Data Visualization : Principles and Practice, Second Edition

"This book explores the study of processing and visually representing data sets. Data visualization is closely related to information graphics, information visualization, scientific visualization, and statistical graphics. This second edition presents a better treatment of the relationship between traditional scientific visualization and information visualization, a description of the emerging field of visual analytics, and updated techniques using the GPU and new generations of software tools and packages. This edition is also enhanced with exercises and downloadable code and data sets"-- Read more... Abstract: "This book explores the study of processing and visually representing data sets. Data visualization is closely related to information graphics, information visualization, scientific visualization, and statistical graphics. This second edition presents a better treatment of the relationship between traditional scientific visualization and information visualization, a description of the emerging field of visual analytics, and updated techniques using the GPU and new generations of software tools and packages. This edition is also enhanced with exercises and downloadable code and data sets" This Book Explores The Study Of Processing And Visually Representing Data Sets. Data Visualization Is Closely Related To Information Graphics, Information Visualization, Scientific Visualization, And Statistical Graphics. This Second Edition Presents A Better Treatment Of The Relationship Between Traditional Scientific Visualization And Information Visualization, A Description Of The Emerging Field Of Visual Analytics, And Updated Techniques Using The Gpu And New Generations Of Software Tools And Packages. This Edition Is Also Enhanced With Exercises And Downloadable Code And Data Sets-- From Graphics To Visualization -- Data Representation -- The Visualization Pipeline -- Scalar Visualization -- Vector Visualization -- Tensor Visualization -- Domain-modeling Techniques -- Image Visualization -- Volume Visualization -- Information Visualization -- Conclusion -- Visualization Software. Alexandru Telea. Includes Bibliographical References (pages 575-598) And Index. "This book explores the study of processing and visually representing data sets. Data visualization is closely related to information graphics, information visualization, scientific visualization, and statistical graphics. This second edition presents a better treatment of the relationship between traditional scientific visualization and information visualization, a description of the emerging field of visual analytics, and updated techniques using the GPU and new generations of software tools and packages. This edition is also enhanced with exercises and downloadable code and data sets"-- Résumé de l'éditeur "This book explores the study of processing and visually representing data sets. Data visualization is closely related to information graphics, information visualization, scientific visualization, and statistical graphics. This second edition presents a better treatment of the relationship between traditional scientific visualization and information visualization, a description of the emerging field of visual analytics, and updated techniques using the GPU and new generations of software tools and packages. This edition is also enhanced with exercises and downloadable code and data sets"-- Provided by publisher 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 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