[[abstract]]The Internet resources organization has recently become one of the most important topics in Library and Information Science fields. Generally speaking, resources organized by libraries are presented in physical forms. They are similar in nature, well-defined, and relatively stable. In contrast, resources available on the Internet are massive, heterogeneous, distributed, and proliferative. Besides, their contents and site address change frequently. Both the thesauri and metadata built by libraries and the knowledge representation languages developed by artificial intelligence fields such as CycL, Loom, and KIF cannot be used directly to process semi-structured resources found on the Web. In other words, when generating a Web knowledge representation, all characteristics of Internet resources must be taken into careful consideration before coming up with a feasible solution. In order to organize Internet Resources and to represent Web knowledge, World Wide Web Consortium (W3C) and International Organization for Standardization (ISO) respectively proposed the Resource Description Framework (RDF) and the Topic Maps in 2000. Both RDF and Topic Maps were developed to manifest knowledge association of humans and were able to provide a data model of semantic interoperability for ontology. However, the original purposes of these two languages were not identical; each has its own interchange syntax. Therefore, the author believed that it’s necessary to find out the differences in the representation of knowledge association, the strengths and weaknesses, and the application feasibility between RDF and Topic Maps. Specifically, this study tries to answer the following research questions: 1. What are the trends in the development of the Web knowledge representation? 2. What are the similarities and differences in syntax for expressing the association of resources or topics between RDF and Topic Maps? What are the semantics these two languages can describe? To what extent can they apply? 3. When organizing Internet Resources, are RDF and Topic Maps feasible in libraries? The author observed trends in the development of Web knowledge representation through literature review. By comparing syntax and analyzing the outcomes of practically applying RDF/XML and XTM in National Central Library’s “Selected Internet Resources Website”, the author explored several similarities and differences in syntax, semantics, and the feasibility of Internet resources organization between RDF and Topic Maps. The results of this study are divided into three parts. The first part concerns the trends in the development of the Web knowledge representation. On a macro scale, the author finds the trend of establishing and sharing knowledge among humans and the trend of helping machines manage resources automatically, thereby enhancing the effectiveness of humans handling resources available on the Web. The second part is the comparison of knowledge representation capability between RDF and Topic Maps. The author discovered that there are differences in element, syntax, semantic representation, and application between RDF and Topic Maps. In addition, each one has its own advantages in helping browsing, information retrieval, information filtering, and resource integration. The third part is about the feasibility of the application of RDF and Topic Maps in libraries. The experiments show that Websites written by RDF/XML and XTM are flexible and extensible in classification structure. Besides, the resources in theses Websites can be browsed by different facets. Their interoperability of classification structures, resources integration, and automated processing capabilities of machines are better than Websites not written by these languages. Finally, this study offers suggestions for RDF and Topic Maps in syntax, application, and their practical application. On syntax part, it is suggested that the written format of RDF/XML should be limited. There are three suggestions for XTM. First, URI is recommended to serve as a reference for subject identity. Second, XTM should support XML Schema. Finally, the direction of association between topics should be restricted. On application part, the author suggests two ways that can be used to describe resources and index subjects at the same time. One is to use RDF/XML in resource description and to use XTM in subject index, then to build links between subjects and resources. The other is to use RDF/XML completely. In RDF/XML, subject index can be built by establishing classes of subjects and using properties to indicate the hierarchical relationships and correlations between classes. Furthermore, the author encourage members of a community to use identical vocabularies (e.g. Dublin Core) and topics (e.g. “rdf:ID” reference to the same URI) to improve the sharing and integration of resources when having the same resource properties and topics. In practical application, the use of popular vocabularies and appropriate ontology is recommended.
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