In order for information from different sources to be integrated, there needs to be a shared understanding of the relevant domain. Knowledge representation formalisms provide structures for organizing this knowledge, but provide no mechanisms for sharing it.
An ontology defines a common vocabulary for researchers who need to share information in a domain. It includes machine-interpretable definitions of basic concepts in the domain and relations among them. An ontology is a formal explicit description of concepts in a domain of discourse (classes (sometimes called concepts)), properties of each concept describing various features and attributes of the concept (slots (sometimes called roles or properties)), and restrictions on slots (facets (sometimes called role restrictions)). An ontology together with a set of individual instances of classes constitutes a knowledge base.
In practical terms, developing an ontology includes:
- defining classes in the ontology,
- arranging the classes in a taxonomic (subclass–superclass) hierarchy,
- defining slots and describing allowed values for these slots,
- filling in the values for slots for instances.
According to Gruber’s definition an ontology is “a formal specification of a conceptualization”. A conceptualisation being a simplified, abstract way of perceiving a segment of the world (a piece of
reality), for which we agree to recognize the existence of a set of objects and their interrelations, as well as the terms we use to refer to them and their agreed meanings and properties.
Some of the reasons to develop an ontology are:
· To share common understanding of the structure of information among software agents
· To enable reuse of domain knowledge
· To make domain assumptions explicit
· To separate domain knowledge from the operational knowledge
· To analyze domain knowledge
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