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More information is now being published in machine processable form on theweb and, as de-facto distributed knowledge bases are materializing, partlyencouraged by the vision of the Semantic Web, the focus is shifting from thepublication of this information to its consumption. Platforms for dataintegration, visualization and analysis that are based on a graphrepresentation of information appear first candidates to be consumers ofweb-based information that is readily expressible as graphs. The question iswhether the adoption of these platforms to information available on theSemantic Web requires some adaptation of their data structures and semantics.Ondex is a network-based data integration, analysis and visualization platformwhich has been developed in a Life Sciences context. A number of features,including semantic annotation via ontologies and an attention to provenance andevidence, make this an ideal candidate to consume Semantic Web information, aswell as a prototype for the application of network analysis tools in thiscontext. By analyzing the Ondex data structure and its usage, we have found aset of discrepancies and errors arising from the semantic mismatch between aprocedural approach to network analysis and the implications of a web-basedrepresentation of information. We report in the paper on the simple methodologythat we have adopted to conduct such analysis, and on issues that we have foundwhich may be relevant for a range of similar platforms

Lost in translation: data integration tools meet the Semantic Web (experiences from the Ondex project)