Beautiful Visualization

Preface

1. On Beauty
-What Is Beauty?
-Learning from the Classics
-How Do We Achieve Beauty?
-Putting It Into Practice
-Conclusion

2. Once Upon a Stacked Time Series
-Question + Visual Data + Context = Story
-Steps for Creating an Effective Visualization
-Hands-on Visualization Creation
-Conclusion

3. Wordle
-Wordle's Origins
-How Wordle Works
-Is Wordle Good Information Visualization?
-How Wordle Is Actually Used
-Conclusion
-Acknowledgments
-References

4. Color: The Cinderella of Data Visualization
-Why Use Color in Data Graphics?
-Luminosity As a Means of Recovering Local Density
-Looking Forward: What About Animation?
-Methods
-Conclusion
-References and Further Reading

5. Mapping Information: Redesigning the New York City Subway Map
-The Need for a Better Tool
-London Calling
-New York Blues
-Better Tools Allow for Better Tools
-Size Is Only One Factor
-Looking Back to Look Forward
-New York's Unique Complexity
-Geography Is About Relationships
-Sweat the Small Stuff
-Conclusion

6. Flight Patterns: A Deep Dive
-Techniques and Data
-Color
-Motion
-Anomalies and Errors
-Conclusion
-Acknowledgments

7. Your Choices Reveal Who You Are: Mining and Visualizing Social -Patterns
-Early Social Graphs
-Social Graphs of Amazon Book Purchasing Data
-Conclusion
-References

8. Visualizing the U.S. Senate Social Graph (1991–2009)
-Building the Visualization
-The Story That Emerged
-What Makes It Beautiful?
-And What Makes It Ugly?
-Conclusion
-References

9. The Big Picture: Search and Discovery
-The Visualization Technique
-YELLOWPAGES.COM
-The Netflix Prize
-Creating Your Own
-Conclusion
-References

10. Finding Beautiful Insights in the Chaos of Social Network Visualizations
-Visualizing Social Networks
-Who Wants to Visualize Social Networks?
-The Design of SocialAction
-Case Studies: From Chaos to Beauty
-References

11. Beautiful History: Visualizing Wikipedia
-Depicting Group Editing
-History Flow in Action
-Chromogram: Visualizing One Person at a Time
-Conclusion

12. Turning a Table into a Tree: Growing Parallel Sets into a Purposeful Project
-Categorical Data
-Parallel Sets
-Visual Redesign
-A New Data Model
-The Database Model
-Growing the Tree
-Parallel Sets in the Real World
-Conclusion
-References

13. The Design of "X by Y"
-Briefing and Conceptual Directions
-Understanding the Data Situation
-Exploring the Data
-First Visual Drafts
-The Final Product
-Conclusion
-Acknowledgments
-References

14. Revealing Matrices
-The More, the Better?
-Databases As Networks
-Data Model Definition Plus Emergence
-Network Dimensionality
-The Matrix Macroscope
-Reducing for Complexity
-Further Matrix Operations
-The Refined Matrix
-Scaling Up
-Further Applications
-Conclusion
-Acknowledgments
-References

15. This Was 1994: Data Exploration with the NYTimes Article Search API
-Getting Data: The Article Search API
-Managing Data: Using Processing
-Three Easy Steps
-Faceted Searching
-Making Connections
-Conclusion

16. A Day in the Life of the New York Times
-Collecting Some Data
-Let's Clean 'Em First
-Python, Map/Reduce, and Hadoop
-The First Pass at the Visualization
-Scene 1, Take 1
-Scene 1, Take 2
-The Second Pass at the Visualization
-Visual Scale and Other Visualization Optimizations
-Getting the Time Lapse Working
-So, What Do We Do with This Thing?
-Conclusion
-Acknowledgments

17. Immersed in Unfolding Complex Systems
-Our Multimodal Arena
-Our Roadmap to Creative Thinking
-Project Discussion
-Conclusion
-References

18. Postmortem Visualization: The Real Gold Standard
Background
-Impact on Forensic Work
-The Virtual Autopsy Procedure
-The Future for Virtual Autopsies
-Conclusion
-References and Suggested Reading

19. Animation for Visualization: Opportunities and Drawbacks
-Principles of Animation
-Animation in Scientific Visualization
-Learning from Cartooning
-Presentation Is Not Exploration
-Types of Animation
-Staging Animations with DynaVis
-Principles of Animation
-Conclusion: Animate or Not?
-Further Reading
-Acknowledgments
-References

20. Visualization: Indexed.
-Visualization: It's an Elephant.
-Visualization: It's Art.
-Visualization: It's Business.
-Visualization: It's Timeless.
-Visualization: It's Right Now.
-Visualization: It's Coded.
-Visualization: It's Clear.
-Visualization: It's Learnable.
-Visualization: It's a Buzzword.
-Visualization: It's an Opportunity.

Appendix: Contributors

Index