# Web Ontology Language

The Web Ontology Language (OWL) is a family of knowledge representation languages for authoring ontologies, and is endorsed by the World Wide Web Consortium.[1] This family of languages is based on two (largely, but not entirely, compatible) semantics: OWL DL and OWL Lite semantics are based on Description Logics,[2] which have attractive and well-understood computational properties, while OWL Full uses a novel semantic model intended to provide compatibility with RDF Schema. OWL ontologies are most commonly serialized using RDF/XML syntax. OWL is considered one of the fundamental technologies underpinning the Semantic Web, and has attracted both academic and commercial interest.

In October 2007, a new W3C working group[3] was started to extend OWL with several new features as proposed in the OWL 1.1 member submission.[4] This new version, called OWL 2, has already found its way into semantic editors such as Protégé and semantic reasoners such as Pellet[5] and FaCT++[6]

## History

There is a long history of ontological development in philosophy and computer science. Since the 1990s, a number of research efforts have explored how the idea of knowledge representation (KR) 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.

The OWL Language is a research-based[7] revision of the DAML+OIL web ontology language. 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 Projects 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 chaired by James Hendler and Guus Schreiber. 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.[8]

## OWL Topics

### OWL ontologies

The data described by an OWL ontology is interpreted as a set of "individuals" and a set of "property assertions" which relate these individuals to each other. An OWL ontology consists of a set of axioms which place constraints on sets of individuals (called "classes") and the types of relationships permitted between them. These axioms provide semantics by allowing systems to infer additional information based on the data explicitly provided. For example, an ontology describing families might include axioms stating that a "hasMother" property is only present between two individuals when "hasParent" is also present, and individuals of class "HasTypeOBlood" are never related via "hasParent" to members of the "HasTypeABBlood" class. If it is stated that the individual Harriet is related via "hasMother" to the individual Sue, and that Harriet is a member of the "HasTypeOBlood" class, then it can be inferred that Sue is not a member of "HasTypeABBlood". A full introduction to the expressive power of the OWL language(s) is provided in the W3C's OWL Guide.

### Relation to description logics

Previous attempts to build large ontologies have been plagued by a lack of clear definitions. For example, one review found 18 different uses of the "Is-A" relationship.[9] OWL tries to avoid this by having an explicit logical basis for the language, based on Description Logics.

Description logics (DLs) are a family of logics that are decidable fragments of first-order logic. The semantics for OWL is given through translation to a particular DL. Therefore OWL is both a syntax for describing and exchanging ontologies, and has a formally defined semantics that gives the meaning. For example, OWL DL corresponds to the $\mathcal{SHOIN} (D)$ description logic, while OWL 2 corresponds to the $\mathcal{SROIQ} (D)$ logic. In addition, sound, complete, and terminating reasoners (i.e. systems which are guaranteed to derive every consequence of the knowledge in an ontology) exist for many DLs including those underlying OWL.

### Sublanguages

The W3C-endorsed OWL specification includes the definition of three variants of OWL, with different levels of expressiveness.

• OWL Lite was originally intended to support those users primarily needing a classification hierarchy and simple constraints. For example, while it supports cardinality constraints, it only permits cardinality values of 0 or 1. It was hoped that it would be simpler to provide tool support for OWL Lite than its more expressive relatives, allowing quick migration path for systems utilizing thesauri and other taxonomies. In practice, however, most of the expressiveness constraints placed on OWL Lite amount to little more than syntactic inconveniences: most of the constructs available in OWL DL can be built using complex combinations of OWL Lite features. Development of OWL Lite tools has thus proven almost as difficult as development of tools for OWL DL, and OWL Lite is not widely used.
• OWL DL was designed to provide the maximum expressiveness possible while retaining computational completeness (all conclusions are guaranteed to be computed), decidability (all computations will finish in finite time), and the availability of practical reasoning algorithms. OWL DL includes all OWL language constructs, but they can be used only under certain restrictions (for example, number restrictions may not be placed upon properties which are declared to be transitive). OWL DL is so named due to its correspondence with description logic, a field of research that has studied the logics that form the formal foundation of OWL.
• OWL Full is based on a different semantics from OWL Lite or OWL DL, and was designed to preserve some compatibility with RDF Schema. For example, in OWL Full a class can be treated simultaneously as a collection of individuals and as an individual in its own right; this is not permitted in OWL DL. OWL Full allows an ontology to augment the meaning of the pre-defined (RDF or OWL) vocabulary. It is unlikely that any reasoning software will be able to support complete reasoning for OWL Full.

Each of these sublanguages is a syntactic extension of its simpler predecessor. The following set of relations hold. Their inverses do not.

• Every legal OWL Lite ontology is a legal OWL DL ontology.
• Every legal OWL DL ontology is a legal OWL Full ontology.
• Every valid OWL Lite conclusion is a valid OWL DL conclusion.
• Every valid OWL DL conclusion is a valid OWL Full conclusion.

In OWL 2, there are three sublanguages of of the language. OWL 2 EL is a fragment that has polynomial time reasoning complexity; OWL 2 QL is designed to enable easier access and query to data stored in databases; OWL 2 RL is a rule subset of OWL 2.

### Open World Assumption

OWL uses Open World Assumption, in contrast to SQL and Prolog, which adopts Closed World Assumption. Under this Open World Assumption, if a statement cannot be proved to be true using current knowledge, we cannot draw the conclusion that the statement is false.

## The acronym

The natural acronym for Web Ontology Language would be WOL instead of OWL. Although the character Owl from Winnie the Pooh wrote his name WOL, the acronym OWL was proposed without reference to that character, as an easily pronounced acronym that would yield good logos, suggest wisdom, and honor William A. Martin's One World Language KR project from the 1970s. And, to quote Guus Schreiber, "Why not be inconsistent in at least one aspect of a language which is all about consistency?"

## Example ontologies

Some existing OWL ontologies[10] may be browsed using an editor such as Protégé-OWL to edit the ontologies posted at the Protégé web site.[11]

There is a large collection of biomedical ontologies available through the OBO Foundry[12], which are available on their download page[13], as well a number of others hosted at the NCBO BioPortal.[14]

Other ontologies can be found by searching for appropriate search terms with the filetype set to ".owl" or ".rdf" or by using the Swoogle semantic web search engine.