By a Ontologie one understands a formally defined system in computer science within the range of the knowledge representation about concepts and relations. Additionally Ontologien contain inference and integrity rules. The most well-known short definition reads "„specification of a Konzeptualisierung "“T.R. Gruber: A translation approach ton portable ontologies. In: Knowledge Acquisition, volume 5, number 2, page 199-220, 1993

Ontologien serve within different ranges as means for the structuring and for data exchange, in order to join knowledge existence already existing - for example genetic data in bio computer science. Experts from different areas must worry only about the modelling of their respective specialized knowledge and the inference processes necessary for it. In this way can be divided deklaratives knowledge, problem solution techniques and conclusion mechanisms of several systems.

Ontologien experienced an upswing with the idea "„of the Semantic Web "“in the last years. A general definition of the term is difficult, since depending upon author different systems are summarized under it. Thus several already longer existing formats and beginnings can be understood such as Frames and semantic nets from artificial intelligence or classifications and thesaurus from the documentation science alternatively as a forerunner, alternatives or than special forms of Ontologien.

Ontologiesprachen

Formal languages for the description of Ontologien are under other billion flow diagram one, DAML+OIL, F-Logic, which publicised Web Ontology LANGUAGE (OWL) from the World Wide Web Consortium for the semantic Web, the Web service Modeling LANGUAGE (WSML) and the Topic map standardized under ISO/CInternational Electronical Commission 13250:2000. Also the Knowledge interCHANGE format (KIF) is occasionally used.

History

Ontologie is original as theory of being ends a philosophical discipline and part of the Metaphysik.

As forerunners of an explicit formalizing of the Ontologiebegriffs Charles S. Peirce and Edmund Husserl are to be called. A formal view on the philosophical Ontologie had also A. Church 1958 (Ontological Commitment, in: The journal OF Philosophy, 55:1008 - 1014), as well as wanting pool of broadcasting corporations Van Orman Quine. Quine spoke a Ontologiebegriff, which broke with the tradition of the classical view of the Ontologiebegriffs in philosophy. After Quine is its: To be worth bound variable. (Relevant texts are of a logical point of view, English Orig. 1961 and Ontologi relativity, English Orig. 1969). In on the way to the truth is the following representation: "“Empirical from importance are at a Ontologie excluding the mentioned neutral knots, them for the structure of the theory contribute."” (W.V.O.Quine, on the way to the truth, "§13 dissolution of the Ontologie, Paderborn and others 1995, S.45.). See also deputy function.

Within the range of artificial intelligence the term became Ontologie starting from beginning of the 1990er by an article of Neches et al. Robert Neches, Richard Fikes, Tim Finin, Thomas Gruber, Ramesh Patil, Ted senator, William R. Swartout: Enabling technology for knowledge sharing. In: AI of magazines, volume 12, number 3, 1991 and following publications popular.

From then on the term Ontologie spread artificial intelligence as explicit formalizing, by research was used and by bio computer science (Ashburner 2000) and further subjects taken up.

1999 presented Tim Berners Lee its vision of the Semantic Web. Today most frequently quoted is Berners Lee 2001.

Structure of Ontologien

Similarly to a data base, where structure (data base schema) and contents of (data) form a whole, the rules and the concepts belong together also with a Ontologie. While classical data bases do not have information about the meaning of the stored data, which are based applications of data bases possess a formal description of the data as well as rules over their connection on Ontologien. These rules make it possible to draw conclusions from the existing data to recognize contradictions in the data and to supplement missing knowledge independently from the existing one. These conclusions are derived by inference, thus by logical concluding.

Under "„Ontology learning "“to perhaps translate (with "„ontologisches learning "“) the process can be described, with which a Ontologie akquiriert by automatic procedures further knowledge and thus in extent and structure continues to increase. But inferences play an important role. During this process the Ontologie to a certain extent produces knowledge, while Ontologien in addition-learn otherwise by inputs on the part of human experts.

Among other things due to its complexity in practice use is made by the possibility of relations over relations (called in RDF Reification) and rules relatively rarely, although straight these characteristics Ontologien differentiate of other systems of concepts.

Ontologiebau

For the production and extension from Ontologien different formalized process cycles were suggested. The procedures after Holsapple and Joshi, after Prez or Uschold dedicate themselves strengthen to the co-operation of experts of the field of knowledge of the Ontologie and computer scientists or general formalists. Automatically supporting procedures have either the goal of making a complete construction of the Ontologie (as for instance the procedure of or existing Ontologien by term suggestions to extend (for example the procedure of Faatz and stone-cutter). With the production of Ontologien also the fusion of existing Ontologien can be from interest. For this there is a formal in procedures mute ones and

Ontologie editors

Different software Tools supports the construction of Ontologien in various Ontologie languages. See major item Ontologie editor.

Categorization of Ontologien

After the internal structure

1. Controlled vocabulary
2. Glossaries
3. Thesaurus: Objects are set arbitrarily with one another in relationship (e.g. "„A is a B "“, "„A is related to B "“).
4. informal "“actualin"” - hierarchies (taxonomy and classifications: Objects are strictly hierarchically classified (e.g. "„A is child of B "“). Taxonomies are visualized frequently by trees.)
5. formal "“actualin"” - hierarchies
6. Frames - classes and their characteristics include
7. Ontologien, the value defaults contained (arrival date is a DATE)
8. Logic guidelines or also logical-mathematical representation: Object relations is represented over formal notations (e.g. "„synonymously (A, b): = synonymously (b, A); "“). The predicate calculus of the first stage (roofridge order logic) is a formal model of a logic.

After their article

1. Knowledge representations (Knowledge Representation - KR)
2. General (English common) Ontologien
3. Top level and/or Upper level Ontologien - see
4. Domain Ontologien: With the knowledge range (knowledge domain), from which the terms and relations of the Ontologie comes, gives it different, often complementary types:
   1. a Ontologie can represent the attempt to possibly illustrate general knowledge or comprehensive and everyday world knowledge,
   2. a Ontologie can illustrate a reduced, specializedspecific knowledge range.
5. Task (tasks) - Ontologie
6. Domain task Ontologie
7. Method Ontologie
8. Application Ontologie

Usually Ontologien illustrate static description of a domain. In addition, certain Ontologien tries to formalize temporal operational sequence like e.g. the PSL written in KIF (Process Specification LANGUAGE).

See also

• Arranged one acyclic graph (representation possibility of Ontologien)
• Ontologiebibliothek

Sources

Articles in category "Ontologie (computer science)"

We found here 3 articles.

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