The Conceptual Frameworks and Organized Vocabularies for AI Programs
"Ontological analysis clarifies the structure of knowledge. Given a domain, its ontology forms the heart of any system of knowledge representation for that domain. Without ontologies, or the conceptualizations that underlie knowledge, there cannot be a vocabulary for representing knowledge....Second, ontologies enable knowledge sharing."
- from What Are Ontologies, and Why Do We Need Them? B. Chandrasekaran, John R. Josephson and V. Richard Benjamins
Imagine that you have a beaker capable of holding 10cc of a liquid and you pour 5cc of water into it. Some people would say that the beaker is half-full ... others would say that it is half-empty ... and some would say that it is filled to one-half of its capacity or that it merely contains 5cc of water.
The point of this exercise is to demonstrate that we can portray the same item in various ways, with each representing a different perspective or mindset. Thus, when selections are made from the set of possible portraits and are then gathered together in the conceptual framework known as an ontology, the result is but one of several possible vistas.
This concept was eloquently explained in What Is a Knowledge Representation?, where under the caption of Role 2: A Knowledge Representation Is a Set of Ontological Commitments, the authors state:
If, as we argue, all representations are imperfect approximations to reality, each approximation attending to some things and ignoring others, then in selecting any representation, we are in the very same act unavoidably making a set of decisions about how and what to see in the world. That is, selecting a representation means making a set of ontological commitments. The commitments are, in effect, a strong pair of glasses that determine what we can see, bringing some part of the world into sharp focus at the expense of blurring other parts.
These commitments and their focusing-blurring effect are not an incidental side effect of a representation choice; they are the essence. [p. 19]
Definition of the Area
"The subject of ontology is the study of the categories of things that exist or may exist in some domain. The product of such a study, called an ontology, is a catalog of the types of things that are assumed to exist in a domain of interest D from the perspective of a person who uses a language L for the purpose of talking about D. The types in the ontology represent the predicates, word senses, or concept and relation types of the language L when used to discuss topics in the domain D. An uninterpreted logic, such as predicate calculus, conceptual graphs, or KIF, is ontologically neutral. It imposes no constraints on the subject matter or the way the subject may be characterized. By itself, logic says nothing about anything, but the combination of logic with an ontology provides a language that can express relationships about the entities in the domain of interest. " -- John Sowa, in Ontology.
What is an Ontology? A concise explanation from Tom Gruber and the Knowledge Systems Laboratory at Stanford University. "An ontology is an explicit specification of a conceptualization. The term is borrowed from philosophy, where an Ontology is a systematic account of Existence. For AI systems, what 'exists' is that which can be represented. ... My colleagues and I have been designing ontologies for the purpose of enabling knowledge sharing and reuse. In that context, an ontology is a specification used for making ontological commitments. ... Practically, an ontological commitment is an agreement to use a vocabulary (i.e., ask queries and make assertions) in a way that is consistent (but not complete) with respect to the theory specified by an ontology. We build agents that commit to ontologies. We design ontologies so we can share knowledge with and among these agents."
What is an ontology? From OWL Web Ontology Language Use Cases and Requirements. W3C Recommendation (10 February 2004). Jeff Heflin, editor. "An ontology defines the terms used to describe and represent an area of knowledge. Ontologies are used by people, databases, and applications that need to share domain information (a domain is just a specific subject area or area of knowledge, like medicine, tool manufacturing, real estate, automobile repair, financial management, etc.). Ontologies include computer-usable definitions of basic concepts in the domain and the relationships among them (note that here and throughout this document, definition is not used in the technical sense understood by logicians). They encode knowledge in a domain and also knowledge that spans domains. In this way, they make that knowledge reusable.... Ontologies are usually expressed in a logic-based language, so that detailed, accurate, consistent, sound, and meaningful distinctions can be made among the classes, properties, and relations."