Model Driven Engineering and Ontology Development by Dragan Ga#evic;Dragan Djuric;Vladan Deved#ic

By Dragan Ga#evic;Dragan Djuric;Vladan Deved#ic

Defining a proper area ontology is mostly thought of an invaluable, to not say helpful step in virtually each software program undertaking. this is why software program bargains with principles instead of with self-evident actual artefacts. even though, this improvement step is hardly performed, as ontologies depend upon well-defined and semantically strong AI suggestions reminiscent of description logics or rule-based platforms, and so much software program engineers are principally unexpected with those.

Gaševic and his co-authors attempt to fill this hole through detailing the best way to use model-driven engineering for ontology improvement at the Semantic net. half I in their publication describes latest applied sciences, instruments, and criteria like XML, RDF, OWL, MDA, and UML. half II provides the 1st distinctive description of OMG's new ODM (Ontology Definition Metamodel) initiative, a specification that is anticipated to be within the kind of an OMG language like UML. eventually, half III is devoted to purposes and useful points of constructing ontologies utilizing MDA-based languages.

For this moment variation, the descriptions of the comparable criteria (like MOF, ODM, OCL, and OWL) were revised and up-to-date; new chapters introducing the fundamental ideas of model-driven engineering, contemporary examine effects on metamodeling Semantic net rule languages, an advent to the Atlas Transformation Language (ATL) and its software aid, and, final yet no longer least, many new examples were added.

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The third definition also uses the AND construct to make the composition of the three concept expressions that follow it. SPORTS-CAR). Note, however, that most frame languages are just a new syntax for parts of first-order logic (Welty 1996). This means that most of these languages do not offer anything new in expressiveness. a Agent))))) Frame-based languages are usually suitable for representing knowledge that does not change. Only very few of them are able to deal with nonmonotonic changes in the knowledge being represented.

Ontological knowledge is an essential supplement to knowledge about a specific domain—it describes the categories of things in that domain and the terms that people use to talk about them (Sowa 2000). For example, the ontological knowledge about an object-oriented language contains the concept of a class, and the ontological knowledge about a 14 1 Knowledge Representation relational database includes tables and fields. Ontological knowledge also describes relations between such categories, and the axioms and constraints in the domain.

Rule languages also differ in terms of the extent to which they control rule ordering during the inference process. Further classifications of rule languages are possible. , when the rule base is large), as there is no ordering of the rules; • inferences cannot be limited to those dealing only with the objects of interest. More recent rule languages combine rules with frame-based features that provide object orientation, better structuring of knowledge through generalization/specialization and concept hierarchies, and natural inference capabilities such as classification and inheritance.

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