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<p>Acknowledgments ix</p> <p>About the Authors xi</p> <p>About the Technical Editor xii</p> <p>Foreword by <i>Pat Hanrahan</i> xiii</p> <p>Introduction xv</p> <p><b>Part A: Perception 1</b></p> <p><b>Chapter 1: The Science Behind Perception 3</b></p> <p>Seeing and Understanding Imagery 3</p> <p>Color Cognition 6</p> <p>Saccade and Directed Attention 10</p> <p>The Notion of Space and Spatial Cognition 11</p> <p>Diagramming the World 13</p> <p>Summary 20</p> <p><b>Chapter 2: Perception in Charts 21</b></p> <p>Visualization and Task 23</p> <p>Chart as an Informational Unit 24</p> <p>Unboxing Functional Aesthetics in the Physical World 27</p> <p>Recursive Proportions 28</p> <p>The Digitized Space: Creating Experiences on the Screen 31</p> <p>Summary 34</p> <p><b>Chapter 3: Charts in Use 35</b></p> <p>The First Charts 36</p> <p>Standardizing Visualization 40</p> <p>The Shifting Role of Data Visualization 43</p> <p>Maturity within the Profession 49</p> <p>Summary 56</p> <p><b>Part B: Semantics 57</b></p> <p><b>Chapter 4: Coming to Terms 59</b></p> <p>Statistical Graphics Are Inherently Abstract 60</p> <p>Flattening the Curve 63</p> <p>Toward Meaningful Depictions 65</p> <p>Situating with Semiotics 68</p> <p>Summary 69</p> <p><b>Chapter 5: Vagueness and Ambiguity 71</b></p> <p>How Tall Is Tall? 71</p> <p>Spicy or Hot—What’s</p> <p>the Difference? 76</p> <p>Clarification, Repair, and Refinement 78</p> <p>Iconicity of Representation 80</p> <p>The Art of Chart 82</p> <p>Summary 85</p> <p><b>Chapter 6: Data Literacy 87</b></p> <p>Navigating Data Literacy 89</p> <p>The Impact of Writing 90</p> <p>Data Orality 92</p> <p>Changing Exposition Styles 96</p> <p>Data Literacy Democratization 97</p> <p>Summary 99</p> <p><b>Chapter 7: Data Preparation 101</b></p> <p>Hairy Dates 102</p> <p>Common Transformations 103</p> <p>Clarity in Conversation 107</p> <p>Shaping for Intent 109</p> <p>Prepping for the Future 110</p> <p>Data Enrichment 113</p> <p>Summary 115</p> <p><b>Chapter 8: Scaling It Down 117</b></p> <p>Generalization 118</p> <p>Natural Sizes 119</p> <p>Fat Fingers and Small Screens 120</p> <p>Color as a Function of Size 123</p> <p>Thumbnails and Visual Summaries 124</p> <p>Summary 128</p> <p><b>Chapter 9: Cohesive Data Messages 129</b></p> <p>Cohesion in Designing Visualizations 131</p> <p>Analytical Conversation 144</p> <p>Summary 152</p> <p><b>Chapter 10: Text and Charts 153</b></p> <p>Medium Being the Message 154</p> <p>Types of Text 155</p> <p>Balancing Text with Charts 161</p> <p>Chart and Text Agreement 163</p> <p>Text in Analytical Conversation 166</p> <p>Making Data More Accessible 168</p> <p>Text for Supporting Reading Fluency 170</p> <p>Summary 171</p> <p><b>Part C: Intent 173</b></p> <p><b>Chapter 11: Defining and Framing 175</b></p> <p>Analytical Intent 176</p> <p>Register 178</p> <p>Repair and Refinement 179</p> <p>Pragmatics 181</p> <p>Practicing Intent 182</p> <p>Summary 185</p> <p><b>Chapter 12: Visual Communication 187</b></p> <p>Do What I Mean, Not What I Say 189</p> <p>Register in Charts 192</p> <p>Registers in Composition 194</p> <p>Mood and Metaphor 197</p> <p>Beyond Language Communication 197</p> <p>Expansion and Contraction 200</p> <p>Summary 201</p> <p><b>Chapter 13: Scaffolds 203</b></p> <p>Visualization Scaffolding 206</p> <p>Scaffolding Data Discovery 210</p> <p>Scaffolding Natural Language Recommendations 213</p> <p>Analytical Conversation to Repair and Refine 217</p> <p>Summary 221</p> <p><b>Chapter 14: Balancing Emphasis 223</b></p> <p>Individual Choices 224</p> <p>Collective Choices 225</p> <p>Correcting Common Problems 228</p> <p>View Snapping 232</p> <p>Summary 238</p> <p><b>Chapter 15: Mode 239</b></p> <p>Navigate Like a Local 241</p> <p>Revisiting Analytical Chatbots 247</p> <p>Video Killed the Radio Star 249</p> <p>Beyond the Desktop 251</p> <p>Future Forward 255</p> <p>Summary 257</p> <p><b>Part D: Putting It All Together 259</b></p> <p><b>Chapter 16: Bringing Everything Together 261</b></p> <p>Addressing the Paper Towel Problem 263</p> <p>Crafting Recipes for Functional Aesthetics 267</p> <p>Summary 286</p> <p><b>Chapter 17: Close 287</b></p> <p>Data in Everything and Everywhere 288</p> <p>New Tools and New Experiences 295</p> <p>Sign-off 297</p> <p>Technical Glossary 299</p> <p>Index 305</p> <p> </p>

<p><b>VIDYA SETLUR, PhD, </b>is the head of Tableau Research. She earned her doctorate in Computer Graphics in 2005 at Northwestern University. Her expertise is in natural language processing and computer graphics, and she seeks to develop new algorithms and user interfaces that enhance communication and understanding.</p> <p><b>BRIDGET COGLEY</b> is the Chief Visualization Officer at Versalytix and is a Tableau Hall of Fame Visionary. As an American Sign Language interpreter turned analyst, her practice incorporates semantics to draw meaning in her designs. She focuses on innovative use cases in data visualization.

<p><i>This is not another book about charts</i></p> <p>What happens when a researcher and a practitioner spend hours crammed in a Fiat discussing data visualization? Beyond creating beautiful charts, they found greater richness in the craft as an integrated whole. <p>Drawing from their unconventional backgrounds, these two women take readers through a journey around perception, semantics, and intent as the triad that influences visualization. This visually engaging book blends ideas from theory, academia, and practice to craft beautiful, yet meaningful visualizations and dashboards.

<p>"Straight away, you can tell this is a labour of love – the enthusiasm and validity with which the authors describe elements from the three elements of theory, academia and practice really shine through. With backgrounds covering all three of these areas, it makes for a complete publication, full of examples not just from practical situations as a practitioner, but from theory – focusing in particular on theory of presentation, psychology, conversation and cognition. All things which influence creation of functional and aesthetic dashboards, most of which, like me, you probably hadn't considered in requisite depth until now..."<br /><b>—Neil Richards, four time Tableau Visionary and Director of Editorial for Viz For Social Good</b></p>

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