Astronomy is undergoing through a methodological revolution triggered by anunprecedented wealth of complex and accurate data. The new panchromatic,synoptic sky surveys require advanced tools for discovering patterns and trendshidden behind data which are both complex and of high dimensionality. Wepresent DAMEWARE (DAta Mining & Exploration Web Application REsource): ageneral purpose, web-based, distributed data mining environment developed forthe exploration of large datasets, and finely tuned for astronomicalapplications. By means of graphical user interfaces, it allows the user toperform classification, regression or clustering tasks with machine learningmethods. Salient features of DAMEWARE include its capability to work on largedatasets with minimal human intervention, and to deal with a wide variety ofreal problems such as the classification of globular clusters in the galaxyNGC1399, the evaluation of photometric redshifts and, finally, theidentification of candidate Active Galactic Nuclei in multiband photometricsurveys. In all these applications, DAMEWARE allowed to achieve better resultsthan those attained with more traditional methods. With the aim of providingpotential users with all needed information, in this paper we briefly describethe technological background of DAMEWARE, give a short introduction to somerelevant aspects of data mining, followed by a summary of some science casesand, finally, we provide a detailed description of a template use case.
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