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Procedia Comput Sci. 2010 May;1(1):1757-1764.

Coupling visualization and data analysis for knowledge discovery from multi-dimensional scientific data.

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  • 1Computational Research Division, Lawrence Berkeley National Laboratory (LBNL), One Cyclotron Road, Berkeley, CA, 94720, USA ; International Research Training Group 1131, University of Kaiserslautern, Germany.

Abstract

Knowledge discovery from large and complex scientific data is a challenging task. With the ability to measure and simulate more processes at increasingly finer spatial and temporal scales, the growing number of data dimensions and data objects presents tremendous challenges for effective data analysis and data exploration methods and tools. The combination and close integration of methods from scientific visualization, information visualization, automated data analysis, and other enabling technologies -such as efficient data management- supports knowledge discovery from multi-dimensional scientific data. This paper surveys two distinct applications in developmental biology and accelerator physics, illustrating the effectiveness of the described approach.

KEYWORDS:

3D gene expression; data analysis; information visualization; laser wakefield particle acceleration; multi-dimensional data; scientific visualization

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