By Asunción Gómez-Pérez PhD, MSc, MBA, Mariano Fernández-López PhD, MSc, Oscar Corcho MSc (auth.)
Ontological Engineering refers back to the set of actions that quandary the ontology improvement approach, the ontology existence cycle, the equipment and methodologies for development ontologies, and the instrument suites and languages that help them. over the last decade, expanding awareness has been occupied with ontologies and Ontological Engineering. Ontologies at the moment are commonly used in wisdom Engineering, synthetic Intelligence and machine technological know-how; in purposes concerning wisdom administration, average language processing, e-commerce, clever integration details, details retrieval, integration of databases, b- informatics, and schooling; and in new rising fields just like the Semantic internet. basic pursuits of this publication are to acquaint scholars, researchers and builders of knowledge structures with the fundamental recommendations and significant problems with Ontological Engineering, in addition to to make ontologies extra comprehensible to these laptop technological know-how engineers that combine ontologies into their info platforms. we've got paid detailed recognition to the impression that ontologies have at the Semantic internet. tips that could the Semantic internet seem in all of the chapters, yet specifically within the bankruptcy on ontology languages and tools.
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Extra resources for Ontological Engineering: With Examples from the Areas of Knowledge Management, e-Commerce and the Semantic Web
4. Meta-ontologies (for Mizoguchi) are equivalent to what other authors refer to as a knowledge representation ontology. 7: Mizoguchi and colleagues (1995) categorization. 8 illustrates: the amount and type of structure of the conceptualization and the subject of the conceptualization. In the first dimension, they distinguish three categories: terminological ontologies such as lexicons, information ontologies such as database schemata, and knowledge modeling ontologies that specify conceptualizations of the knowledge.
It is used with the properties rdf:first and rdf:rest, which represent the relationship between a list and its first item, and between the list and the rest of the list, respectively. The primitive rdf:nil is an instance of rdf:List that represents the empty list. x Class rdf:XMLLiteral. It is a datatype that defines the class of well-formed XML literal values. x Properties rdf:predicate, rdf:subject and rdf:object. They define the property, subject resource, and object resource of a statement respectively.
It defines the class to which a resource belongs. x Property rdf:value. It defines the value of a property, usually a string, when the value is a structured resource (another RDF statement). The RDF data model does not provide modeling primitives for defining the relationships between properties and resources. For instance, in RDF we cannot define that the relation arrivalPlace can only hold between instances of the classes Travel and Location. This limitation is solved by the RDF Vocabulary Description Language (Brickley and Guha, 2003), also known as RDF Schema or RDFS.