Semantic Web-Based Information Systems: State-of-the-Art ...

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Table 1. Examples of transformations at the lexical layer Bu ld ng Ontology Translat on Systems WebODE.Identifier. Target. Result. Reasons.for.Transformation. Business Trip Ontolingua Business-Trip Blank spaces in identifiers are not allowed in Ontolingua 1StarHotel RDF(S) OneStarHotel Identifiers cannot start with a digit in RDF(S). They do not form valid QNames Concepts Name and Name Ontolingua classes Name and Name_1 Ontolingua is not case sensitive Concept Room attribute fare Concept Flight attribute fare Concept Name attribute Name OWL classes Room, Flight datatypeProperty roomFare datatypeProperty flightFare WebODE attributes are local to concepts. OWL datatype properties are not defined in the scope of OWL classes, but globally Protégé-2000 class Name; slot name The identifiers of classes and slots cannot overlap in Protégé-2000 Figure 2. Examples of transformations at the syntactic layer Copyright © 2007, Idea Group Inc. Copying or distributing in print or electronic forms without written permission of Idea Group Inc. is prohibited.
Corcho & Gómez-Pérez problems related to how the symbols are structured in the source and target formats, taking into account the derivation rules for ontology components in each of them. In this layer, the following types of transformations are included: • Transformations of ontology component definitions according to the grammars.of.the.source.and.target.formats: For instance, the grammar to define a concept in Ontolingua is different than that in OCML. • Transformations.of.datatypes:.For instance, the datatype date in WebODE must be transformed to the datatype &xsd;date in OWL. Figure 2 shows an example of how a WebODE concept definition (expressed in XML) is transformed into Ontolingua and OWL. In this example, both types of translation problems are dealt with. Among the most representative ontology languages and tools, we can distinguish the following (overlapping) groups of formats: • Lisp-based. formats: The syntax of several classical ontology languages are based on the Lisp language; namely, KIF and Ontolingua, LOOM, and OCML, together with their corresponding ontology tools (Ontolingua Server, OntoSaurus, and WebOnto, respectively). • XML-based. formats:. Ontology markup languages are characterized by being represented in XML syntax. Among them, we can cite SHOE, XOL, RDF, RDFS, OIL, DAML+OIL, and OWL. In addition, ontology tools such as OntoEdit, Protégé-2000, and WebODE also provide ad hoc XML backends to implement their ontologies. • Ad.hoc.text.formats:.There are other ontology languages that do not provide any of the previous syntaxes, but they provide their own ad hoc formats. These languages are F-Logic, the ASCII syntax of OIL, and the Notation-3 (N3) syntax used to represent ontologies in RDF, RDFS, and OWL. Except for F-Logic, these syntaxes are alternative and mainly intended for human consumption. • Ontology.management.APIs: Finally, several ontology languages and tools provide ontology management APIs. These APIs are included here because they can be considered as another form of syntax; the expressions used to access, create, and modify ontology components in the programming language in which these APIs are available have to be created according to the specification provided by the API. Among the languages with an ontology management API, we have all the ontology markup languages, where ontologies can be created using available XML Java APIs such as DOM, SAX, and so forth; and, more specifically, RDF, RDFS, DAML+OIL, and OWL, for which there are specific Copyright © 2007, Idea Group Inc. Copying or distributing in print or electronic forms without written permission of Idea Group Inc. is prohibited.
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Semantic Web-Based Information Syst
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Chapter.VIII Querying.the.Web.Recon
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the semantics in the Semantic Web.
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the conventional Web, and the emerg
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Chapter.I Semant cs for the Semant
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Semant cs for the Semant c Web and
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Semant cs for the Semant c Web in t
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Entity Identification/Disambiguatio
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Question Answering Systems Semant c
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Semant cs for the Semant c Web The
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The Human Semant c Web tion between
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The Human Semant c Web Figure 2. Th
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• Databases with entry-portals
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The Human Semant c Web • Knowledg
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Conceptual.Modeling The Human Seman
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The Human Semant c Web in relations
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Conceptual.Calibration The Human Se
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Figure 16. The present structure of
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The Human Semant c Web entire healt
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The Human Semant c Web If your answ
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The Human Semant c Web In the Knowl
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The Human Semant c Web ing Environm
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The Human Semant c Web Takeuchi, H.
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26 Between February 2001 and Februa
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General Adaptat on Framework Proact
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General Adaptat on Framework semant
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Ontology Creat on Methodolog es obt
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Table 5. TOVE methodology Ontology
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Semant c E-Bus ness Papazoglou, M.
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Distributed Patient Identification
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Web Serv ce Messages amination, or
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Web Serv ce Messages The full shara
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Web Serv ce Messages standards. For
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Web Serv ce Messages Figure 4 depic
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Figure 6. An example SimilarTo patt
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Figure 12. Target instance 8351-9
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Web Serv ce Messages 0 Brujin, J.,
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About.the.Authors About the Authors
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About the Authors 0 Veli. Bicer. is
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About the Authors 0 in refereed jou
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About the Authors 0 partment (1992)
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About the Authors Anton.Naumenko.is
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About the Authors Centre and head o
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consumer-centric business model 30
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semantic e-business 214 semantic in
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