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In computing, an ontology is a precise description of the concepts in a subject area and the relationships among them, written so people and software can interpret that domain consistently. For example, a wine ontology could define wines, meals, and preferences—and describe which wines pair with which meals.
How an ontology goes beyond a glossary
A glossary defines terms. An ontology also makes connections among those terms explicit. A glossary might define “wine” and “main course”; an ontology can state that a wine pairs with a course, or that a person dislikes a particular wine.
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That structured meaning matters when software needs to work with more than matching words. In the wine-selection example in the W3C OWL Guide, relationships among wines, courses, and preferences can help an agent interpret a request for a suitable pairing while excluding a disliked wine.
What an ontology contains
Ontologies commonly describe a domain using classes, properties, instances, and axioms. In OWL, these are represented through entities and expressions that form precise statements about the domain. The W3C OWL 2 Primer, Second Edition defines an ontology as “a set of precise descriptive statements about some part of the world” (the domain of interest).
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Classes: categories of things
A class represents a category, such as Wine or Course. Classes let an ontology describe kinds of things rather than only naming individual items.
Properties: attributes and relationships
A property describes an attribute or a connection between things. For example, a wine could have a color, while a wine-to-course property could express a pairing relationship.
Instances: particular things
An instance is a specific thing described in the domain, such as a particular bottle of wine or a named course. The W3C OWL Guide notes that an ontology may include descriptions of classes, properties, and their instances.
Axioms: formal statements
Axioms are the formal statements that specify what the ontology says about its concepts and relationships. Because OWL has formal semantics, reasoning software can check whether statements are consistent and derive some facts that are implicit in them. This is a capability of the representation; it does not mean software understands every nuance of human knowledge.
Ontology, OWL, RDF, and XML Schema: what is the difference?
These terms are related, but they do not mean the same thing. An ontology is the structured description of a domain; OWL is one language for expressing one. RDF provides a data model for resources and relations, while XML and XML Schema address structured documents and their constraints.
| Term | What it represents | Relationships and machine interpretation | Primary purpose |
|---|---|---|---|
| Glossary | Terms and their definitions. | Definitions alone do not necessarily make relationships among terms explicit. | Help people understand vocabulary. |
| Ontology | Concepts in a domain and precise statements about them. | Can make relationships explicit; a formal representation can support machine interpretation and reasoning. | Represent selected knowledge about a domain. |
| OWL | A W3C language for expressing ontologies. | Its formal semantics support machine interpretation and reasoning. | Express rich descriptions of things, groups of things, and relationships. |
| RDF | A data model for resources and relations. | Has its own simple semantics; RDF data can be represented in different syntaxes. | Represent data about resources and their relationships. |
| RDF Schema | A vocabulary for describing RDF classes and properties. | Can express class and property hierarchies, including generalization. | Describe the vocabulary used in RDF data. |
| XML and XML Schema | XML is a syntax for structured documents; XML Schema can constrain document structure. | Primarily describes document structure or message format, rather than domain meaning. | Represent and validate structured documents. |
These distinctions follow the W3C’s OWL 2 Primer, OWL Guide, and OWL 2 New Features and Rationale. A database schema, taxonomy, knowledge graph, or list of categories is not automatically an ontology; the label depends on how it represents concepts and their relationships.
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Why formalize a domain as an ontology?
When people or systems use the same terms differently, data can be difficult to combine or interpret. An ontology provides a shared, explicit representation of selected concepts and their connections. When expressed in a formal language such as OWL, it can also allow software to check consistency or infer some consequences of the stated relationships.
An ontology is a model of a chosen subject area, not a complete account of reality. Its usefulness depends on which concepts and relationships it represents and how precisely those are stated.
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