Web Ontology Language (OWL)

Web Ontology Language (OWL) is a markup language for publishing and sharing data using ontologies on the Internet. OWL is a vocabulary extension of the Resource Description Framework (RDF) and is derived from the [[DAML+OIL]] Web Ontology Language (see also DAML and OIL). Together with RDF and other components, these tools make up the Semantic Web project.

OWL represents the meanings of terms in vocabularies and the relationships between those terms in a way that is suitable for processing by software.

The OWL specification is maintained by the World Wide Web Consortium (W3C).

OWL is seen as a major technology for the future implementation of a Semantic Web. OWL was designed specifically to provide a common way to process the content of web information. The language is intended to be read by computer applications instead of by humans. And because OWL is written in XML, OWL information can be easily exchanged between different types of computers using different operating systems, and application languages. OWL’s main purpose will be to provide standards that provide a framework for asset management, enterprise integration and the sharing and reuse of data on the Web. OWL was developed mainly because it has more facilities for expressing meaning and semantics than XML, RDF, and RDF-S, and thus OWL goes beyond these languages in its ability to represent machine interpretable content on the web. [1]

OWL currently has three flavors (sometimes also referred to as ’species’): OWL Lite, OWL DL, and OWL Full. These flavors incorporate different features, and in general it is easier to reason about OWL Lite than OWL DL and OWL DL than OWL Full. OWL Lite and OWL DL are constructed in such a way that every statement can be decided in finite time; OWL Full can contain endless ‘loops’.

History of OWL

A number of research efforts during the mid to late 1990s explored how the idea of knowledge representation from AI could be made useful on the World Wide Web. These included languages based on HTML (called SHOE), XML (called XOL, later OIL), and various frame-based KR languages and knowledge acquisition approaches.

OWL DL is based in part on the description logic and also on a number of earlier KR systems known as frame-based systems. Its subset OWL Lite is based on the less expressive logic . All reasoning tasks in both OWL DL and OWL Lite can be reduced to knowledge based (KB) satisfiablity. OWL Full operates outside the bounds of Description Logic, allowing more power and expressivity and having less constraints on use, but at the cost of decidability. (OWL Full’s semantics is based on the Semantics of RDF) OWL is encoded in RDF/XML documents.

The OWL Language is a revision of the DAML+OIL web ontology language incorporating learnings from the design and application use of DAML+OIL. DAML+OIL was developed by a group called the “US/UK ad hoc Joint Working Group on Agent Markup Languages” which was jointly funded by the US Defense Advanced Research and Development Agency (DARPA) under the DAML program and the EU’s IST funding project.

The World Wide Web Consortium created the “Web Ontology Working Group” which began work on November 1, 2001 chaired by James Hendler and Guus Shreiber. The first working drafts of the abstract syntax, reference and synopsis were published in July 2002. The OWL documents became a formal W3C recommendation on February 10, 2004 and the working group was disbanded on May 31, 2004.[3]

Within the working group, effort to identify design goals and requirements was led by Jeff Heflin. Some of the requirements were contributed by Deborah McGuinness based upon over a decade of work in building ontology-based systems. Other requirements were identified as part of Heflin’s Ph.D. thesis work in building a prototype Semantic Web system. The other members of the working group contributed over 25 use cases, which were later boiled down into defining a set of use cases. (For example, a draft version of the Corporate Web Site Management section was written by Michael Smith, a use case on agent-based computing was developed by Tim Finin, etc.).[4]

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