298 Pages 146 Color Illustrations
    by A K Peters/CRC Press

    298 Pages 146 Color Illustrations
    by A K Peters/CRC Press

    298 Pages 146 Color Illustrations
    by A K Peters/CRC Press

    Visualizing with Text uncovers the rich palette of text elements usable in visualizations from simple labels through to documents. Using a multidisciplinary research effort spanning across fields including visualization, typography, and cartography, it builds a solid foundation for the design space of text in visualization. The book illustrates many new kinds of visualizations, including microtext lines, skim formatting, and typographic sets that solve some of the shortcomings of well-known visualization techniques.

    Key features:

    • More than 240 illustrations to aid inspiration of new visualizations
    • Eight new approaches to data visualization leveraging text
    • Quick reference guide for visualization with text
    • Builds a solid foundation extending current visualization theory
    • Bridges between visualization, typography, text analytics, and natural language processing

    The author website, including teaching exercises and interactive demos and code, can be found here. Designers, developers, and academics can use this book as a reference and inspiration for new approaches to visualization in any application that uses text.

    Contents

    List of Figures and Credits , xvii

    Foreword, xxiii

    Preface, xxvii

    About the Author, xxix

    Part I Defining Text Elements

    Chapter 1 ◾ Why Visualize with Text? 3

    1.1 WHY TEXT? 3

    1.2 500 YEARS OF PUSHING TEXT OUT OF VISUALIZATIONS 4

    1.3 (RE)LEARNING FROM HISTORY 10

    1.3.1 Cartography 10

    1.3.2 Typography 11

    1.3.3 Tables 13

    1.3.4 Science Classification and Notation 14

    1.3.5 Code Editors 18

    1.3.6 Alphanumeric Charts 19

    1.3.7 Art and Poetry 20

    1.3.8 Graphic Design and Advertising 20

    1.3.9 Comics 22

    1.3.10 Post-Modern Text 23

    1.3.11 Data Visualization 24

    1.4 FURTHER READING 26

    Chapter 2 ◾ The Design Space of Visualization with Text 27

    2.1 IS TEXT VISUALIZATION? 27

    2.1.1 Visualization as Visual Patterns 28

    2.1.2 Visualization as Organized Inventory 30

    2.1.3 Visualization as Communication 31

    2.2 VISUALIZATION DESIGN SPACE TODAY 31

    2.2.1 Visualization Anatomy 31

    2.2.2 Visualization Encoding 31

    2.3 PREPROCESSING TEXT FOR THE VISUALIZATION PIPELINE 36

    2.4 DERIVING A VISUALIZATION PIPELINE FOR TEXT 37

    2.5 FURTHER READING 40

    Chapter 3 ◾ Characterizing Text 43

    3.1 LITERAL DATA 43

    3.1.1 Functional Benefits: The Data Contains Text 44

    3.1.2 Perceptual Benefits: Fast, Efficient Access to Detail 44

    3.1.3 Cognitive Benefits: Reasoning Aid 47

    3.1.4 Language Constraints 48

    3.2 TYPOGRAPHIC ATTRIBUTES 49

    3.2.1 Alphanumeric Glyphs (i.e. Letters and Numbers) 50

    3.2.2 Symbols and Paired Delimiters 51

    3.2.3 Weight (and Bold) 52

    3.2.4 Oblique Angle (and Italic) 53

    3.2.5 Underlines 54

    3.2.6 Case (Upper, Lower, Small Caps, and Proper) 55

    3.2.7 Width (Condensed/Expanded, Scaling, and Spacing) 56

    3.2.8 Typeface (i.e. Font) 57

    3.2.9 Low-Level Font Parameters: X-Height, Contrast, Stress,

    Serif Types, etc. 59

    3.2.10 Shifting Baseline and Text on a Path 61

    3.3 NON-TYPE VISUAL ATTRIBUTES 62

    3.3.1 Size 63

    3.3.2 Rotation 64

    3.3.3 Fill Color 64

    3.3.4 Outline and Outline Color 64

    3.3.5 Gradients or Drop-Shadows 65

    3.3.6 Superimposition and Contrast 66

    3.3.7 Distortion and Extrusion 66

    3.3.8 3D Orientation 66

    3.3.9 Motion 67

    3.3.10 More: Texture, Blur, Transparency, Etc. 67

    3.4 MARKS AND TEXT SCOPE 67

    3.4.1 Point Marks: Characters, Codes, Syllables, and Words 68

    3.4.2 Line Marks: Phrases and Sentences 69

    3.4.3 Area Marks: Paragraphs and Chapters 69

    3.4.4 Readability of Text 71

    3.5 TEXT LAYOUTS: PROSE, TABLES, AND LISTS 71

    3.5.1 Prose 71

    3.5.2 Tables 72

    3.5.3 Lists and Indices 73

    3.6 TEXT INTERACTIONS 74

    3.7 TEXT CHARACTERIZATION FOR VISUALIZATION DESIGN

    SUMMARY 76

    3.8 FURTHER READING 77

    Chapter 4 ◾ Using the Design Space 79

    4.1 STRUCTURED DATA AND BERTIN’S PERMUTATIONS 80

    4.2 UNSTRUCTURED DATA ANALYSIS AND NLP 82

    4.3 MULTIPLE ATTRIBUTES 85

    4.4 ROLES FOR TEXT IN VISUALIZATIONS 86

    4.5 VISUALIZATION BUSINESS OPPORTUNITIES 90

    4.6 FURTHER READING 93

    Part II Labels

    Chapter 5 ◾ Point Labels 97

    5.1 LABELS AS POINT MARKS 97

    5.2 READING IS FASTER THAN INTERACTING 97

    5.3 CODES AS LABELS 99

    5.4 FULL LABELS 102

    5.5 GROUP LABELS AND VERY LONG LABELS 104

    5.6 MANY LABELS AND LONG LABELS 106

    5.7 MASSIVE DATA, LABELS, AND ZOOM 108

    5.8 FURTHER READING 110

    Chapter 6 ◾ Distributions 111

    6.1 HIGHLIGHTING VALUES IN STEM AND LEAF PLOTS 112

    6.2 LITERAL LEAVES 113

    6.2.1 Literal Leaves Showing Alphanumeric Codes 113

    6.2.2 Literal Leaves Showing Words and Phrases 114

    6.3 LITERAL STEMS AND LITERAL LEAVES 116

    6.3.1 Literal Stems and Leaves with Codes 116

    6.3.2 Literal Stems and Leaves with Words 118

    6.3.3 Literal Stems and Leaves with Phrases 120

    6.4 STEMS AND LEAF HIERARCHIES AND GRAPHS 121

    6.4.1 Simple Stems and Leaf Hierarchy 121

    6.4.2 Stems and Leaf Graph 122

    6.4.3 Stems and Leaf Hierarchies on a Corpus 124

    6.5 STEMS AND LEAF INTERACTIONS 125

    6.6 FURTHER READING 130

    Chapter 7 ◾ Microtext Lines 131

    7.1 TEXT ON PATHS 131

    7.2 THE NEED TO VISUALIZE MANY TIMESERIES 132

    7.2.1 Line Charts with Many Lines 135

    7.2.2 Microtext and River Labels with Many Lines 138

    7.2.3 Do Microtext Lines Work? 140

    7.2.4 Interactive Microtext Line Charts 141

    7.3 MICROTEXT APPLIED TO OTHER VISUALIZATION LAYOUTS 143

    7.4 FURTHER READING 144

    Part III Formats

    Chapter 8 ◾ Sets and Categories 149

    8.1 CHALLENGES VISUALIZING MULTIPLE CATEGORIES 149

    8.2 INDICATING SET MEMBERSHIP WITH TEXT 151

    8.3 TYPOGRAPHIC VENN AND EULER DIAGRAMS 153

    8.4 TYPOGRAPHIC GRAPHS 156

    8.5 TYPOGRAPHIC SCATTERPLOTS 161

    8.6 TYPOGRAPHIC MOSAIC PLOTS 162

    8.7 TYPOGRAPHIC BAR CHARTS WITH STACKED LABELS 165

    8.8 HANDLING MANY CATEGORIES 168

    8.8.1 Many Different Visual Attributes 168

    8.8.2 Visual Attributes Applied to Individual Characters 171

    8.8.3 Decoding vs. Noticing a Difference 171

    8.8.4 Going Further 172

    8.9 FURTHER READING 172

    Chapter 9 ◾ Maps and Ordered Data 175

    9.1 PROBLEMS WITH THEMATIC MAPS 176

    9.2 TYPOGRAPHIC THEMATIC MAP WITH A SINGLE ORDERED

    VARIABLE 177

    9.3 MULTI-VARIATE TYPOGRAPHIC THEMATIC MAPS 179

    9.4 HANDLING LONG LABELS 180

    9.5 SCALING TO THOUSANDS OF LABELS 180

    9.6 NON-DISTORTED TYPOGRAPHIC MAPS 181

    9.7 TYPOGRAPHIC SCOPE: PARAGRAPHS AND GLYPHS 181

    9.8 DO TYPOGRAPHIC THEMATIC MAPS WORK? 184

    9.9 TYPOGRAPHIC ORDERING WITH OTHER ATTRIBUTES AND

    LAYOUTS 186

    9.10 FURTHER READING 187

    Chapter 10 ◾ Ratios and Quantitative Data 189

    10.1 QUANTITATIVE DATA 189

    10.2 PROPORTIONS ALONG A STRING (BAR CHARTS WITH LONG

    LABELS) 190

    10.2.1 Proportions along Words and Phrases 190

    10.2.2 Proportions along Lines of Text 191

    10.2.3 Proportions to Indicate Ranges 191

    10.2.4 Proportions, Distributions, and Areas 192

    10.2.5 Proportions in Paragraphs 196

    10.2.6 Stacked Proportions 200

    10.2.7 Multiple Proportions 200

    10.2.8 Semantic Proportions and Expressive Text 203

    10.3 POSITIONS ALONG A STRING 204

    10.4 CAVEATS, ISSUES, AND LIMITATIONS 205

    Part IV Text Layouts

    Chapter 11 ◾ Prose and Prosody 211

    11.1 ENHANCED READING 211

    11.2 SKIM FORMATTING 212

    11.3 FORMATTING LETTERS FOR PRONUNCIATION, SPELLING, AND

    PROSODY 218

    11.4 FURTHER READING 220

    Chapter 12 ◾ SparkWords 221

    12.1 HISTORIC PRECEDENT FOR SPARKWORDS 221

    12.2 SPARKWORDS DEFINED 222

    12.3 SPARKWORDS IN NARRATIVE 222

    12.3.1 Categoric SparkWords 222

    12.3.2 Ordered SparkWords 223

    12.3.3 Quantitative SparkWords 228

    12.4 SPARKWORDS IN LISTS 230

    12.5 SPARKWORDS IN TABLES 230

    12.5.1 Orders of Magnitude 230

    12.5.2 Tables with Data Added into Typographic Formats 233

    12.6 FURTHER READING 237

    Chapter 13 ◾ Opportunity and Checklist 239

    13.1 VALIDATION 242

    13.2 CHECKLIST 242

    13.2.1 Language 242

    13.2.2 Legibility 243

    13.2.3 Alphanumeric Codes 244

    13.2.4 Formats 244

    13.2.5 Long Labels 245

    13.2.6 Layout Challenges 246

    13.2.7 Typeface 246

    13.2.8 Interactions 247

    13.2.9 More 247

    Chapter 14 ◾ References 249

    14.1 ACKNOWLEDGMENTS 249

    14.2 PEER-REVIEWED RESEARCH 249

    BIBLIOGRAPHY 252

    INDEX, 263

    Biography

    Richard Brath has been actively involved in the research, design, and development of data visualization and visual analytics since 1990. His research interests include exploration of the boundaries of visualization – such as this book regarding text and visualization – as well as graph visualization, automated insights, 3D, spreadsheets, aesthetics, and machine learning. From a commercial perspective, Richard focuses on the creation of unique, innovative visualizations that are in use by hundreds of thousands of users. Richard originally acquired a degree in architecture and worked in industrial design, special effects, and 3D animation. With the opportunity to solve business challenges with interactive computer graphics, Richard switched to visualization, creating one of the first interactive 3D financial visualizations on the web (1996). Richard is a partner at Uncharted Software, where his team creates a wide variety of visualizations, ranging from small mobile screens to multi-screen video walls. These visualizations are used in domains such as financial markets, professional sports, health care, journalism, and customer analytics. Richard has a personal blog at richardbrath.wordpress.com.

    “A treasure trove of inspiring ideas presented in 250 mind expanding examples, systematic, yet playful; complex, yet simply astonishing.

    Richard Brath’s delightful tour shows how to integrate text into visualizations and visualizations into text. His charming old examples and eye-opening fresh ideas show readers a remarkable range of possibilities.

    Wow! This delightful book shows so many fresh ideas and novel visualizations that I had to rethink what I believed was possible. Richard Brath’s book expands my mind in ways I never thought possible.  What fun!”

    --Ben Shneiderman, University of Maryland

    "Attention graphic designers! This is an important and serious book. It’s a delightful invitation to follow Richard Brath down lots of information-related rabbit holes. Brath has collected hundreds of examples of text visualizations from medieval manuscripts to contemporary big data graphics and has designed a hundred more new kinds of text visualizations. Come to think of it, Attention all readers!"

    -- Nigel HolmesGraphic Designer, Author, Former Graphics Director, Time Magazine

    “A systematic study of how text functions as an element of design, not just as a carrier of content but as an intrinsic tool in presenting and organizing that content. Well illustrated and clearly described.”

    --John Berry, past president of ATypI (Association Typographique Internationale) 

    “Text with imagery is an important tool for supporting effective visual communication. The value of text is seldom exploited to its potential, particularly in the context of information visualization. There is a need for helping people see and understand their data, and effective text can provide takeaways and narratives when combined with charts. I am delighted to endorse Richard Brath’s upcoming book, Visualizing with Text as it serves a useful perspective of visualization with text. The repertoire of topics with thoughtful examples offers the reader an appreciation for the role of text in supporting a better semantic understanding of data.”

    --Vidya Setlur, Principal Research Scientist, Tableau Software