1.  Though it’s popularly reported that more than 80% of brain activity is devoted to what we see, the Harvard visual perception scientist George Alvarez says the number is probably closer to 55%—still far more than for any other perceptual activity.

2.  Willard C. Brinton, Graphic Methods for Presenting Facts (The Engineering Magazine Company, 1914), 61, 82, https://archive.org/details/graphicmethodsfo00brinrich.

3.  Naveen Srivatsav, “Insights for Visualizations—Jacques Bertin & Jock Mackinlay,” hastac.org blog post, February 16, 2014, https://www.hastac.org/blogs/nsrivatsav/2014/02/16/insights-visualizations-jacques-bertin-jock-mackinlay.

4.  Jock Mackinlay, “Automating the Design of Graphical Presentations of Relational Information,” ACM Transactions on Graphics 5 (1986), http://dl.acm.org/citation.cfm?id=22950.

5.  One computer scientist and visualization expert, who asked not to be named, has described Tufte as “basically a Bauhaus designer with an understanding of statistics.”

6.  William S. Cleveland and Robert McGill, “Graphical Perception: Theory, Experimentation, and Application to the Development of Graphical Methods,” Journal of the American Statistical Association 79 (1984); “Graphical Perception and Graphical Methods for Analyzing Scientific Data,” Science 229 (1985); and William S. Cleveland, Charles S. Harris, and Robert McGill, “Experiments on Quantitative Judgments of Graphs and Maps,” Bell System Technical Journal 62 (1983).

7.  In order to get through this history quickly so that we can move on to the practical lessons, I’m skimming right over important researchers such as Stephen Kosslyn and Barbara Tversky, among others. Suffice to say that dozens of important people and papers were influential during this time.

8.  For better or worse, pie charts became anathema, while treemaps and other new procedures gained purchase.

9.  I’m also speeding past the development of visualization software. It started in the 1970s, but in the past ten years the number of tools has exploded, and their ease of use is one of their core selling points. Strangely, Excel, among business’s core data tools, remains in the estimation of many frustratingly behind the curve in its visualization capabilities and default settings. Most visualization software mitigates this disconnect by allowing easy imports of data from the Excel spreadsheets that businesses will no doubt continue to use.

10.  See davidmccandless.com and Carey Dunne, “How Designers Turn Data into Beautiful Infographics,” Fast Company Design, January 6, 2015, http://www.fastcodesign.com/3040415/how-designers-turn-data-into-beautiful-infographics.

11.  See Manuel Lima’s website, visualcomplexity.com.

12.  An excellent example is “A Visual Guide to Machine Learning,” R2D3, http://www.r2d3.us/visual-intro-to-machine-learning-part-1/.

13.  See Alex Lundry, “Chart Wars: The Political Power of Data Visualization,” YouTube video, April 28, 2015, https://www.youtube.com/watch?v=tZl-1OHw9MM.

14.  M. A. Borkin, et al., “What Makes a Visualization Memorable?,” IEEE Transactions on Visualization and Computer Graphics (Proceedings of InfoVis 2013). This research is still highly controversial. Memorability is a useful quality in a chart, but the research doesn’t test the effectiveness of communicating the idea in the data, or whether the chartjunk skews attitudes toward it. Still, that the authors merely call into question the long-held belief that chartjunk is verboten indicates the provocative tenor of the new generation of research, which doesn’t assume anything about tenets that feel true.

15.  The research also suggests that pies work well when proportions are recognizable, such as 25% or 75%. J. G. Hollands and Ian Spence, “Judging Proportion with Graphs: The Summation Model,” Applied Cognitive Psychology 12 (1998); and Ian Spence, “No Humble Pie: The Origins and Usage of a Statistical Chart,” Journal of Educational and Behavioral Statistics 30 (2005).

16.  Alvitta Ottley, Huahai Yang, and Remco Chang, “Personality as a Predictor of User Strategy: How Locus of Control Affects Search Strategies on Tree Visualizations,” Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems, 2015; Caroline Ziemkiewicz, Alvitta Ottley, R. Jordan Crouser, Ashley Rye Yauilla, Sara L. Su, William Ribarsky, and Remco Chang, “How Visualization Layout Relates to Locus of Control and Other Personality Factors,” IEEE Transactions on Visualization & Computer Graphics 19 (2013); Evan M. Peck, Beste F. Yuksel, Lane Harrison, Alvitta Ottley, and Remco Chang, “Towards a 3-Dimensional Model of Individual Cognitive Differences,” Proceedings of the 2012 BELIV Workshop: Beyond Time and Errors—Novel Evaluation Methods for Visualization (2012).

17.  Anshul Vikram Pandey et al., “The Persuasive Power of Data Visualization,” New York University Public Law and Legal Theory Working Papers, paper 474 (2014), http://lsr.nellco.org/cgi/viewcontent.cgi?article=1476&context=nyu_plltwp.

18.  Brendan Nyhan and Jason Reifler, “The Roles of Information Deficits and Identity Threat in the Prevalence of Misperceptions,” June 22, 2015, http://www.dartmouth.edu/~nyhan/opening-political-mind.pdf.

19.  Michael Greicher et al., “Perception of Average Value in Multiclass Scatterplots,” http://viscog.psych.northwestern.edu/publications/GleicherCorellNothelferFranconeri_inpress.pdf; Michael Correll et al., “Comparing Averages in Time Series Data,” http://viscog.psych.northwestern.edu/publications/CorrellAlbersFranconeriGleicher2012.pdf.

20.  Jeremy Boy et al., “A Principled Way of Assessing Visualization Literacy,” IEEE Transactions on Visualization and Computer Graphics 20 (2014).

21.  Alberto Cairo asks these and other good questions in the foreword to Data Visualization in Society (Amsterdam University Press, 2020).

1.  Gestalt psychology principles are often used to describe how we see charts. For example, the law of similarity suggests that like objects, such as data categories, should share values, such as color. Throughout this chapter and in others, I offer principles that borrow from Gestalt psychology but also go beyond it to other science.

2.  See “Writing Direction Index,” Omniglot.com, http://www.omniglot.com/writing/direction.htm#ltr.

3.  Dereck Toker, Cristina Conati, Ben Steichen, and Giuseppe Carenini, “Individual User Characteristics and Information Visualization: Connecting the Dots through Eye Tracking,” Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (2013); Dereck Toker and Cristina Conati, “Eye Tracking to Understand User Differences in Visualization Processing with Highlighting Interventions,” Proceedings of UMAP 2014, the 22nd International Conference on User Modeling, Adaptation, and Personalization (2014).

4.  No magic number exists as the threshold for the number of variables we can handle before they become “too much.” I chose eight colors as a maximum on the basis of a conversation with the visualization researcher and author Tamara Munzer, who said, “There are fewer distinguishable categorical colors than you’d like. You don’t get more than eight.”

5.  Display media limits this visualization as well. We can’t zoom in to discrete points here, but all the data points are plotted, and the creator of this chart, Alex “Sandy” Pentland of MIT, had a version from which he could zoom into subsets to see all the points.

6.  Researcher Steven Franconeri used this term to distinguish how we process information at two levels. The “blurry level” is fast, almost subconscious and helps us quickly pick out patterns. More deliberate parsing, which evaluates single values and compares values, is a slower process. Franconeri’s point was that the blurry level, which is often disregarded when talking about making good charts, shouldn’t be. He said: “Heat maps are disparaged because it’s hard to pick out a single value from them. But take a year’s worth of sales data, typically shown as a line graph, then imagine it as a heat map. It’s hard in the heat map to read off absolute values, but ask someone what is the month with highest average sales and it turns out that the heat map is way better because you’re not obsessed with the peaks and shape recognition as you would be with a line chart.” George Alvarez of Harvard University described perception similarly as happening on a “low road” and a “high road.”

7.  Viola S. Störmer and George A. Alvarez, “Feature-Based Attention Elicits Surround Suppression in Feature Space,” Current Biology 24 (2014); and Steven B. Most, Brian Scholl, Erin R. Clifford, and Daniel J. Simons, “What You See Is What You Set: Sustained Inattentional Blindness and the Capture of Awareness,” Psychological Review 112 (2005).

8.  Jon Lieff, “How Does Expectation Affect Perception,” Searching for the Mind blog, April 12, 2015, http://jonlieffmd.com/blog/how-does-expectation-affect-perception.

9.  Scott Berinato, “In Marketing, South Beats North,” Harvard Business Review, June 22, 2010, https://hbr.org/2010/06/in-marketing-south-beats-north/.

10.  I’ve changed the title, subject, and data points to protect the innocent, but the structure and conventions they used remain the same.

11.  Encyclopedia Britannica Online, s.v. “Weber’s law,” http://www.britannica.com/science/Webers-law.

12.  Ronald A. Rensink and Gideon Baldridge, “The Perception of Correlation in Scatterplots,” Computer Graphics Forum 29 (2010).

13.  In statistics, correlation is referred to with “r” where r = –1 is negative correlation, r = 0 is no correlation, and r = 1 is correlation.

14.  Lane Harrison et al., “Ranking Visualizations of Correlation Using Weber’s Law,” IEEE Transactions on Visualization and Computer Graphics 20 (2014); Matthew Kay and Jeffrey Heer, “Beyond Weber’s Law: A Second Look at Ranking Visualizations of Correlation,” IEEE Transactions on Visualization and Computer Graphics 22 (2016).

15.  Helen Kennedy and Rosemary Lucy Hill, “The Feeling of Numbers: Emotions in Everyday Engagements with Data and Their Visualisation,” Sociology 52, no. 4 (2018): 830–848.

16.  Data Stories (podcast), “Data Visualization Literacy with Jeremey Boy, Helen Kennedy, and Andy Kirk,” episode 69, March 9, 2016.

17.  Kennedy and Hill, “The Feeling of Numbers.”

18.  Ludovic Trinquart, David Merritt Johns, and Sandro Galea, “Why Do We Think We Know What We Know? A Metaknowledge Analysis of the Salt Controversy,” International Journal of Epidemiology 45, no. 1 (February 2016): 251–260, https://doi.org/10.1093/ije/dyv184.

19. I wish I could give more proper credit to the creator of this rather elegant chart. In trying to track down its provenance, no one seemed to want to take credit for it. The author of the story, Sandro Galea, said it was the work of Fortune, but the head of information design there said it came from the research paper, though a thorough search of those papers did not turn up any such chart. Whoever created it, nice work! Even if it doesn’t represent virtuous chaos, it’s a smart solution to visualizing a complex data set.

20.  Daniel M. Oppenheimer and Michael C. Frank, “A Rose in Any Other Font Wouldn’t Smell as Sweet: Effects of Perceptual Fluency on Categorization,” Cognition 106 (2008).

1.  For thoughtful and entertaining examinations of “crap circles,” see Gardiner Morse, “Crap Circles,” Harvard Business Review, November 2005, https://hbr.org/2005/11/crap-circles; and Gardiner Morse, “It’s Time to Retire ‘Crap Circles,’ ” Harvard Business Review, March 19, 2013, https://hbr.org/2013/03/its-time-to-retire-crap-circle.

2.  An idea pioneered by Eric von Hippel, as cited in Marion Poetz and Reinhard Prügl, “Find the Right Expert for Any Problem,” Harvard Business Review, June 2015, https://hbr.org/2014/12/find-the-right-expert-for-any-problem.

3.  The process described here is inspired by the process used by a data analysis company called Quid. The network diagram is inspired by one of Quid’s examples. See Sean Gourley, “Vision Statement: Locating Your Next Strategic Opportunity,” Harvard Business Review, March 2011, https://hbr.org/2011/03/vision-statement-locating-your-next-strategic-opportunity.

1.  Abela’s best-known book is Advanced Presentations by Design: Creating Communication That Drives Action, 2nd ed. (Wiley, 2013).

2.  The sketches in this book look neat and reasonably orderly. A highly skilled designer created them to be readable. You should not expect or aim to sketch as neatly as what appears here. It’s only necessary that you can interpret your sketches. Value speed over aesthetics.

3.  Andrew Wade and Roger Nicholson, “Improving Airplane Safety: Tableau and Bird Strikes,” http://de2010.cpsc.ucalgary.ca/uploads/Entries/Wade_2010_InfoVisDE_final.pdf.

4.  See Richard Arias-Hernandez, Linda T. Kaastra, Tera M. Green, and Brian Fisher, “Pair Analytics: Capturing Reasoning Processes in Collaborative Analytics,” Proceedings of Hawai’i International Conference on System Sciences 44, International Conference on System Sciences 44, January 2011, Kauai, Hawai’i.

5.  Roger Nicholson and Andrew Wade, “A Cognitive and Visual Analytic Assessment of Pilot Response to a Bird Strike,” International Bird Strike Committee Annual Meeting, 2009, http://www.int-birdstrike.org/Cairns%202010%20Presentations/IBSC%202010%20Presentation%20-%20R%20Nicholson.pdf.

6.  Bart deLanghe, Stefano Puntoni, and Richard Larrick, “Linear Thinking in a Nonlinear World,” Harvard Business Review, May–June 2017, https://hbr.org/2017/05/linear-thinking-in-a-nonlinear-world.

7.  David McCandless, “If Twitter Was 100 People …” information is beautiful, July 10, 2009, http://www.informationisbeautiful.net/2009/if-twitter-was-100-people/.

1.  Williams, Style, 17.

2.  Sometimes a title more like the former is not only okay but desirable. If you’re striving for total objectivity, a literal transfer of facts and a straight description of the chart’s structure may work fine as a headline. By using more-descriptive supporting elements, you may be shaping the audience’s thinking.

3.  Like Twain, Einstein is too often cited as the source of quotations. As Quote Investigator shows, we can’t be sure that he said this first, but he seems to have said something like it. http://quoteinvestigator.com/2011/05/13/einstein-simple/.

4.  Edward Tufte, The Visual Display of Quantitative Information, 2nd ed. (Graphic Press, 2001).

5.  Remember, though, that the medium of presentation matters. Some grays that appear “quiet” but readable on a page disappear when projected on a large screen or in a light room. Light colors, too, may fade or disappear, or their fidelity may be low; oranges may become indistinguishable from reds. Know your equipment and choose colors that work with it.

6.  The web is full of sites that help create color schemes. My favorite is paletton.com, which lets you switch easily between complementary and contrasting color schemes.

7.  Most recently, Steve J. Martin, Noah J. Goldstein, and Robert B. Cialdini, The Small Big: Small Changes That Spark Big Influence (Grand Central Publishing, 2014), about how small persuasions can lead to massive change. Cialdini is the author of several seminal works on persuasion science.

8.  Steve J. Martin, from the April 2015 issue of High Life, the British Airways in-flight magazine.

9.  Noah J. Goldstein, Steve J. Martin, and Robert B. Cialdini, Yes!: 50 Scientifically Proven Ways to Be Persuasive (Free Press, 2008).

10.  Koert van Ittersum and Brian Wansink, “Plate Size and Color Suggestibility: The Delboeuf Illusion’s Bias on Serving and Eating Behavior,” Journal of Consumer Research 39 (2012).

11.  “U.S. Budget Boosts Funding for Weapons, Research, in New Areas,” Reuters, February 2, 2015, http://www.reuters.com/article/2015/02/02/us-usa-budget-arms-idUSKBN0L625Q20150202.

12.  Martha McSally, “Saving a Plane That Saves Lives,” New York Times, April 20, 2015, http://www.nytimes.com/2015/04/20/opinion/saving-a-plane-that-saves-lives.html.

13.  I recognize that in the modern, blogging world, this line has smudged to near imperceptibility, a trend some rue. The point stands that reporters report, don’t insert opinion without evidence, and present both sides of an argument, whereas editorials are well-structured arguments that proffer a point of view.

14.  I’ve updated this data since I first wrote Good Charts. Just a few years ago, the average price of a beer was $5.98, the price of an average “Ballpark Case” was $115, and the most expensive was the Red Sox’s, at $186 per case.

15.  Daniel Kahneman and Richard Thaler, “Anomalies: Utility Maximization and Experienced Utility,” Journal of Economic Perspectives 20 (2006); Amos Tversky and Daniel Kahneman, “Availability: A Heuristic for Judging Frequency and Probability,” Cognitive Psychology 5 (1973).

16.  Petia K. Petrova and Robert B. Cialdini, “Evoking the Imagination as a Strategy of Influence,” Handbook of Consumer Psychology (Routledge, 2008), 505–524.

17.  We tend to react more viscerally to the unit chart than to a statistically driven chart. This is related to a phenomenon known as imaging the numerator. In a notable study that demonstrates this effect, experienced psychiatrists were given the responsibility of deciding whether or not to discharge a psychiatric patient. All the doctors were given an expert analysis, but some were told by the expert that 20% of patients like this one were likely to commit an act of violence upon release. Other doctors were told that 20 out of every 100 patients like this one were likely to commit an act of violence.

In the group that was told “20%,” about 80% of the doctors decided to release the patient. In the group that was told “20 out of every 100,” only about 60% suggested releasing him. The likelihood of recidivism was the same for both groups, so why the great disparity? The latter group was imaging the numerator. In the minds of those doctors, 20 out of 100 turned into 20 people committing acts of violence. The former group didn’t react the same way because percentages don’t commit acts of violence.

This phenomenon occurs because the experiential part of the brain—the part that relies on metaphor and narrative to create feelings—quickly and powerfully overrides the rational part that analyzes statistics. Unit charts take advantage of this. See Veronica Denes-Raj and Seymour Epstein, “Conflict between Intuitive and Rational Processing: When People Behave against Their Better Judgment,” Journal of Personality and Social Psychology 66 (1994); and Paul Slovic, John Monahan, and Donald G. MacGregor, “Violence Risk Assessment and Risk Communication: The Effects of Using Actual Cases, Providing Instruction, and Employing Probability versus Frequency Formats,” Law and Human Behavior 24 (2000): 271–296.

18.  I should note that imaging the numerator in evaluating risk is considered a negative phenomenon. For example, in the original study Denes-Raj and Epstein showed that when people were offered a chance to win money by picking red beans from a jar, they chose to pick from a jar that had more red beans even if red beans were proportionally fewer in that jar. Thus they were picking from a jar in which their odds of getting a red bean were lower. Imaging the numerator can also make us inflate risks. Paul Slovic noted in one study that when trying to communicate how infinitesimal parts per billion were, researchers told people to imagine one crouton in a 1,000-ton salad. Unfortunately, although the numerator (the crouton) was an easily understood concept, the massive salad was not. People ended up thinking that risks stated in parts per billion were more significant than they actually are. So although unit charts can persuasively convey individuality and help connect us to values by making statistics less abstract, they can also backfire or artificially exaggerate the data.

19.  I kept the design and the data but changed the subject.

20.  Suzanne B. Shu and Kurt A. Carlson, “When Three Charms but Four Alarms: Identifying the Optimal Number of Claims in Persuasion Settings,” Journal of Marketing 78 (2014).

1.  The term “facticity” carries several meanings, including some related to philosophy. This use of it isn’t necessarily the most common one, though it is increasingly common as a way to describe something that feels like an objective reflection of data, facts, and reality.

2.  This is not real data.

3.  “manipulate,” Merriam-Webster, https://www.merriam-webster.com/dictionary/manipulate.

4.  A term coined by Matthew Zeitlin as part of a discussion with my former colleague Justin Fox, who had the temerity to tweet positively about a chart with a truncated y-axis. Read the entertaining and thoughtful account here: Justin Fox, “The Rise of the Y-Axis-Zero Fundamentalists,” byjustinfox.com, December 14, 2014, http://byjustinfox.com/2014/12/14/the-rise-of-the-y-axis-zero-fundamentalists/.

5.  Danielle Ivory and Hiroko Tabuchi, “About Data Tampering,” New York Times, January 4, 2016, https://www.nytimes.com/2016/01/05/business/takata-emails-show-brash-exchanges-about-data-tampering.html.

6.  This was the case Tufte cited when arguing for truncation. You might suspect he’d be a y-axis-zero fundamentalist, but in fact he was open to the idea of truncation and cited its common use in scientific and academic circles as support for his view: “The scientists want to show their data, not zero.” See the bulletin board conversation “Baseline for Amount Scale” at http://www.edwardtufte.com/bboard/q-and-a-fetch-msg?msg_id=00003q.

7.  Hannah Groch-Begley and David Shere, “A History of Dishonest Fox Charts,” Media Matters, October 1, 2012, http://mediamatters.org/research/2012/10/01/a-history-of-dishonest-fox-charts/190225.

8.  This comes from tylervigen.com, whose owner, Tyler Vigen, is a JD student at Harvard Law School. He wrote a script that finds statistical correlations in unrelated data sets and then charted them. Vigen’s examples are usually silly; he has collected them in an entertaining book, Spurious Correlations (Hachette Books, 2015).

9.  Ioannidis was writing about data, not visualizations—specifically, how research into the effects of nutrients on the human body is notoriously dodgy: “Almost every single nutrient imaginable has peer reviewed publications associating it with almost any outcome.” We can apply what he says about big data sets to the visualization of such sets. John P. A. Ioannidis, “Implausible Results in Human Nutrition Research,” BMJ, November 14, 2013, http://www.bmj.com/content/347/bmj.f6698.

10.  For an excellent discussion of this trend, see Nathan Yau, “The Great Grid Map Debate of 2015,” FlowingData, May 12, 2015, https://flowingdata.com/2015/05/12/the-great-grid-map-debate-of-2015/; and Danny DeBelius, “Let’s Tesselate: Hexagons for Tile Grid Maps,” NPR Visuals Team, May 11, 2015, http://blog.apps.npr.org/2015/05/11/hex-tile-maps.html.

11.  An excellent discussion of these hurricane charts and other visualizations of uncertainty can be found in Jessica Hullman’s excellent article, “How to Get Better at Embracing Unknowns,” Scientific American, September 1, 2019, https://www.scientificamerican.com/article/how-to-get-better-at-embracing-unknowns/.

12.  Scott Dance and Amudalat Ajasa, “Cone of Confusion: Why Some Say Iconic Hurricane Map Misled Floridians,” Washington Post, October 4, 2022, https://www.washingtonpost.com/climate-environment/2022/10/04/hurricane-cone-map-confusion/.

13.  Scott Berinato, “In Marketing, South Beats North,” Harvard Business Review, June 22, 2010, https://hbr.org/2010/06/in-marketing-south-beats-north.

1.  I recommend Nancy Duarte, HBR Guide to Persuasive Presentations (Harvard Business Review Press, 2012); Duarte’s work at Duarte.com; and Andrew Abela, Advanced Presentations by Design: Creating Communication That Drives Action (Wiley, 2013).

2.  Mary Budd Rowe is generally considered the inventor of this educational technique, and multiple studies have confirmed its positive effects. See Mary Budd Rowe, “Wait Time: Slowing Down May Be a Way of Speeding Up!” Journal of Teacher Education 37 (January–February 1986), http://www.sagepub.com/eis2study/articles/Budd%20Rowe.pdf.

3.  You might suggest that this presenter change the title of the chart to something that reflects the idea, such as “Money Doesn’t Buy Comfort in Air Travel (Unless You Spend a Lot).”

4.  Some may take exception to connecting discrete categorical data like this. For example, if I rolled this radial chart out flat, it would essentially be a line chart whose area was filled in with color. And connecting would make categorical data look like a continuous trend line, which is one of the few absolute no-nos in charting, because there is no inherent connection between categories of sales skills rankings, but a trend would suggest that they are connected. That’s a fair argument, and I’d understand if you chose to forgo using radar charts because of it. But I still believe they’re useful, because connecting the points radially doesn’t spark the trend line convention in our minds. Instead, it makes us see a shape to which we can assign meaning.

5.  Two of my favorites: Gregor Aisch et al., “Where We Came From and Where We Went, State by State,” New York Times Upshot, August 14, 2014, http://www.nytimes.com/interactive/2014/08/13/upshot/where-people-in-each-state-were-born.html; and Timothy B. Lee, “40 Maps That Explain the Roman Empire,” Vox, August 19, 2014, http://www.vox.com/2014/8/19/5942585/40-maps-that-explain-the-roman-empire.

6.  Ho Ming Chow, Raymond A. Mar, Yisheng Xu, Siyuan Liu, Suraji Wagage, and Allen R. Braun, “Personal Experience with Narrated Events Modulates Functional Connectivity within Visual and Motor Systems during Story Comprehension,” Human Brain Mapping 36 (2015).

7.  Robyn M. Dawes, “A Message from Psychologists to Economists,” Journal of Economic Behavior & Organization 39 (May 1999), http://www.sciencedirect.com/science/article/pii/S0167268199000244.

8.  Ingraham’s story was an online article, not a live presentation. Smartly, he broke up the page so that the visualizations were separated by enough text that the audience could see only one at a time, as if they were presentation slides. This maximizes the effect of the final reveal. Each block of text that follows its visualization could actually serve as a smart script for a live presentation, because it adds context and understanding about the amount of water we’re looking at and doesn’t simply repeat what we see. Christopher Ingraham, “Visualized: How the Insane Amount of Rain in Texas Could Turn Rhode Island into a Lake,” Washington Post Wonkblog, May 27, 2015, http://www.washingtonpost.com/blogs/wonkblog/wp/2015/05/27/the-insane-amount-of-rain-thats-fallen-in-texas-visualized/.

9.  See “Bait and Switch,” changingminds.org, http://changingminds.org/techniques/general/sequential/bait_switch.html; and Robert V. Joule, Fabienne Gouilloux, and Florent Weber, “The Lure: A New Compliance Procedure,” Journal of Social Psychology 129 (1989). This work refers more to people’s commitment to a menial task when they thought they’d be doing a fun one, but the mechanism is similar: if you get someone to commit to one way of seeing things, the inconsistency upon reveal of a new way of seeing things creates tension that the person feels compelled to resolve. The greater the inconsistency, the more they will feel compelled to understand and resolve the dissonance.

10.  See “Consistency,” changingminds.org, http://changingminds.org/principles/consistency.htm.

11.  Dietrich Braess, Anna Nagurney, and Tina Wakolbinger, “On a Paradox of Traffic Planning,” Transportation Science 39 (November 2005), http://homepage.rub.de/Dietrich.Braess/Paradox-BNW.pdf.

12.  Moran Cerf and Samuel Barnett, “Engaged Minds Think Alike: Measures of Neural Similarity Predict Content Engagement,” Journal of Consumer Research, in review.

13.  writzter, comment on “The Fallen of World War II,” http://www.fallen.io/ww2/#comment-2044710701.

14.  This is a masterful use of animation and data. Harry Stevens, “Why Outbreaks like Coronavirus Spread Exponentially, and How to ‘Flatten the Curve,’ ” Washington Post, March 14, 2020, https://www.washingtonpost.com/graphics/2020/world/corona-simulator/.

15.  For a fuller exploration of storytelling with data, you can purchase my “Storytelling with Data Toolkit” with the Good Charts Workbook. Both include deep dives on this topic. https://store.hbr.org/product/good-charts-workbook-storytelling-with-data-toolkit/10310.

1.  Hugo Bowne-Anderson, “What Data Scientists Really Do, According to 35 Data Scientists,” Harvard Business Review, August 15, 2018, https://hbr.org/2018/08/what-data-scientists-really-do-according-to-35-data-scientists.

2.  Thomas H. Davenport and DJ Patil, “Data Scientist: The Sexiest Job of the 21st Century,” Harvard Business Review, October 2012, https://hbr.org/2012/10/data-scientist-the-sexiest-job-of-the-21st-century.

3.  Eelke Heemskerk, “How Corporate Boards Connect, in Charts,” Harvard Business Review, April 21, 2016, https://hbr.org/2016/04/how-corporate-boards-connect-in-charts.

4.  Ben Jones and Michael Correll, “BI Trend #2: Liberal Arts Impact,” n.d., https://www.tableau.com/learn/webinars/bi-trend-2-liberal-arts-impact.

5.  Scott Berinato, “Inside Facebook’s AI Workshop,” Harvard Business Review, July 19, 2017, https://hbr.org/2017/07/inside-facebooks-ai-workshop.

1.  This sentence is paraphrased from Kirk Goldsberry.

2.  Some visualization pros marvel at Microsoft’s missed opportunity with charts and graphs in Excel, where a lot of corporate data sits. Excel wasn’t originally terrible at generating charts, says Leland Wilkinson, a dataviz veteran and the author of The Grammar of Graphics, 2nd ed. (Springer, 2005), who recently joined Tableau. “Its first charts were rather nice,” he said to me. “Then they got nervous because people were out there doing chartjunk”—3-D charts and gradient fills; cones instead of flat bars; exploded pies. There’s a certain look to Excel charts from the 1990s and the early 2000s that is closely identified with the prototypical business presentation: gray background, heavy horizontal grid lines, blue line with large square dots as data points. “Bad software leads people to do bad graphics,” Wilkinson says. “I’m delighted by PowerPoint. If you use it right, it’s wonderful. I think almost the opposite of charting in Excel.” At any rate, other software and online services have filled the void left by Excel, and the ease of importing and exporting spreadsheet data has obviated the need for good charting in the spreadsheet program itself.

All sketches by James de Vries

Page number 3 (top left) Dr. Paul S. Bradley, FMPA.co.uk, BarcaInnovationHub.com

3 (top right) Robin Stewart, Weatherstrip.app

3 (bottom right) Harvard Business Review

14 Catalin Ciobanu, CWT

21 (all) Wikimedia Commons

22 (both) Internet Archive

25 Willard Britton, Graphic Methods for Presenting Facts, 1912

43 Alex “Sandy” Pentland, MIT

44 (bottom left) James de Vries

48 From Ludovic Trinquart, David Merritt Johns, and Sandro Galea, “Why Do We Think We Know What We Know? A Metaknowledge Analysis of the Salt Controversy,” International Journal of Epidemiology 45, no. 1, February 2016. Reprinted with permission.

52 (both) Lane Harrison

53 Lane Harrison, Matthew Kay, and Jeffrey Heer

63 (top left) Harvard Business Review

63 (top right) Harvard Business Review

67 (left) HBR.org

70 (top right) Carlson Wagonlit Travel (CWT) Solutions Group, Travel Stress Index research (2013)

74 (left) Sean Gourley, Quid Inc.

82 Weather Underground

105 Harvard Business Review

106 (both charts) Produced using the IN-SPIRE™ software developed at the Pacific Northwest National Laboratory, operated by Battelle for the U.S. Department of Energy, and Tableau Software

107 (all charts) Produced using the IN-SPIRE™ software developed at the Pacific Northwest National Laboratory, operated by Battelle for the U.S. Department of Energy, and Tableau Software

116 © The Economist Newspaper Limited, London, May 24, 2015

133 (bottom left) From The New England Journal of Medicine, Willem G. van Panhuis, M.D., Ph.D., John Grefenstette, Ph.D., Su Yon Jung, Ph.D., Nian Shong Chok, M.Sc., Anne Cross, M.L.I.S., Heather Eng, B.A., Bruce Y. Lee, M.D., Vladimir Zadorozhny, Ph.D., Shawn Brown, Ph.D., Derek Cummings, Ph.D., M.P.H., and Donald S. Burke, M.D., Contagious Diseases in the United States from 1888 to the Present, 369, 2152–2158, Copyright © (2013) Massachusetts Medical Society. Reprinted with permission from Massachusetts Medical Society.

133 (bottom right) Republished with permission of Dow Jones Inc., from WSJ.com, “Battling Infectious Diseases in the 20th Century: The Impact of Vaccines” by Tynan DeBold and Dov Friedman; permission conveyed through Copyright Clearance Center, Inc.

135 Max Woolf

136 Getty Images/Mark Wilson

137 (bottom right) Matt Parilla, Ramblemaps.com

141 Harvard Business Review

142 Harvard Business Review

177 “Total Recall: Internal Documents Detail Takata’s Broken Safety Culture and the Need for a More Effective Recall Process ADDENDUM to Danger Behind the Wheel: The Takata Airbag Crisis and How to Fix Our Broken Auto Recall Process June 22, 2015” from the Office of Oversight and Investigations Minority Staff Report, February 23, 2016, United States Senate Committee on Commerce, Science, and Transportation

184 (top right) Tyler Vigen, tylervigen.com.

171 (top) J. Emory Parker

171 (bottom) Mike Bostock

191 (top) HBR.org

206 (left) Bonnie Scranton

206 (right) Carlson Wagonlit Travel (CWT) Solutions Group, Travel Stress Index research (2013)

209 (both) Methodology courtesy of Lynette Ryals, Iain Davies

210 (all) Methodology courtesy of Lynette Ryals, Iain Davies

211 Methodology courtesy of Lynette Ryals, Iain Davies

220 (both) Christopher Ingraham, Washington Post

221 (both) Christopher Ingraham, Washington Post

226 (all) Neil Halloran, fallen.io