
Topological Methods in Data Analysis and Visualization
Theory, Algorithms, and Applications
Springer (Publisher)
Published on 23. August 2016
Book
Paperback/Softback
VIII, 260 pages
978-3-662-50604-2 (ISBN)
Description
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).
More details
Series
Edition
Softcover reprint of the original 1st ed. 2011
Language
English
Place of publication
Berlin
Germany
Publishing group
Springer Berlin
Target group
Professional and scholarly
Illustrations
VIII, 260 p.
Dimensions
Height: 235 mm
Width: 155 mm
Thickness: 15 mm
Weight
417 gr
ISBN-13
978-3-662-50604-2 (9783662506042)
DOI
10.1007/978-3-642-15014-2
Schweitzer Classification
Other editions
Additional editions

Valerio Pascucci | Xavier Tricoche | Hans Hagen
Topological Methods in Data Analysis and Visualization
Theory, Algorithms, and Applications
Book
11/2010
1st Edition
Springer
€106.99
Shipment within 7-9 days
Content
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.