Ontology (information science)

The term ontology in computer science refers to the attempt to formulate an exhaustive and rigorous conceptual schema within a given domain, in order to facilitate communication and sharing of information between different systems. This is a different from, but takes its name from an analogy with, the philosophical meaning of the word ontology.

A common current technological use of the concept of ontology, in this sense, is in artificial intelligence and knowledge representation. In some applications many schemas are combined into a de facto complete data structure containing all the relevant entities and their relationships within a domain.

Computer programs can then use the ontology for a variety of purposes including inductive reasoning, classification, and a variety of problem solving techniques.

Typically, ontologies in computers are tied closely with fixed vocabularies--a foundation ontology --in whose terms everything else must be described. Because these may be poor representations for certain problem domains, more specialized schema must be created to make the data useful in making real world decisions.

Such ontologies are commercially valuable, creating competition to define them. Peter Murray-Rust has claimed that this leads to "semantic and ontological warfare due to competing standards". Accordingly any standard foundation ontology is likely to be contested among commercial or political parties, each with their own idea of 'what exists' (in the philosophy sense).

For a recently proposed variation see MathWorld site whose owner has argued that the universe is better described by computer programs than mathematics.

Marginalia

Barbara Ann Kipfer, a Connecticut lexicographer involved in AI projects, has written a popular book 14,000 Things to Be Happy About ISBN 0894803700 which essentially is a happiness ontology.