Luengo, Cris
- Centre for Image Analysis, Swedish University of Agricultural Sciences
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. (C) 2010 Published by Elsevier Ltd.
Keywords
scientific visualization; information visualization; data analysis; multi-dimensional data; laser wakefield particle acceleration; 3D gene expression
Published in
Procedia Computer Science
2010, volume: 1, number: 1, pages: 1751-1758
Publisher: ELSEVIER ACADEMIC PRESS INC, 525 B STREET, SUITE 1900, SAN DIEGO, CA 92101-4495 USA
Conference
The International Conference on Computational Science 2010
SLU Authors
UKÄ Subject classification
Computer Science
Publication identifier
- DOI: https://doi.org/10.1016/j.procs.2010.04.197
Permanent link to this page (URI)
https://res.slu.se/id/publ/31857