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An Interoperable Framework for Data Mining and Analysis of Space Science Data
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| The F-MASS research team, composed of Information Technology and Space Science researchers propose to create an interoperable Framework for Mining and Analysis of Space Science Data (F-MASS). This framework will extend an existing scientific data mining system by providing Space Science data filters, Data Mining algorithms and customized user interfaces appropriate for the Space Science research domain. Data mining techniques such as statistical analysis, pattern recognition, feature classification, and image processing will be selected for the framework using Space Science research problems as drivers for this development. The F-MASS team consists of Space Science researchers who will be working with the teams Information Technology researchers to adapt the existing ADaM data mining system to provide a comprehensive framework for Space Science data investigations. The framework will focus on problems such as the handling of large datasets inherent in the Space Science communities, the heterogeneity of the data, the incorporation of specialized data mining algorithms, and domain-specific user interfaces. The expected result of this project will be a framework that can be used across the Space Science research community for advanced data analysis and mining. The full proposal details specific Space Science research scenarios that will be used as use case drivers for F-MASS and some candidate data mining techniques that will be incorporated into the framework. |
Bibliography
| | Comparing Different Thresholding Algorithms for Segmenting Auroras
Graves, Sara; Internation Conferece on Information Technology, Las Vegas, NV,
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