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Using the Ontology Paradigm to Integrate Information Systems. Oveia: Expanding the Topic Maps frontier

Paper, was published by José Carlos Ramalho, Giovani Rubert Librelotto, Pedro Rangel Henriques, and Weber Souza at 2004-07-21

This paper describes the components of the Oveia environment to build ontologies.

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Ontology based websites are one possible implementation of the Semantic Web. There are several languages for ontology specification: RDF, OWL, Topic Maps. Topic Maps follow a structure formally specified what makes them a good choice for semantic website specification. The process of ontology development based in topic maps is complex, time consuming, and it requires a lot of human and financial resources, because they can have a lot of topics and associations, and the number of information resources can be very large. To overcome this problem a new environment is proposed, Oveia. Oveia is composed by four components which have relevant contributions to the Semantic Web area. This paper describes these components in detail. Two components representing a metadata extractor: heterogeneous data integration (through XSDS specifications) and an homogeneous intermediate data representation for the extracted metadata (datasets). The Ontology builder who builds an ontology from metadata stored in a set of datasets (construction rules are specified in a new domain specific language: XS4TM). The Ontology builder stores the result in XTM files or in relational databases according to the Topic Map structure. Finally, Ulisses, the navigational component, generates web interfaces through which is possible to move inside the topic map and among information resources.

Authors

Weber Souza

No contact information available. 

Signet_person

Weber is author of Using the Ontology Paradigm.. .

glossary

XTM1

is associated with 22 items.

Signet_glossary

XTM1 is the short name for Topic Maps XML Syntax, Version 1.0.

 

Resellers can give their customers the opportunity to apply Web 3.0 technology to their web sites with topics maps-based searching, which is more suitable for single sites than Google-style navigation.

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