# Web Ontology Language

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.
Ontologies resemble class hierarchies in object-oriented programming but there are several critical differences. Class hierarchies are meant to represent structures used in source code that evolve fairly slowly (perhaps with monthly revisions) whereas ontologies are meant to represent information on the Internet and are expected to be evolving almost constantly. Similarly, ontologies are typically far more flexible as they are meant to represent information on the Internet coming from all sorts of heterogeneous data sources. Class hierarchies on the other hand tend to be fairly static and rely on far less diverse and more structured sources of data such as corporate databases.
The OWL languages are characterized by formal semantics. They are built upon the World Wide Web Consortium's (W3C) standard for objects called the Resource Description Framework (RDF). OWL and RDF have attracted significant academic, medical and commercial interest.
In October 2007, a new W3C working group was started to extend OWL with several new features as proposed in the OWL 1.1 member submission. W3C announced the new version of OWL on 27 October 2009. This new version, called OWL 2, soon found its way into semantic editors such as Protégé and semantic reasoners such as Pellet, RacerPro, FaCT++ and HermiT.
The OWL family contains many species, serializations, syntaxes and specifications with similar names. OWL and OWL2 are used to refer to the 2004 and 2009 specifications, respectively. Full species names will be used, including specification version (for example, OWL2 EL). When referring more generally, OWL Family will be used.

## History
### Early ontology languages

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 artificial intelligence (AI) could be made useful on the World Wide Web. These included languages based on HTML (called SHOE), based on XML (called XOL, later OIL), and various frame-based KR languages and knowledge acquisition approaches.

## Ontology languages for the web

In 2000 in the United States, DARPA started development of DAML led by James Hendler. In March 2001, the Joint EU/US Committee on Agent Markup Languages decided that DAML should be merged with OIL. The EU/US ad hoc Joint Working Group on Agent Markup Languages was convened to develop DAML+OIL as a web ontology language. This group was jointly funded by the DARPA (under the DAML program) and the European Union's Information Society Technologies (IST) funding project. DAML+OIL was intended to be a thin layer above RDFS, with formal semantics based on a description logic (DL).
DAML+OIL is a particularly major influence on OWL; OWL's design was specifically based on DAML+OIL.

### Semantic web standards

   The Semantic Web provides a common framework that allows data to be shared and reused across application, enterprise, and community boundaries.

#### RDF schema

   a declarative representation language influenced by ideas from knowledge representation
In the late 1990s, the World Wide Web Consortium (W3C) Metadata Activity started work on RDF Schema (RDFS), a language for RDF vocabulary sharing. The RDF became a W3C Recommendation in February 1999, and RDFS a Candidate Recommendation in March 2000. In February 2001, the Semantic Web Activity replaced the Metadata Activity. In 2004 (as part of a wider revision of RDF) RDFS became a W3C Recommendation. Though RDFS provides some support for ontology specification, the need for a more expressive ontology language had become clear.

#### Web-Ontology Working Group

   As of Monday, the 31st of May, our working group will officially come to an end. We have achieved all that we were chartered to do, and I believe our work is being quite well appreciated.
The World Wide Web Consortium (W3C) created the Web-Ontology Working Group as part of their Semantic Web Activity. It began work on November 1, 2001 with co-chairs James Hendler and Guus Schreiber. The first working drafts of the abstract syntax, reference and synopsis were published in July 2002. OWL became a formal W3C recommendation on February 10, 2004 and the working group was disbanded on May 31, 2004.

#### OWL Working Group

In 2005, at the OWL Experiences And Directions Workshop a consensus formed that recent advances in description logic would allow a more expressive revision to satisfy user requirements more comprehensively whilst retaining good computational properties. In December 2006, the OWL1.1 Member Submission was made to the W3C. The W3C chartered the OWL Working Group as part of the Semantic Web Activity in September 2007. In April 2008, this group decided to call this new language OWL2, indicating a substantial revision.
OWL 2 became a W3C recommendation in October 2009. OWL 2 introduces profiles to improve scalability in typical applications.

### Acronym

   Why not be inconsistent in at least one aspect of a language which is all about consistency?
OWL was chosen as an easily pronounced acronym that would yield good logos, suggest wisdom, and honor William A. Martin's One World Language knowledge representation project from the 1970s.

### Adoption

A 2006 survey of ontologies available on the web collected 688 OWL ontologies. Of these, 199 were OWL Lite, 149 were OWL DL and 337 OWL Full (by syntax). They found that 19 ontologies had in excess of 2,000 classes, and that 6 had more than 10,000. The same survey collected 587 RDFS vocabularies.

## Ontologies

   An ontology is an explicit specification of a conceptualization.
The data described by an ontology in the OWL family is interpreted as a set of "individuals" and a set of "property assertions" which relate these individuals to each other. An 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. A full introduction to the expressive power of the OWL is provided in the W3C's OWL Guide.
OWL ontologies can import other ontologies, adding information from the imported ontology to the current ontology.

### 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 that 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". This is, however, only true if the concepts of "Parent" and "Mother" only mean biological parent or mother and not social parent or mother.

### Logic

To choose a subset of first-order logic that is decidable, propositional logic was used, increasing its power by adding logics represented by convention with acronyms:
| Letter or symbol of logic | Description |
| ${\mathcal {AL}}$ | Inclusion and equivalence between classes, definition of atomic classes, universe class, intersection between classes, definitions of classes formed by elements that take part in relationships or have a relationship of a certain type only with elements of a certain class, congruence operator between individuals and an individual's membership in a class |
| ${\mathcal {ALC}}$ | adds to AL the empty class, the complement classes, the union of classes and the classes of elements that are in a certain relationship with elements of a certain class |
| ${\mathcal {S}}$ | Adds the definition of the transitivity of a relation to ALC |
| ${\mathcal {H}}$ | Inclusion and equivalence between relations |
| ${\mathcal {R}}$ | disjunction of properties, reflexivity, asymmetry, irreflexivity, relations composed of other relations, definition of non-relationship between two individuals |
| ${\mathcal {O}}$ (One of) | creation of classes via list of all and only the individuals contained |
| ${\mathcal {I}}$ (Reverse) | definition of inverse property |
| ${\mathcal {F}}$ (Feature) | definition of functional properties |
| ${\mathcal {N}}$ (Number) | cardinality restriction: number of elements participating in a certain relationship less than, greater than or equal to a value n |
| ${\mathcal {Q}}$ (Qualified) | like N, but the relationship can be qualified |
| ${\mathcal {D}}_{n}$ (Countable domain) | definition of domains (data types) to which a relationship can lead (e.g. "Mario is n years old") |

## Species
### OWL dialects

The W3C-endorsed OWL specification includes the definition of three variants of OWL, with different levels of expressiveness. These are OWL Lite, OWL DL and OWL Full (ordered by increasing expressiveness). 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.

#### OWL Lite

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 using 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, and is equally expressive as the description logic ${\mathcal {SHIF}}(\mathbf {D} )$. Development of OWL Lite tools has thus proven to be almost as difficult as development of tools for OWL DL, and OWL Lite is not widely used.

#### OWL DL

OWL DL is designed to provide the maximum expressiveness possible while retaining computational completeness (either φ or ¬φ holds), decidability (there is an effective procedure to determine whether φ is derivable or not), 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; and while a class may be a subclass of many classes, a class cannot be an instance of another class). 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.
This one can be expressed as ${\mathcal {SHOIN}}(\mathbf {D} )$, using the letters logic above.

#### OWL Full

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. OWL Full is undecidable, so no reasoning software is able to perform complete reasoning for it.

### OWL2 profiles

In OWL2 there are three sublanguages (known as profiles):
* OWL2 EL is a fragment that has polynomial time reasoning complexity. It is based on the description logic ${\mathcal {EL}}$.
* OWL2 QL is designed to enable easier access and query to data stored in databases. It is based on the DL-Lite family of description logics.
* OWL2 RL is a rule subset of OWL 2 (the acronym "RL" stands for "Rule Language"). It is based on the so-called description logic programs (DLP). Later, a logic called ${\mathcal {RL}}$ corresponding to this profile has been introduced.

## Syntax

The OWL family of languages supports a variety of syntaxes. It is useful to distinguish high level syntaxes aimed at specification from exchange syntaxes more suitable for general use.

### High level

These are close to the ontology structure of languages in the OWL family.

#### OWL abstract syntax

High level syntax is used to specify the OWL ontology structure and semantics.
The OWL abstract syntax presents an ontology as a sequence of annotations, axioms and facts. Annotations carry machine and human oriented meta-data. Information about the classes, properties and individuals that compose the ontology is contained in axioms and facts only. Each class, property and individual is either anonymous or identified by an URI reference. Facts state data either about an individual or about a pair of individual identifiers (that the objects identified are distinct or the same). Axioms specify the characteristics of classes and properties. This style is similar to frame languages, and quite dissimilar to well known syntaxes for DLs and Resource Description Framework (RDF).
Sean Bechhofer, et al. argue that though this syntax is hard to parse, it is quite concrete. They conclude that the name abstract syntax may be somewhat misleading.

#### OWL2 functional syntax

This syntax closely follows the structure of an OWL2 ontology. It is used by OWL2 to specify semantics, mappings to exchange syntaxes and profiles.

### Exchange syntaxes
#### RDF syntaxes

Syntactic mappings into RDF are specified for languages in the OWL family. Several RDF serialization formats have been devised. Each leads to a syntax for languages in the OWL family through this mapping. RDF/XML is normative.

#### OWL2 XML syntax

OWL2 specifies an XML serialization that closely models the structure of an OWL2 ontology.

#### Manchester Syntax

The Manchester Syntax is a compact, human readable syntax with a style close to frame languages. Variations are available for OWL and OWL2. Not all OWL and OWL2 ontologies can be expressed in this syntax.

### Examples

* The W3C OWL 2 Web Ontology Language provides syntax examples.

#### Tea ontology

Consider an ontology for tea based on a Tea class. First, an ontology identifier is needed. Every OWL ontology must be identified by a URI (http://www.example.org/tea.owl, say). This example provides a sense of the syntax. To save space below, preambles and prefix definitions have been skipped.

##### OWL2 Functional Syntax

    Ontology(<http://example.org/tea.owl> Declaration( Class( :Tea ) ) )

##### OWL2 XML Syntax

    <Ontology ontologyIRI="http://example.org/tea.owl" ...> <Prefix name="owl" IRI="http://www.w3.org/2002/07/owl#"/> <Declaration> <Class IRI="Tea"/> </Declaration> </Ontology>

##### Manchester Syntax

    Ontology: <http://example.org/tea.owl> Class: Tea

##### RDF/XML syntax

    <rdf:RDF ...> <owl:Ontology rdf:about=""/> <owl:Class rdf:about="#Tea"/> </rdf:RDF>

##### RDF/Turtle

    <http://example.org/tea.owl> rdf:type owl:Ontology . :Tea rdf:type owl:Class .

## Semantics
### Relation to description logics

OWL classes correspond to description logic (DL) concepts, OWL properties to DL roles, while individuals are called the same way in both the OWL and the DL terminology.
   In the beginning, IS-A was quite simple. Today, however, there are almost as many meanings for this inheritance link as there are knowledge-representation systems.
Early attempts to build large ontologies were plagued by a lack of clear definitions. Members of the OWL family have model theoretic formal semantics, and so have strong logical foundations.
Description logics are a family of logics that are decidable fragments of first-order logic with attractive and well-understood computational properties. OWL DL and OWL Lite semantics are based on DLs. They combine a syntax for describing and exchanging ontologies, and formal semantics that gives them meaning. For example, OWL DL corresponds to the ${\mathcal {SHOIN}}^{\mathcal {(D)}}$ description logic, while OWL 2 corresponds to the ${\mathcal {SROIQ}}^{\mathcal {(D)}}$ logic. Sound, complete, terminating reasoners (i.e. systems which are guaranteed to derive every consequence of the knowledge in an ontology) exist for these DLs.

### Relation to RDFS

OWL Full is intended to be compatible with RDF Schema (RDFS), and to be capable of augmenting the meanings of existing Resource Description Framework (RDF) vocabulary. A model theory describes the formal semantics for RDF. This interpretation provides the meaning of RDF and RDFS vocabulary. So, the meaning of OWL Full ontologies are defined by extension of the RDFS meaning, and OWL Full is a semantic extension of RDF.

### Open world assumption

   [The closed] world assumption implies that everything we don't know is false, while the open world assumption states that everything we don't know is undefined.
The languages in the OWL family use the open world assumption. Under the open world assumption, if a statement cannot be proven to be true with current knowledge, we cannot draw the conclusion that the statement is false.

#### Contrast to other languages

A relational database consists of sets of tuples with the same attributes. SQL is a query and management language for relational databases. Prolog is a logical programming language. Both use the closed world assumption.

## Public ontologies
### Libraries
#### Biomedical

* OBO Foundry
* NCBO BioPortal
* NCI Enterprise Vocabulary Services

### Standards

* Suggested Upper Merged Ontology (SUMO)
* TDWG
* PROV-O, the ontology version of the W3C's PROV-DM
* Basic Formal Ontology (BFO)
* European Materials Modelling Ontology (EMMO)

### Browsers

The following tools include public ontology browsers:
* Protégé OWL

### Search

* Swoogle

## Limitations

* No direct language support for n-ary relationships. For example, modelers may wish to describe the qualities of a relation, to relate more than 2 individuals or to relate an individual to a list. This cannot be done within OWL. They may need to adopt a pattern instead which encodes the meaning outside the formal semantics.