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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]
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 ...
The Unified Medical Language System (UMLS) is a compendium of many controlled vocabularies in the biomedical sciences (created 1986). [1] It provides a mapping structure among these vocabularies and thus allows one to translate among the various terminology systems; it may also be viewed as a comprehensive thesaurus and ontology of biomedical concepts.
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.
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]
SIMS [6] a prominent example of this approach. The Structured Knowledge Source Integration component of Research Cyc is another prominent example of this approach. [7] [8] (Title = Harnessing Cyc to Answer Clinical Researchers' Ad Hoc Queries). The Gellish Taxonomic Dictionary-Ontology follows this approach as well. [9] Multiple ontologies
Ontologies can be used for structuring data in a machine-readable manner. [14] In this context, an ontology is a controlled vocabulary of classes that can be placed in hierarchical relations with each other. [15] These classes can represent entities in the real world which data is about.
Basic taxonomic tree of the General Formal Ontology. GFO (General Formal ontology) draws a fundamental distinction between concrete entities, categories and sets.Sets are described by an axiomatic fragment of set theory of Zermelo-Fraenkel, although fragments of anti-foundation axiom set theories such as ZF-AFA are considered.