Applied Ontology

The YouTube video, Ontologies as Conceptualizations by Nicola Guarino, helps one understand the application of ontologies and ontology like things to control systems.  Applied ontology is the application of ontology for practical purposes.

Per my understanding (i.e. paraphrasing from the video); applied ontology, or applied computational ontology, is an emerging interdisciplinary area which defines an ontology as an artifact that expresses the intended meaning of a vocabulary in a machine readable form.  The practical intention is to enable competent use of the vocabulary in real situations.  It defines primitive categories of things and nature and structure of those things within a domain of discourse.

The purpose of an ontology, per applied ontology, is to increase understanding and clarity by making explicit and communicating people's assumptions about the nature and structure of a domain of discourse.  The objective is to help people understand each other. Ultimately, an ontology is a tool for communications.

An ontology does not specify what exists in "reality", rather it articulates one perception of reality per the explicitly assumptions of the ontology. Commitment to the nature and structure and the vocabulary used to discuss the conceptualization, to that perception, is ontology commitment.  It is like a pair of glasses, it is a perception of an area of knowledge made explicit and documented in machine readable form.

An ontology is all possible allowed interpretations of a domain of discourse.  An intended model is consistent with the allowed interpretations.  Intended models should be the same as set of models admitted by the ontology.

Admitted ontology models and intended models should be the same.  Models should have high precision and maximum correctness. That constitutes a "good model".  Correct means all intended models are covered.

Bad things happen when false agreement occurs.  False agreement is believing you agree but you actually do not agree. Underspecifying is bad.  "Super specification" is good. Capturing all intended models is not enough for a perfect ontology.  Models are not enough.


Putting all of the above into my terms, I get this:

Subject matter experts (SMEs) must clearly understand their area of knowledge and explicitly state their assumptions about a particular area of knowledge. This clarity ensures effective communication among SMEs regarding that area of knowledge.

An ontology (a.k.a. theory, ontology-like things) serves as a deliberate, explicit, and formal representation of this understanding. Such a representation facilitates communication within an area of knowledge and across different areas of knowledge.

This representation intentionally describes stakeholders' explicit assumptions about the important, relevant nature and structure of the area of knowledge, along with a vocabulary that stakeholders can use to discuss these concepts. The vocabulary and relevant nature and structure constitute a commitment to the area of knowledge, known as ontological commitment. The goal is to minimize ambiguity and misunderstandings among stakeholders within an area of knowledge. Another goal is to enable stakeholders to effectively expand or extend the vocabulary, nature, and structure of the area of knowledge when necessary. These expansions should be plausible and consistent with the representation.

An ontology does not describe what exists in "reality"; instead, it articulates one perception of reality based on the explicit assumptions of the ontology. It acts like a pair of glasses, making a specific view of an area of knowledge explicit. Other ontologies could have different explicit assumptions.

With good ontologies, common agreement can be achieved by stakeholders.  But in addition, reasons for disagreement can be understood and discussed effectively.

A well-founded ontology can make explicit the reasons for agreement and the reasons for disagreement therefore make obstacles to interoperability clear.

Additional Information:


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