Data Visualization
Principles and Practice, Second Edition
2nd Edition
Published on 18. September 2014
617 pages
978-1-4987-5979-3 (ISBN)
Description
Designing a complete visualization system involves many subtle decisions. When designing a complex, real-world visualization system, such decisions involve many types of constraints, such as performance, platform (in)dependence, available programming languages and styles, user-interface toolkits, input/output data format constraints, integration wi
Reviews / Votes
"The second edition of Data Visualization: Principles and Practice provides a streamlined introduction to various visualization techniques. The book illustrates a wide variety of applications of data visualizations, illustrating the range of problems that can be tackled by such methods, and emphasizes the strong connections between visualization and related disciplines such as imaging and computer graphics. It covers a wide range of sub-topics in data visualization: data representation; visualization of scalar, vector, tensor, and volumetric data; image processing and domain modeling techniques; and information visualization." --Timothy King, Solutions Review"An ideal textbook for academic course work and should be an integral part of all academic library instructional reference collections."
-Michael J. Carson, Midwest Book Review
More details
Edition
2nd edition
Language
English
Place of publication
London
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
Professional and scholarly
Product notice
Reflowable
ISBN-13
978-1-4987-5979-3 (9781498759793)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Book
09/2014
2nd Edition
A K Peters
€111.50
Shipment within 15-20 days
Person
Alexandru C. Telea, Professor of Visual Data Analytics at the Department of Information and Computing Sciences, Utrecht University. Former professor of Multiscale Visual Analytics in the Scientific Visualization and Computer Graphics (SVCG) group at the Bernoulli Institute, Faculty of Science and Engineering, University of Groningen.
Content
Introduction. Computer Graphics and Visualization. Discrete Data Representation in (Scientific) Visualization Applications. Visualization Pipeline. Fundamental Techniques for Scalar Visualization. Vector Visualization Techniques. Tensor Visualization Techniques. Domain Modeling Techniques. Scientific Visualization and Signal/Image Processing. Scalar Visualization. Information Visualization (Infovis) Techniques. The Value and Price of Visualization. Challenges and Prospects of the Visualization Field. Appendix.
