System architectural design of multiwavelength data mining

Abstract

Data avalanche faced in astronomy, astronomical data covers from radio, infrared, optical, X-ray, even gamma ray band. Astronomy enters an all sky-survey era. Transforming data into knowledge depends on data mining techniques. How to effectively and efficiently extract knowledge from databases is an important issue. Especially mining knowledge from different bands or multiband is of great significance. In this paper, we design a system which includes four fundamental blocks: the first is used to create databases; the second for cross-matching objects from different bands, the third for mining knowledge from the large data volume and the last one for final result evaluation. The functionalities of the four blocks are described. The cross-match results are divided, and the analysis mode for each of them is touched upon. Moreover the schemes of classification, regression, clustering analysis and outlier detection are demonstrated.

Data Mining in Astronomy

“…In addition, we previously proposed an architecture for multiwavelength data mining. 11 In this system, users with no database knowledge may create their own databases and federate multiwavelength data using automated database-creation and cross-match tools. The use of such data-mining tools will enable scientists to work with large data samples.…”