Web search engines such as Google have made people “smarter” by making knowledge readily available whenever we need to look up a fact, evaluate options or learn about a topic. The Semantic Web effort aims to make such knowledge accessible to computer programs by encoding it on the web in machine interpretable form using RDF and OWL. As the volume of RDF encoded knowledge on the Web grows, software agents will need their own search engines to help them find the relevant and trustworthy knowledge needed to carry our their tasks. We will discuss the general issues underlying the indexing and retrieval of RDF based information and describe Swoogle, a crawler based search engine whose index contains information on over 700,000 RDF documents. Swoogle also serves human knowledge engineers by providing a means for them to find ontologies, terms and data and to understand how and by whom they are being used.

We will describe Swoogle 3.0 (to be released in January 2006), its new knowledge navigation model and ranking algorithms, new web service APIs and support for specialized collections.

[1] Li Ding, Tim Finin, Anupam Joshi, Rong Pan, R. Scott Cost, Joel Sachs, Vishal Doshi, Pavan Reddivari and Yun Peng, Swoogle: A Search and Metadata Engine for the Semantic Web, Proc. 13th ACM Conf. on Information and Knowledge Management, Washington DC, November 2004.

[2] Li Ding, Tim Finin, Anupam Joshi, Yun Peng, Rong Pan and Pavan Reddivari, Search on the Semantic Web, IEEE Computer, October 2005.

[3] Li Ding, Rong Pan, Tim Finin, Anupam Joshi, Yun Peng and Pranam Kolari, Finding and Ranking Knowledge on the Semantic Web, Proc. 4th Int. Semantic Web Conf., Galway IE, Nov. 2005.