Information Visualization

1. Foundations for an Applied Science of Data Visualization
2. The Environment, Optics, Resolution, and the Display
3. Lightness, Brightness, Contrast, and Constancy
4. Color
5. Visual Salience and Finding Information
6. Static and Moving Patterns
7. Space Perception
8. Visual Objects and Data Objects
9. Images, Narrative, and Gestures for Explanation
10. Interacting with Visualizations
11. Visual Thinking Processes
12. Designing for Perception (new)

Visual Thinking Algorithms
Visual Queries
Pathfinding on a Map or Diagram
Reasoning with a Hybrid of a Visual Display and Mental Imagery
Design Sketching
Brushing
Small Pattern Comparisons in a Large Information Space
Degree-of-Relevance Highlighting
Generalized Fisheye Views
Multidimensional Dynamic Queries with Scatter Plot
Visual Monitoring Strategies

APPENDIX
A. Changing Primaries
B. CIE Color Measurement System
Techniques and Systems
C. Guidelines

Information Visualization: Perception for Design, Fourth Edition explores the art and science of why we see objects the way we do. Based on the science of perception and vision, the author presents the key principles at work for a wide range of applications--resulting in visualization of improved clarity, utility, and persuasiveness. This new edition has been revised and updated to include the latest relevant research findings. Content has been updated in such areas as the cognitive neuroscience of maps and navigation, the neuroscience of pattern perception, and the hierarchy of learned patterns. New changes to the book make it easier to apply perceptual lessons to design decisions, while as with previous editions, the book continues to offer practical guidelines that can be applied by anyone: interaction designers, graphic designers of all kinds (including web designers), data miners, and financial analysts.

• Includes the latest research findings in visualization and perception
• A new chapter on designing for perception to help bridge the gap between specific perception-based guidelines and common design decisions
• Packed with over 400 informative full color illustrations, which are key to understanding of the subject

Upper level undergraduate and graduate students taking data visualization courses in computer science, computer engineering, and physics departments; professionals in user interface/user interaction designer; computer graphics, research scientists and engineers; data miners; and managers faced with information-intensive challenges