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A domain of a given property is the class for which the first argument of the property is specified; a range of a given property is the class for which the second argument of the property is specified. Think of the relation/property has-Father(Child, Father): Child is the domain of the property hasFather, Father is the range of the property hasFather. This simply means that any instance/individual in the domain must be a member of the Child class; any instance in the range must be a member of the Father class. If there were a defined inverse property fatherOf(Father, Child), then the domain of fatherOf would be Father; the range would be Child. OWL Lite also enables you to constrain the range of properties using the quantifier expressions allValuesFrom and someValuesFrom (expressions described in the preceding text).
OWL DL extends OWL Lite by permitting cardinality restrictions that are not limited to 0 or 1. Also, you can define classes based on specific property values using the hasValue construct. At the OWL DL level, you can create class expressions using boolean combinators (set operators) such as unionOf, intersectionOf, and complementOf. Furthermore, classes can be enumerated (listed) using the oneOf construct or specified to be disjoint using disjointWith construct.
OWL Full extends OWL DL by permitting classes to be treated simultaneously as both collections and individuals (instances). Also, a given datatypeProperty can be specified as being inverseFunctional, thus enabling, for example, the specification of a string as a unique key.
In this chapter, you have been given a solid but necessarily brief introduction to ontologies. We looked at what ontologies are and gave some examples and definitions. We reviewed notions that are important for discussing ontologies, such as the roles of syntax, structure, semantics, and pragmatics in the definition and use of ontologies. We looked at important concepts for ontologies and ontological engineering, such as extension and intension, the difference between labels (terms) and concepts (meaning), the levels every ontology has (meta and object levels; upper, middle, and lower or domain levels), and the distinction between a class (concept) and an instance (individual). We saw that knowledge representation languages are important for ontologies, as is logic (propositional, predicate, and higher logics). Finally, we discussed some ontology management tools and some of the Semantic Web ontology languages that are emerging, such as RDF/S, DAML+OIL, and OWL. You have been given wide, foundational knowledge about ontologies and are now prepared to dig deeper technically into these topics, if you so desire.
But what's the bottom line here? What are the real values for using ontologies? The real value of using ontologies and the Semantic Web is that you are able to express for the first time the semantics of your data, your document collections, and your systems using the same semantic resource and that resource is machine-interpretable: ontologies. Furthermore, you can reuse what you've previously developed, bring in ontologies in different or related domains created by others, extend yours and theirs, make the extensions available to other departments within your company (or your trading consortium or supply chain), and really begin to establish enterprise- or community-wide common semantics.
From our discussion of semantic mapping and merging, we now understand that this does not require a common semantics or common model (a monolithic ontology in our terminology) across the enterprise or community, but instead a set (or probably more accurately, a lattice) of integrated ontologies: upper, middle, and domain (or subdomain) levels integrated logically and thus not all in the same namespace and all contexts not the same, and all applications not using the same portions of the lattice of ontologies. Instead, ontologies across the board—upper modules, middle modules, domain modules, context modules, application modules—are coherently used (and reused!) across the enterprise or community, but according to the requirements of applications, which ultimately means, according to end-user needs, whoever the specific end users are, and in fact all end users in your enterprise or community.
With the widespread development and adoption of ontologies, which explicitly represent domain and cross-domain knowledge, we will have enabled our information technology to move upward—if not a quantum leap, then at least a major step—toward having our machines interact with us at our human conceptual level, not forcing us human beings to interact at the machine level. We predict that the rise in productivity at exchanging meaning with our machines, rather than semantically uninterpreted data, will be no less than revolutionary for information technology as a whole.
Crafting Your Company's Roadmap to the Semantic Web