The idea of an ontology is that it represents complex relationships among the objects or concepts themselves. The intent of an ontology is to provide a way to connect objects.
In computer science and information science, an ontology encompasses a representation, formal naming and definition of the categories, properties and relations between the concepts, data and entities that substantiate one, many, or all domains of discourse.
Ontologies on the semantic web are, by nature, decentralized. From the body of ontology mapping approaches, one could draw a conclusion that an effective approach to automate ontology mapping requires both data and metadata in application domains.
“Ontology” is a word like “facet”; it is searching for a real definition. Until the various knowledge and research communities fully coalesce, we won’t know exactly what someone means by “ontology.” That means when you start a conversation with someone about an ontology it is best to first set the syntactical framework of your conversation. What do they mean when they say “ontology?”
Ontologies tend to include a lot of fairly complex rules governing relationships. When people talk about semantic networks, they are not necessarily talking about ontologies. They could be speaking of applying controlled vocabularies, another kind of knowledge organization system (KOS), to their data. The authors might have a different implementation in mind entirely.
The choice of language used to represent terms, definitions, and facts is designed to implement a solution, and that isn’t always about being efficient and effective. Turing equivalence is about procedural languages that specify the steps to accomplish something. However, logical languages specify what is true, rather than a series of steps to perform.
In the health care industry, large chunks of unstructured data could be put to use to extract useful information. There are platforms based on machine learning and natural language processing techniques that help computers understand human language efficiently and process the available conversations, regarding drugs, medical devices and other health care products.
This is often in lieu of an ontology, and they have devised it in such a way that it can extract information from slang, misspellings, run-on sentences and obscure use of punctuation.
With an ontology to define content, the relationships and connections are identified, and that provides consistency in data sharing.
Data Harmony is a fully customizable suite of software products designed to maximize precise, efficient information management and retrieval. Our suite includes tools for taxonomy and thesaurus construction, machine-aided indexing, database management, information retrieval and explainable artificial intelligence.
Melody K. Smith
Sponsored by Access Innovations, changing search to found.
