Abstract. To date, the majority of Web search engines have provided simple keyword search interfaces that present the results as a ranked list of hyperlinks. More recently researchers have been investigating interactive, graphical and multimedia approaches which use ontologies to model the knowledge space. Such systems use the semantic relationships to structure the assimilated search results into interactive semantic graphs or hypermedia presentations which enable the user to quickly and easily explore the results and detect previously unrecognized associations. More recently, the proliferation of eResearch communities has led to a demand for search interfaces which automate the discovery, analysis and assimilation of multiple information sources in order to prove or disprove a particular scientific theory or hypothesis. We believe that such semiautomated analysis, assimilation and hypothesis-driven approaches represent the next generation of search engines. In this paper we describe and evaluate such a search interface which we have developed for a particular eScience application.