Finding knowledge, data and answers on the Semantic Web

Web search engines like Google have made us all smarter by providing ready access to the world's knowledge whenever we need to look up a fact, learn about a topic or evaluate opinions. The W3C's Semantic Web effort aims to make such knowledge more accessible to computer programs by publishing it in machine understandable form.

As the volume of Semantic Web data grows software agents will need their own search engines to help them find the relevant and trustworthy knowledge they need to perform 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 a million RDF documents.

We will illustrate its use in several Semantic Web related research projects at UMBC including a distributed platform for constructing end-to-end use cases that demonstrate the semantic web’s utility for integrating scientific data. We describe ELVIS (the Ecosystem Location Visualization and Information System), a suite of tools for constructing food webs for a given location, and Triple Shop, a SPARQL query interface which searches the Semantic Web for data relevant to a given query ELVIS functionality is exposed as a collection of web services, and all input and output data is expressed in OWL, thereby enabling its integration with Triple Shop and other semantic web resources.