Information Visualization, 3rd Edition

Table of contents

1. Cover Image
2. Table of Contents
3. Title
4. Copyright
5. Preface
6. About the Author
7. Chapter One. Foundations for an Applied Science of Data Visualization
   1. Visualization Stages
   2. Experimental Semiotics Based on Perception
   3. Semiotics of Graphics
   4. Sensory versus Arbitrary Symbols
   5. Gibson's Affordance Theory
   6. A Model of Perceptual Processing
   7. Costs and Benefits of Visualization
   8. Types of Data
   9. Metadata
   10. Conclusion
8. Chapter Two. The Environment, Optics, Resolution, and the Display
   1. The Environment
   2. The Eye
   3. The Optimal Display
   4. Conclusion
9. Chapter Three. Lightness, Brightness, Contrast, and Constancy
   1. Neurons, Receptive Fields, and Brightness Illusions
   2. Luminance, Brightness, Lightness, and Gamma
   3. Perception of Surface Lightness
   4. Monitor Illumination and Monitor Surrounds
   5. Conclusion
10. Chapter Four. Color
    1. Trichromacy Theory
    2. Color Measurement
    3. Opponent Process Theory
    4. Properties of Color Channels
    5. Color Appearance
    6. Applications of Color in Visualization
    7. Application 1: Color Specification Interfaces and Color Spaces
    8. Application 2: Color for Labeling (Nominal Codes)
    9. Application 3: Color Sequences for Data Maps
    10. Application 4: Color Reproduction
    11. Conclusion
11. Chapter Five. Visual Salience and Finding Information
    1. Eye Movements
    2. V1, Channels, and Tuned Receptors
    3. Preattentive Processing and Ease of Search
    4. Integral and Separable Dimensions: Glyph Design
    5. Representing Quantity
    6. The Searchlight Metaphor and Cortical Magnification
    7. Conclusion
12. Chapter Six. Static and Moving Patterns
    1. Gestalt Laws
    2. Texture: Theory and Data Mapping
    3. Perception of Transparency: Overlapping Data
    4. Perceiving Patterns in Multidimensional Discrete Data
    5. Pattern Learning
    6. The Visual Grammar of Node–Link Diagrams
    7. The Visual Grammar of Maps
    8. Patterns in Motion
    9. Perception of Animated Motion
    10. The Processes of Pattern Finding
13. Chapter Seven. Space Perception
    1. Depth Cue Theory
    2. Depth Cues in Combination
    3. Task-Based Space Perception
    4. Tracing Data Paths in 3D Graphs
    5. Judging the Morphology of Surfaces
    6. Patterns of Points in 3D Space
    7. Perceiving Patterns in 3D Trajectories
    8. Judging Relative Positions of Objects in Space
    9. Judging the Relative Movements of Self within the Environment
    10. Selecting and Positioning Objects in 3D
    11. Judging the “Up” Direction
    12. The Aesthetic Impression of 3D Space (Presence)
    13. Conclusion
14. Chapter Eight. Visual Objects and Data Objects
    1. Image-Based Object Recognition
    2. Structure-Based Object Recognition
    3. The Object Display and Object-Based Diagrams
    4. Faces
    5. Coding Words and Images
    6. Labels and Concepts
    7. Concept Mapping
    8. Iconic Images versus Words versus Abstract Symbols
    9. Scenes and Scene Gist
    10. Conclusion
15. Chapter Nine. Images, Narrative, and Gestures for Explanation
    1. The Nature of Language
    2. Integrating Visual and Verbal and the Narrative Thread
    3. Animated versus Static Presentations
    4. Visual Narrative
    5. Conclusion
16. Chapter Ten. Interacting with Visualizations
    1. Data Selection and Manipulation Loop
    2. Exploration and Navigation Loop
    3. Focus, Context, and Scale in Nonmetaphoric Interfaces
    4. Conclusion
17. Chapter Eleven. Visual Thinking Processes
    1. The Cognitive System
    2. Memory and Attention
    3. Long-Term Memory
    4. Knowledge Formation and Creative Thinking
    5. Visualizations and Mental Images
    6. Review of Visual Cognitive System Components
    7. Visual Thinking Algorithms
    8. Algorithm 1: Visual Queries
    9. Algorithm 2: Pathfinding on a Map or Diagram
    10. Algorithm 3: Reasoning with a Hybrid of a Visual Display and Mental Imagery
    11. Algorithm 4: Design Sketching
    12. Algorithm 5: Brushing
    13. Algorithm 6: Small Pattern Comparisons in a Large Information Space
    14. Algorithm 7: Degree-of-Relevance Highlighting
    15. Algorithm 8: Generalized Fisheye Views
    16. Algorithm 9: Multidimensional Dynamic Queries with Scatter Plot
    17. Algorithm 10: Visual Monitoring Strategies
    18. Conclusion
18. APPENDIX A. Changing Primaries
19. APPENDIX B. CIE Color Measurement System
20. APPENDIX C. The Perceptual Evaluation of Visualization Techniques and Systems
21. APPENDIX D. Guidelines
22. Bibliography
23. Index