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In formal extensional ontologies, only the utterances of words and numbers are considered individuals – the numbers and names themselves are classes. In a 4D ontology, an individual is identified by its spatio-temporal extent. Examples of formal extensional ontologies are BORO, ISO 15926 and the model in development by the IDEAS Group.
Fact ontologies present a different approach by focusing on how entities belonging to different categories come together to constitute the world. Facts, also known as states of affairs, are complex entities; for example, the fact that the Earth is a planet consists of the particular object the Earth and the property being a planet. Fact ...
As building ontologies manually is extremely labor-intensive and time-consuming, there is great motivation to automate the process. Information extraction and text mining have been explored to automatically link ontologies to documents, for example in the context of the BioCreative challenges. [34]
The ontologies should be useful for multiple different people, and ontology developers should document the evidence of use. This criterion is important for the review process. Examples of use include linking to terms by other ontologies, use in semantic web projects, use in annotations or other research applications. [37]
Example of a constructed MBED Top Level Ontology based on the nominal set of views. [1]In computer science, information science and systems engineering, ontology engineering is a field which studies the methods and methodologies for building ontologies, which encompasses a representation, formal naming and definition of the categories, properties and relations between the concepts, data and ...
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While extensional classes are more well-behaved and well understood mathematically, as well as less problematic philosophically, they do not permit the fine grained distinctions that ontologies often need to make. For example, an ontology may want to distinguish between the class of all creatures with a kidney and the class of all creatures ...
Some upper ontologies—Cyc is often cited as an example in this regard—are very large, ranging up to thousands of elements (classes, relations), with complex interactions among them and with a complexity similar to that of a human natural language, and the learning process can be even longer than for a natural language because of the ...