Web Ontology Language

Web Ontology Language
Name	Web Ontology Language
Paradigm	Declarative programming
Designer	World Wide Web Consortium
Latest release version	OWL 2
Influenced by	RDF Schema, DAML+OIL, Description logic
Influenced	Semantic Web Rule Language, SPARQL

Web Ontology Language. It is a family of knowledge representation languages designed for authoring ontologies within the Semantic Web framework. Developed under the auspices of the World Wide Web Consortium, it provides a formal framework for defining structured, machine-interpretable vocabularies. These vocabularies enable sophisticated automated reasoning about data, facilitating greater interoperability and intelligence across distributed information systems.

Overview

The primary purpose is to formally describe the meaning of information in web documents and data sources, going beyond the basic relational structures of Resource Description Framework. It is built upon the foundational standards of the World Wide Web Consortium, including RDF Schema and XML Schema Definition. The language allows users to define complex classes, properties, and relationships between entities, creating a shared conceptualization of a domain. This formalization is crucial for enabling applications in fields like bioinformatics, e-commerce, and knowledge management to process information with a deeper understanding of its context and meaning.

Syntax and structure

It is expressed using multiple syntaxes to cater to different tools and communities. The primary exchange syntax is RDF/XML, which serializes ontologies using the Extensible Markup Language format defined for the Resource Description Framework. For human readability, alternative syntaxes like Turtle and Manchester Syntax are widely used. Structurally, an ontology consists of a header and a series of axioms, which include declarations for classes, properties, and individuals. These axioms can define hierarchies using rdfs:subClassOf, specify property characteristics like transitivity, and assert equivalences between entities, forming a rich logical structure.

Semantics and reasoning

The formal meaning is defined by mapping its constructs to expressions in description logic, a decidable fragment of first-order logic. This mapping provides a precise model-theoretic semantics, allowing for the use of automated reasoning systems. Tools like Pellet, HermiT, and FaCT++ can perform tasks such as checking ontology consistency, classifying subsumption hierarchies, and inferring new knowledge not explicitly stated. The language specification defines several profiles, including OWL 2 EL, which is optimized for large-scale biomedical ontologies like the SNOMED CT clinical terminology.

Applications and use cases

A major application domain is life sciences, where it is used to represent complex biological knowledge in resources like the Gene Ontology and the National Cancer Institute Thesaurus. In healthcare, it supports semantic interoperability for electronic health records through standards like the HL7 Fast Healthcare Interoperability Resources. Within government data initiatives, such as data.gov, it helps publish linked open data. Commercial enterprises use it for integrating heterogeneous data sources, enhancing search engine capabilities, and powering intelligent agents. The BBC utilized it to structure content for its dynamic website.

Related standards and languages

It is a core component of the Semantic Web stack, building directly upon the Resource Description Framework and RDF Schema. The query language SPARQL is used to interrogate knowledge bases. For defining rules, the Semantic Web Rule Language provides complementary expressivity. Earlier ontology languages that influenced its design include the DARPA Agent Markup Language and the combined DAML+OIL. Simpler vocabulary languages like Simple Knowledge Organization System offer a lightweight alternative for basic classification needs, while Common Logic provides a more expressive framework outside the web context.

Development and history

Development began in the early 2000s through the work of the World Wide Web Consortium's Web Ontology Working Group. The first version, now known as OWL 1, became a formal World Wide Web Consortium Recommendation in 2004, synthesizing ideas from several predecessor projects including the United States DARPA's DAML+OIL initiative. A revised version, OWL 2, was standardized in 2009, introducing new features and optimized reasoning profiles. The ongoing evolution of the language is guided by the World Wide Web Consortium OWL Working Group, with input from academic institutions like the University of Manchester and industrial research labs.

Category:World Wide Web Consortium standards Category:Semantic Web Category:Knowledge representation