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the semantic web a gide to the future of XML, Web Services and Knowledge Management - Daconta M,C.

Daconta M,C. the semantic web a gide to the future of XML, Web Services and Knowledge Management - Wiley publishing , 2003. - 304 p.
ISBN 0-471-43257-1
Download (direct link): thesemanticwebguideto2003.pdf
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■ An ontology defines the common words and concepts (the meaning) used to describe and represent an area of knowledge.
■ An ontology is an engineering product consisting of "a specific vocabulary used to describe [a part of] reality, plus a set of explicit assumptions regarding the intended meaning of that vocabulary"1—in other words, the specification of a conceptualization.2
Let's try to unpack these definitions. The first definition has two parts:
■ Describing and representing an area of knowledge
■ Defining the common words and concepts of the description
Recall from the previous chapter what we learned about a domain: A domain is a subject matter area or area of knowledge. Some examples of areas of knowledge or domains are medicine, automobile repair, financial planning, machine tooling, business management, physics, textiles, and geopolitics. Describing an area of knowledge is the act of expressing, in either written or spoken words, the important points about a specific area of knowledge. For example, in describing automobile repair, we would probably talk about the following:
■ The kinds of cars there are (sedans, station wagons, sports cars, luxury cars, compacts, domestic and foreign cars)
■ The types of engines (corresponding perhaps to the types of fuel used: gasoline, diesel, electric-powered, hybrid)
'Guarino (1998, p. 4). 2Gruber (1993).
Understanding Ontologies
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■ The particular engines (for example, a 1995-96 V-6 Ford Taurus 244/4.0 Aerostar Automatic with Block Casting # 95TM-AB, Head Casting 95TM)
■ The manufacturers (Ford, General Motors, Chevrolet, Nissan, Honda, Volvo, Volkswagen, Saab, Hyundai, and so on)
■ The things that constitute cars (engines, brake systems, cooling systems, electric systems, suspension, body, and so on) and their properties (an engine has 4, 6, 8, or 12 cylinders; brake pads have different compositions such as semimetallic or nonferrous material)
We'll see in the next section a more complicated, technical definition of description, one that brings into our discussion the semantic notion of intension.
An important part of automobile repair is elaborating how to repair various cars, subsystems of cars, diagnosis, tools to use in diagnosis and repair, parts to use in the repair process, costing and estimating of repairs, how to manage an automobile repair facility, certification of excellence in automobile repair, and so on. When describing an area of knowledge—a domain—we describe the important things in the domain, their properties, and the relationships among the things. If we were to elaborate our description (because, say, we were writing a paper or a book on automobile repair), we may even include rules about the domain, such as the following diagnosis rule, which specifies how to determine what is wrong with an automobile system in order to repair it: If the car won't start and it doesn't turn over, check and clean the battery connections.
Therefore, a description is or can be an ontology. As we saw in Chapter 7, it includes the same kinds of concepts:
■ Classes (general things) in the many domains of interest
■ Instances (particular things)
■ The relationships among those things
■ The properties (and property values) of those things
■ The functions of and processes involving those things
■ Constraints on and rules involving those things
In addition to describing an area of knowledge, we also need to represent that description. What does representation mean? Representing means that we encode the description in a way that enables someone to use the description. A description consists of words and phrases in a natural language (such as English or Chinese), that is, vocabulary/terminology and sentences that combine terminologies to express relationships among the terms (we'll use vocabulary and terminology as equivalent here and use term for the individual
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Chapter 8
word). So representing means that we represent the description using terms and sentences. We define the terms (or we already have the terms defined in our mental lexicon), and then we combine those defined terms in ways that elaborate more of the meaning about the area of knowledge.
In information technology, however, we use a slightly more complicated notion of representing. We represent in order to use the description in information technology; in other words, we create a model that software will be able to utilize. We represent the classes, instances, relationships, properties, and rules for the area of knowledge. We use the terms of the natural-language description as labels for the underlying concepts—that is, the meaning of the area of knowledge consisting of classes, properties, and relationships. Typically, we represent or codify the ontology in a logical, knowledge representation language (which we discuss a bit later) rather than a natural language, because we want to represent our description as clearly, precisely, and unambiguously as possible, and natural language can be very ambiguous. We also want to make its meaning available for information technology use. Representation thus has to do with defining the terms (the vocabulary that acts as labels for the concepts), and that means also defining the concepts and their relationships that are behind the labels and that constitute the meaning of the model of the knowledge area we are interested in.
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