 |
    |
Towards a Global Scale Semantic Web
Zhengxiang Pan
Department of Computer Science and Engineering, Lehigh University, 19 Memorial Dr. West, Bethlehem, PA 18015, U.S.A.zhp2@lehigh.edu
Abstract. By transforming the Web from a collection of documents to a collection of semantically rich data sources, the Semantic Web promises an unprecedented benefit of a global knowledge infrastructure. My PhD research will try to help make that happen at a global scale by doing the following proposed work:
1. Design and implement a highly scalable Semantic Web knowledge base system by exploiting modern relational database technologies combined with the state-of-the-art description logics reasoners.
2. Build and empirically verify a framework that handles ontology evolution and the reuse of data on top of the perspective theory [1]. This framework should be able to relieve inconsistency and heterogeneity in a global scale Semantic Web.
3. Systematically evaluate the resulting system’s capability and scalability in processing, integrating and querying data under the real world environment.
LNCS 4273, p. 986 f.
lncs@springer.com
© Springer-Verlag Berlin Heidelberg 2006