Orthodoxy and Eccentricity
Preface to ‘Data Sketches: A journey of imagination, exploration, and beautiful data visualizations’, a book by Nadieh Bremer and Shirley Wu
By Alberto Cairo, Knight Chair at the University of Miami and author of ‘How Charts Lie: Getting Smarter About Visual Information’
Orthodoxy and eccentricity are opposing but complementary forces in any field, and data visualization isn’t an exception. Periods when orthodoxy prevails over eccentricity discourage whim, passion, and experimentation, and favor stability and continuity. When the opposite happens, when eccentrics take over, chaos and turmoil ensue, but progress becomes more rapid, and invention—fruitful or useless—more likely. This is a book where eccentricity abounds.
The formalization and systematization of data visualization took decades, and happened thanks to the work of people such as Jaques Bertin, John Tukey, William Cleveland, Naomi Robbins, Stephen Kosslyn, Leland Wilkinson, Tamara Munzner, Stephen Few, and many others. It is because of them that we possess a common language to discuss what constitutes a well-designed chart or graph, and principles that aid us when creating them. They deserve our gratitude.
What most of those authors have in common is a background in statistics, analytics, or the sciences, and I suspect that this has had great influence over the styles that visualization designers have traditionally favored. Since the 1970s at least, data visualization has been governed by a vague consensus—an orthodoxy—that prioritizes bare clarity over playfulness, simplicity over allegedly-gratuitous adornments, supposed objectivity over individual expression.
As a consequence, generations of visualization designers grew up in an era of stern and often pious sobriety that sadly degenerated sometimes into the dismissive self-righteousness of popular slurs such as ‘chart junk’.
I think it’s time not to abandon that orthodoxy outright—when the goal of a visualization is to conduct exploratory analysis, reveal insights, and inform decisions, prioritizing clarity and sticking to standard graphic forms, conventions, and practices is still sound advice—but to acknowledge that other orthodoxies are possible and necessary. Visualization can be designed and experienced in various ways, by people of various backgrounds, and in various circumstances. That’s why reflecting on the purpose of a visualization is paramount before we design it—or before we critique it. This is a lesson I’ve learned myself the hard way.
Nadieh Bremer and Shirley Wu are wondrous eccentrics. Their splendid book is the product of a collaborative experimental project, DataSketch.es, that might be one of the first exponents of an emerging visualization orthodoxy in which uniqueness is paramount and templates and conventions are seen with skepticism.
I discovered DataSketch.es right after it was launched, back in 2016, and I was immediately enthralled by such initiative, even if I had to make a bit of an effort to understand many of its graphics. They are insanely complex and ornate, I thought, colorful, often mysteriously organic, a departure from the strictures of classic graphs, charts, and maps. I felt that Nadieh and Shirley were not only pushing what was possible, but also wished to defy what was acceptable.
The book that you have in your hands reveals how Nadieh and Shirley think. This is useful. Visualization is, like written language, based on a body of symbols and a syntax that help us arrange those symbols to convey information. However, this system of symbols and syntax isn’t rigid—again like written language—but flexible and in constant flux. That’s why I’ve come to believe that visualization can’t be taught as a set of rules, but as a principled process of reasoning about how to make good decisions when it comes to what to show and how to show it.
This process ought to be informed by what we know about vision and cognitive science, rhetoric, graphic and interaction design, UX, the visual arts, and many other fields. However, this knowledge shouldn’t be a straitjacket. Rather, it’s a foundation that opens up multiple possibilities, some more appropriate, some less, always depending on the purpose of each visualization, on the data that it encodes, and on its intended audience. Therefore, the education of visualization designers, whether it’s formal or not, can’t be based on memorizing rules, but on learning how to justify our own choices based on ethics, aesthetics, and the incomplete but ever-expanding body of empirical evidence coming from research and academia.
There are plenty of lengthy and detailed discussions in Data Sketches about how to balance out these considerations, and it’s always useful to peek into the minds of great designers, if only to borrow ideas from them. Some of you will be persuaded by those discussions, and others will disagree and argue against them. That’s fine. Conversation is what may help us determine whether certain novelties fail, and therefore should be discarded, or succeed, and therefore become convention.
Today’s eccentricity is tomorrow’s orthodoxy.
Now go ahead: read, think, and discuss. And consider becoming a bit more of an eccentric.
Data Sketches is available now from Routledge, Bookshop, and Amazon.
