Prototyping a Knowledge IntegrationFramework to Solve Science Problems

Key information technology advances in recent years include the emergence of distributed computing architectures based on web services; knowledge engineering efforts as evidenced by the development of science domain ontologies in the Semantic Web; and growing interest in scientific data mining as a means for automated knowledge extraction from the ever-increasing volumes of science observations and model data available. We present the results of our prototype study that bring together these key information technology components, as applied to the problem of feature extraction and morphology identification for multi-wavelength images of the Sun. We present, the science application, the linked ontologies describing both the data mining, manipulation and analysis services as well as the science domain; and a web-based user interface based on an existing smart search tool (NOESIS) which allows a user to discover and explore available data and perform the desired analysis.