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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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Immediately we see that an ontology tries to capture the meaning (what we will call semantics) of a particular subject area or area of knowledge that corresponds to what a human being knows about that domain. An ontology also characterizes that meaning in terms of concepts and their relationships. Furthermore, an ontology is often represented as classes, relations, properties, attributes, and values.
Figure 8.1 is a graphical fragment of a simple ontology attempting to model the human resources domain (person, employee, organization), their subclasses (staff employee, management employee, company, group, division, and department), their properties, and the relationships among those concepts.
Chapter 8
Understanding Ontologies
183
Figure 8.1 Graphical ontology example: Human resources.
Listing 8.1 is a fragment of the textual view of the same ontology—see the companion Web site (http://www.wiley.com/compbooks/daconta) for the equivalent of the same ontology represented in RDF/S. In the case of Listing 8.1, the language used is the Open Knowledge Base Connectivity Language (OKBC, http://www.ai.sri.com/~okbc/). Both underscore an important point: There is no logical difference between a graphical and a textual rendition of an ontology (or any other model, for that matter).
This fact is important, because a key point of this chapter is that an ontology is represented in a knowledge representation language (such as a Semantic Web language like RDF/S, DAML+OIL, OWL, or in an ontology language that predates the Semantic Web, such as Ontolingua/KIF/Common Logic, OKBC, CycL, or Prolog). Furthermore, such ontology languages are in turn typically
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based on a particular logic, with the logic itself being a language with a syntax and a semantics (these latter concepts are explained later in this chapter). Sometimes, therefore, we call the language in which the ontology is represented a logic-based language. So ultimately it does not matter whether you see a graphical or a textual rendition of an ontology; both are exactly equivalent. The important issue is that of the power of the underlying language used to represent the ontology.
(defclass
(is-a USER)
(role concrete)
(single-sot managed_by (type SYMBOL)
;+ (allowed-classes Management_Employee)
;+ (cardinality 1 1)
(create-accessor read-write)) (single-slot part_of (type SYMBOL)
;+ (allowed-parents Organization)
;+ (cardinality 0 1)
(create-accessor read-write)) (multislot employs (type SYMBOL)
;+ (allowed-parents Employee)
(cardinality 1 ?VARIABLE) (create-accessor read-write)))
(defclass Department
(is-a Organization)
(role concrete)
(single-slot part_of (type SYMBOL)
;+ (allowed-parents Division)
;+ (cardinality 0 1)
(create-accessor read-write)))
(defclass Company
(is-a Organization)
(role concrete)
(single-slot part_of (type SYMBOL)
;+ (allowed-parents Company)
;+ (cardinality 0 1)
(create-accessor read-write)))
(defclass Person
Listing 8.1 Textual ontology example: Human resources.
Understanding Ontologies
185
(is-a USER)
(role concrete)
(single-slot birthdate (type STRING)
;+ (cardinality 1 1)
(create-accessor read-write)) (single-slot name_
(type STRING)
;+ (cardinality 1 1)
(create-accessor read-write)) (single-slot address (type STRING)
;+ (cardinality 1 1)
(create-accessor read-write)) (single-slot ssn
(type STRING)
;+ (cardinality 1 1)
(create-accessor read-write)))
... some classes omitted for brevity (see companion website for complete listing)...
Listing 8.1 (continued)
A corollary issue is that high-end ontology languages are backed by a rigorous formal logic, which thereby makes the ontology machine-interpretable. By machine-interpretable we mean that the semantics of the model is semantically interpretable by the machine; in other words, the computer and its software can interpret the semantics of the model directly—without direct human involvement. Software supported by ontologies moves up to the human knowledge/conceptual level; humans do not have to move down to the machine level. Interaction with computers takes place at our level, not theirs. This is an extremely important point, and it underscores the value of ontologies. In the following sections, we elaborate these issues so that you understand the importance of ontologies in the coming Semantic Web.
Ontology Definitions
The description and the picture and the code are nice, but just what is an ontology? An ontology defines the common words and concepts (the meaning) used to describe and represent an area of knowledge. But what does that definition mean? Let's delve into just what ontology is and what ontologies are. If you look up ontology in the dictionary, you'll find the following definition (from Merriam-Webster OnLine: http://www.m-w.com/):
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1. A branch of metaphysics concerned with the nature and relations of being
2. A particular theory about the nature of being or the kinds of existents
This definition indicates that the term originates in philosophy—specifically, a part of metaphysics that is the systematic study of the principles underlying a particular subject, most often the nature of being and the nature of experience. Often these days, the distinction is made between "big O" Ontology and "little o" ontology. "Big O" Ontology is the philosophical discipline. "Little O" ontology is the information technology engineering discipline that has emerged over the past eight or so years. Much like the distinction between ordinary taxonomies and taxonomies as used in information technology, there is a comparable distinction for ontologies. IT offers the following definitions. The first definition is really a simple paraphrase in everyday language of the more technically jargonistic second definition, but to understand the second, it helps to build on an elucidation of the first definition:
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