user-friendly, and game changing solutions. Its proceedings are published in the Lecture Notes in Computer Science by Springer-Verlag.
Ulrike M. Sattler is a professor of computer science in the information management group of the Department of Computer Science at the University of Manchester and a visiting professor at the University of Oslo.
Pascal Hitzler is a German American computer scientist specializing in Semantic Web and Artificial Intelligence. He is endowed Lloyd T. Smith Creativity in Engineering Chair, one of the Directors of the Institute for Digital Agriculture and Advanced Analytics (ID3A) and Director of the Center for Artificial Intelligence and Data Science (CAIDS) at Kansas State University, and the founding Editor-in-Chief of the Semantic Web journal and the IOS Press book series Studies on the Semantic Web.
Sheila Ann McIlraith is a Canadian computer scientist specializing in artificial intelligence. She is a Professor in the Department of Computer Science, University of Toronto. She is a Canada CIFAR AI Chair, a faculty member of the Vector Institute, and Associate Director and Research Lead of the Schwartz Reisman Institute for Technology and Society.
In knowledge representation and reasoning, a knowledge graph is a knowledge base that uses a graph-structured data model or topology to represent and operate on data. Knowledge graphs are often used to store interlinked descriptions of entities – objects, events, situations or abstract concepts – while also encoding the free-form semantics or relationships underlying these entities.
Jens Lehmann is a computer scientist who works with knowledge graphs and artificial intelligence. He is a principal scientist at Amazon, an honorary professor at TU Dresden, and a fellow of the European Laboratory for Learning and Intelligent Systems. He was formerly a full professor at the University of Bonn, Germany and lead scientist for Conversational AI and Knowledge Graphs at Fraunhofer IAIS.
“All text published under the heading 'Biography' on Fellow profile pages is available under Creative Commons Attribution 4.0 International License.” --Royal Society Terms, conditions and policies at the Wayback Machine (archived 2016-11-11)