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Abstract: To run scientific and business applications distributed computing environments, like Grids and Clouds, must support adaptive knowledge discovery and data mining applications by offering resources, services, and decentralized data analysis methods. In particular, according to the service oriented architecture (SOA) model, data mining tasks and knowledge discovery processes can be delivered as services in Grid and Cloud computing infrastructures.
Through a service-based approach we can define integrated services for supporting distributed scientific data analysis tasks in Grids and Clouds. Those services can address all the tasks that must be considered in knowledge discovery processes from data selection and transport, to data analysis, knowledge model representation and visualization. We are working along this direction by providing service-oriented architectures and services for distributed knowledge discovery.
This collection of data mining services composes an Open Service Framework for Distributed Knowledge Discovery. This framework allows developers to design distributed KDD processes as a composition of services that are available over HPC computers and large scale distributed infrastructures (e.g., from a single Cloud to Interclouds).
Here we describe a strategy based on the use of services for the design of open distributed knowledge discovery services and outline how Grid and Cloud application frameworks can be developed as a collection of services.
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