Data Visualization

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The goal of data visualization is to use images to improve our understanding of a dataset, drawing on techniques from mathematics, computer science, cognitive and perception science, and physics. In this introductory text, the author provides a compact introduction to the field that allows readers to learn about visualization techniques. The material focuses on those techniques and methods that have a broad applicability in visualization applications, occur in most practical problems in various guises, and do not demand a specialized background to be understood. However, the author has also included a number of less mainstream visualization techniques. With these methods, the book aims to give the reader an idea of the large variety of applications of data visualizations, illustrate the wide range of problems that can be tackled by such methods, and also emphasize the strong connections between visualization and related disciplines such as imaging and computer graphics.

Theory and algorithms for a wide range of visualization techniques are presented, as well as practical examples in C++ and OpenGL. Specific techniques covered include:

• scalar visualization
• vector visualization
• tensor visualization
• domain modeling
• image visualization
• volume visualization

information visualization