The Semantic Web, as an emerging extension to the World Wide Web, is increasingly attracting the attention of research. The vision of the Semantic Web is to populate the current Web by metadata with well-defined meaning so that software agents can better process the wealth of information that is available. Amongst the building blocks of the Semantic Web, RDF provides a framework for representing the metadata describing Web resources and OWL is a language for defining ontologies that associate metadata to each other.

 
With the establishment of such standards as RDF and OWL, we could expect an increasing number of developments and deployments of systems that process the data on the “semantic web layer” and provide access services to human users or program applications. To this end, existing knowledge base engineering technologies may be exploited. However, since the Semantic Web represents much larger problem sizes than those traditionally found in Artificial Intelligence, scalability becomes a stronger and more critical requirement for a Semantic Web knowledge base system. To certain extent, the success of those systems hinges on their scalability. The importance of this issue has been widely recognized in the community.


The SSWS 2005 workshop aims at bringing together researchers and practitioners to present recent ideas and results towards addressing the above challenge. The workshop will create a forum for discussing major questions including: the evaluation of existing Semantic Web knowledge base systems and the principles, methodologies and tools for evaluating the systems; foundations, methods and technologies to improve the state-of-the-art; identification of new challenges and research directions. We also welcome participants from related disciplines such as Artificial Intelligence, Databases, and information integration.

Topics of interest include, but are not limited to:

. Semantic Web repositories;

. Query evaluation and optimization;

. Performance evaluation and benchmarks;

. Distributed knowledge base systems and P2P systems;

. Large scale knowledge base management;

. Inference and inconsistency;

. Semantic Web-based information integration