  More information is now being published in machine processable form on the
web and, as de-facto distributed knowledge bases are materializing, partly
encouraged by the vision of the Semantic Web, the focus is shifting from the
publication of this information to its consumption. Platforms for data
integration, visualization and analysis that are based on a graph
representation of information appear first candidates to be consumers of
web-based information that is readily expressible as graphs. The question is
whether the adoption of these platforms to information available on the
Semantic Web requires some adaptation of their data structures and semantics.
Ondex is a network-based data integration, analysis and visualization platform
which has been developed in a Life Sciences context. A number of features,
including semantic annotation via ontologies and an attention to provenance and
evidence, make this an ideal candidate to consume Semantic Web information, as
well as a prototype for the application of network analysis tools in this
context. By analyzing the Ondex data structure and its usage, we have found a
set of discrepancies and errors arising from the semantic mismatch between a
procedural approach to network analysis and the implications of a web-based
representation of information. We report in the paper on the simple methodology
that we have adopted to conduct such analysis, and on issues that we have found
which may be relevant for a range of similar platforms
