This article is about ontology in information science. What ontologies have in common in both computer science and philosophy is the representation of entities, ideas and events, along with their properties and relations, according to a system of categories. Differences between the two are automotive domain knowledge pdf matters of focus.
Other fields make ontological assumptions that are sometimes explicitly elaborated and explored. The traditional goal of ontological inquiry in particular is to divide the world “at its joints” to discover those fundamental categories or kinds into which the world’s objects naturally fall. Some researchers, drawing inspiration from philosophical ontologies, viewed computational ontology as a kind of applied philosophy. This definition is consistent with the usage of ontology as set of concept definitions, but more general. And it is a different sense of the word than its use in philosophy. Ontologies are often equated with taxonomic hierarchies of classes, class definitions, and the subsumption relation, but ontologies need not be limited to these forms. To specify a conceptualization, one needs to state axioms that do constrain the possible interpretations for the defined terms.
An ontology is a formal, explicit specification of a shared conceptualization that is characterized by high semantic expressiveness required for increased complexity. Contemporary ontologies share many structural similarities, regardless of the language in which they are expressed. In this section each of these components is discussed in turn. Particular meanings of terms applied to that domain are provided by domain ontology.
Since domain ontologies represent concepts in very specific and often eclectic ways, they are often incompatible. As systems that rely on domain ontologies expand, they often need to merge domain ontologies into a more general representation. This presents a challenge to the ontology designer. At present, merging ontologies that are not developed from a common foundation ontology is a largely manual process and therefore time-consuming and expensive. Domain ontologies that use the same foundation ontology to provide a set of basic elements with which to specify the meanings of the domain ontology elements can be merged automatically.
A survey of ontology visualization techniques is presented by Katifori et al. The most established ontology visualization techniques, namely indented tree and graph are evaluated by Fu et al. Ontology engineering aims to make explicit the knowledge contained in software applications, and organizational procedures for a particular domain. Ontology engineering offers a direction for overcoming semantic obstacles, such as those related to the definitions of business terms and software classes. Some provide export to other ontology languages however. Ontologies are developed for a specific purpose and application.
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