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Logics for Ontologies (EPSRC Senior Research Fellowship)

1st September 2007 to 28th February 2011

Ontologies help both humans and computer applications to communicate by providing a vocabulary of terms together with formal and computer-processable descriptions of their meanings and the relationships between them. They play a major role in the next-generation World Wide Web (known as the Semantic Web), where they are used to describe the content of Web resources, with the aim of both improving search for human users and making it easier for computer programs to exploit the vast range of information that is available on the Web. Ontologies are also widely used to define specialised vocabularies for use in medicine, biology and other scientific disciplines.

Ontologies are usually developed by human experts, but even for experts the job of defining all the relevant terms is a difficult and time consuming one. It is therefore important to provide "intelligent" tools that support ontology designers. For this reason, many ontology languages, including OWL (the standard language used for Semantic Web ontologies), are based on logics. This provides a formal specification of the meaning of the language and allows tools to use automated reasoning systems, e.g., to check that interactions between descriptions do not lead to logical contradictions. Reasoning systems are also useful when ontologies are deployed in applications, where they could be used, e.g., to determine which Web pages match a search request that uses terms defined in an ontology.

The central role of ontologies in the above mentioned applications brings with it, however, requirements for expressive power and reasoning support which are beyond the capabilities of existing ontology languages and reasoning systems. For example, OWL cannot express the fact that the brother of a person's father is also their uncle, and even for OWL, no practical reasoning system is yet available. Moreover, existing reasoning systems often have difficulties dealing with the very large ontologies that are needed in many realistic applications. The research described in this proposal aims at bridging this gulf between requirements and capabilities; its ultimate goal is the development of logics and reasoning techniques that that will form the foundations of the next generation of ontology languages and reasoning systems.

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