This paper provides a blueprint for constructing collaborative and distributed knowledge discovery systems within Grid-based computing environments. The need for such systems is driven by the quest for sharing knowledge, information and computing resources within the boundaries of single large distributed organisations or within complex Virtual Organisations (VO) created to tackle specific projects. The proposed architecture is built on top of a resource federation management layer and is composed of a set of different resources. We show how this architecture will behave during a typical KDD process design and deployment, how it enables the execution of complex and distributed data mining tasks with high performance and how it provides a community of e-scientists with means to collaborate, retrieve and reuse both KDD algorithms, discovery processes and knowledge in a visual analytical environment.
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