Topological Methods in Data Analysis and Visualization

Topology-based methods are of increasing importance in the analysis and visualization of datasets from a wide variety of scientific domains such as biology, physics, engineering, and medicine. Current challenges of topology-based techniques include the management of time-dependent data, the representation of large and complex datasets, the characterization of noise and uncertainty, the effective integration of numerical methods with robust combinatorial algorithms, etc. . The editors have brought together the most prominent and best recognized researchers in the field of topology-based data analysis and visualization for a joint discussion and scientific exchange of the latest results in the field. This book contains the best 20 peer-reviewed papers resulting from the discussions and presentations at the third workshop on "Topological Methods in Data Analysis and Visualization", held 2009 in Snowbird, Utah, US. The 2009 "TopoInVis" workshop follows the two successful workshops in 2005 (Slovakia) and 2007 (Germany).

Important contribution to the field High-quality current research Growing field Includes supplementary material: sn.pub/extras

Auteur
Hans Hagen is heading the research group for Computer Graphics and Computer Geometry at the University of Kaiserslautern, Germany, and is Scientific Director of the research lab Intelligent Visualization and Simulation at the German Research Center for Artificial Intelligence (DFKI). His research domains are geometric modeling and scientific visualization.

Contenu
Foundations of Computational Topology.- Hierarchical Topological Data-Structures.- Topological Feature Extraction Algorithms.- Applications in Scientific Data Analysis and Visualization.- Topological Analysis of Large-Scale Scientific Data.- Indices.