Topic maps, RDF graphs, and ontologies visualization

Abstract

Information retrieval in current information systems has become very difficult. These systems' complexity is due to the large volume of data, their lack of structure, and theirmultidimensionality. The SemanticWeb Initiative, proposed byTimBerners-Lee (2001), aims at making computers process datamore efficiently by adding semantics-such as definitions or relationships-between resources on the Web. The Semantic Web is not intended to replace the currentWeb, but to extend it. Several levels compose the SemanticWeb, thus providing several degrees of expressivity: • XML is a first level of semantics, which allows users to structure data with regard to their content rather than their presentation (Yergeau et al., 2004). • However, more semantics can be added with the Resource Description Framework (RDF) or Topic Maps standards. RDF was developed by the World Wide Web Consortium (1999) whereas Topic Maps were defined by the International Organization for Standardization (1997). The Topic Map paradigm was adapted to theWeb by the TopicMaps.Org Consortium (2001). Both RDF and TopicMaps aim at representing knowledge about information resources by annotating them. • Ontologies generally consist of a taxonomy-or vocabulary-and of inference rules such as transitivity and symmetry. Ontologies may be used in conjunction with RDF or Topic Maps (e.g., to allow consistency checking or to infer new information). • The Semantic Web architecture also defines more expressive layers that provide further reasoning capabilities; they will not be developed in this chapter. With such standards, any data on the Web may now be annotated semantically. Does this mean that the problem ofWeb mining is solved? Unfortunately not, but we are definitely on the right way toward a really more efficient information retrieval on the (Semantic)Web.