Table of Contents Chapter 1 On Beauty What Is Beauty? Learning from the Classics How Do We Achieve Beauty? Putting It Into Practice Conclusion Chapter 2 Once Upon a Stacked Time Series Question + Visual Data + Context = Story Steps for Creating an Effective Visualization Hands-on Visualization Creation Conclusion Chapter 3 Wordle Wordle's Origins How Wordle Works Is Wordle Good Information Visualization? How Wordle Is Actually Used Conclusion Acknowledgments References Chapter 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 Chapter 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 Chapter 6 Flight Patterns: A Deep Dive Techniques and Data Color Motion Anomalies and Errors Conclusion Acknowledgments Chapter 7 Your Choices Reveal Who You Are: Mining and Visualizing Social Patterns Early Social Graphs Social Graphs of Amazon Book Purchasing Data Conclusion References Chapter 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 Chapter 9 The Big Picture: Search and Discovery The Visualization Technique YELLOWPAGES.COM The Netflix Prize Creating Your Own Conclusion References Chapter 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 Chapter 11 Beautiful History: Visualizing Wikipedia Depicting Group Editing History Flow in Action Chromogram: Visualizing One Person at a Time Conclusion Chapter 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 Chapter 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 Chapter 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 Chapter 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 Chapter 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 Chapter 17 Immersed in Unfolding Complex Systems Our Multimodal Arena Our Roadmap to Creative Thinking Project Discussion Conclusion References Chapter 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 Chapter 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 Chapter 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