When I participated as a judge and speaker at last year’s Malofiej conference in Spain—the Oscars of journalistic infographics—I had a chance to become acquainted with Alberto Cairo, who has since become a trusted friend and colleague. I discovered while at the conference that it was a result of Alberto’s suggestion that I was invited to attend. Alberto is one of the few infographic designers that I know who has a mature understanding of the work. Beginning as a journalist in Spain, Alberto approached the work first as a communicator, and second as a graphic designer. He has worked in various parts of the world for news publications and at universities where he has honed his craft and thought deeply about the principles and practices that make it effective. Now, after most recently working in Brazil, he is teaching in the United States for a second time at the University of North Carolina at Chapel Hill in the Master of Arts in Technology and Communication program and also at the University of Miami where he works with communication and journalism students.

Mostly in response to his new book, The Functional Art, (so far only available in Spanish, but in the process of being translated into English) Alberto was recently interviewed for an article in the Velora Newsletter. If you’re interested in infographics, I encourage you to read it. Alberto’s thoughtful advice serves as a desperately needed voice of sanity in this time of infographicmania.

Take care,

I was listening to “Science Friday” on NPR last week and heard about the work of Ted Kaptchuk, Director of Harvard University’s Program in Placebo Studies and the Therapeutic Encounter. I was particularly interested in one of his studies that investigated placebo effects on asthma. This study tested physical effects of real medication vs. placebos as well as patients’ perceptions of the effects. Over the course of 12 sessions, subjects were given the following three different treatments and a non-treatment session three times each: 1) an albuterol inhaler, 2) a placebo inhaler, 3) a fake acupuncture treatment, and 4) several minutes in the waiting room with no subsequent treatment. In each case physical effects were subsequently tested by measuring subjects’ lung capacity and subjective effects were tested by asking subjects to rate their perception of improvement on a 1 to 10 point scale. Based on actual lung function, the albuterol inhaler—the only real medical treatment—produced a 20% improvement while the two placebo treatments and waiting without treatment each produced a 7% improvement. Apparently the mere act of sitting for a while without activity produced some improvement. What’s interesting is that, even though neither placebo produced an effect greater than no treatment at all, indicating the absence of an objective placebo effect, subjective perceptions were quite different. Subjects reported the following perceived levels of improvement: 50% for the albuterol inhaler, 45% for the placebo inhaler, 46% for the fake acupuncture treatment, and 21% for merely waiting without treatment. Both placebo treatments provided subjective perceptions of improvement that were almost as great as the medical treatment.

In an article about this study in the Wall Street Journal’s Health Blog titled “The Placebo Effect, This Time in Asthma” Katherine Hobson wrote:

Isn’t it enough to feel better? In the case of some conditions, yes, says senior author Ted Kaptchuk…

He tells the Health Blog that when it comes to things like asthma or cholesterol or diabetes, while patient reports are important, it’s key to keep tabs on objective measures, too. I may feel great, but if my cholesterol level isn’t budging, the statin isn’t working and my risk for another heart attack isn’t going down.

But in conditions such as depression, pain and insomnia, the subjective response is the main thing being treated. If I’m depressed, take a pill and no longer feel depressed, by definition the medicine is working. There’s no blood or imaging test used to confirm whether my condition is being fixed.

I share Kaptchuk’s opinion. In a case such as insomnia, if a placebo allows someone to sleep, it does the job, and that’s enough. If a patient’s health is at risk, however, making her think she’s getting better when she isn’t is potentially harmful.

As I was listening to this story on NPR, I began to think of similar issues involving data visualization. If people enjoy your infographic, isn’t that enough? Or in the realm of information dashboards, if the CEO has fun looking at the flashy gauges, isn’t that enough? No, it isn’t. Both are meant to inform. To understand the story of an infographic or an organization’s performance on a dashboard requires real information. Enjoying a pretty picture and feeling like you’ve been informed is not the same as the actual understanding that’s needed to make better decisions.

I like to feel good as much as the next guy. Data visualizations often give me great pleasure. I do not think, however, that enjoyment is the goal. It is not essential. In fact, enjoyment that distracts from the information rather than drawing people into it in meaningful and useful ways impedes the goal. When it comes to the real health of people’s minds and decisions, placebos are definitely not enough.

Take care,

On Monday of this week I travelled from Berkeley across the Bay Bridge into San Francisco to have dinner with a friend who was staying at a hotel next to the Museum of Modern Art, so I decided to go a little early and enjoy the current exhibits. I’m glad I did, because the work of industrial designer Dieter Rams is currently on exhibit, along with his extraordinary principles for good design.

For several decades Rams designed products for Braun and Vitsoe, and has been a leading inspiration behind Apple’s approach to product design. The simple beauty of products such as the iPhone reflect Rams’ design aesthetic. According to the website of Vitsoe, “Back in the early 1980s, Dieter Rams was becoming increasingly concerned by the state of the world around him — ‘an impenetrable confusion of forms, colours and noises.’ Aware that he was a significant contributor to that world, he asked himself an important question: is my design good design?” In response to this question, he developed the following 10 principles of good design:

Good design is innovative.

The possibilities for innovation are not, by any means, exhausted. Technological development is always offering new opportunities for innovative design. But innovative design always develops in tandem with innovative technology, and can never be an end in itself.

Good design makes a product useful.

A product is bought to be used. It has to satisfy certain criteria, not only functional, but also psychological and aesthetic. Good design emphasises the usefulness of a product whilst disregarding anything that could possibly detract from it.

Good design is aesthetic.

The aesthetic quality of a product is integral to its usefulness because products we use every day affect our person and our well-being. But only well-executed objects can be beautiful.

Good design makes a product understandable.

It clarifies the product’s structure. Better still, it can make the product talk. At best, it is self-explanatory.

Good design is unobtrusive.

Products fulfilling a purpose are like tools. They are neither decorative objects nor works of art. Their design should therefore be both neutral and restrained, to leave room for the user’s self-expression.

Good design is honest.

It does not make a product more innovative, powerful or valuable than it really is. It does not attempt to manipulate the consumer with promises that cannot be kept.

Good design is long-lasting.

It avoids being fashionable and therefore never appears antiquated. Unlike fashionable design, it lasts many years — even in today’s throwaway society.

Good design is thorough, down to the last detail.

Nothing must be arbitrary or left to chance. Care and accuracy in the design process show respect towards the consumer.

Good design is environmentally-friendly.

Design makes an important contribution to the preservation of the environment. It conserves resources and minimises physical and visual pollution throughout the lifecycle of the product.

Good design is as little design as possible.

Less, but better — because it concentrates on the essential aspects, and the products are not burdened with non-essentials. Back to purity, back to simplicity.

I hope you find these principles as sensible, insightful, and inspiring as I do.

Today, Rams looks at the world and sighs. Quoted in The Telegraph on June 4, 2011, he said:

I am troubled by the devaluing of the word “design”. I find myself now being somewhat embarrassed to be called a designer. In fact I prefer the German term, Gestalt-Ingenieur. Apple and Vitsoe are relatively lone voices treating the discipline of design seriously in all corners of their businesses. They understand that design is not simply an adjective to place in front of a product’s name to somehow artificially enhance its value. Ever fewer people appear to understand that design is a serious profession; and for our future welfare we need more companies to take that profession seriously.

What concerns Rams about the design of physical products today is perhaps even more evident in the design of software. Most software vendors bother little with design and fill their products with the kinds of contrivances that Rams has fought for years to discourage. “My goal is to omit everything superfluous so that the essential is shown to best possible advantage” (Rams, 1980). Business intelligence and so-called analytics vendors are notorious for their insatiable appetites for wasteful, ill conceived, and dysfunctionally designed features. With few exceptions, what they call innovation is anything but. “Things which are different in order simply to be different are seldom better, but that which is made to be better is almost always different” (Rams, 1993).

The best designers, whether of the industrial variety, such as Rams, or any other type, including those who apply their skills to data visualization, strive for a marriage of form and function, beauty and usability, which refuses to see these forces in necessary conflict. Thanks to designers like Rams who care, we might someday live in a world where bad design is the exception rather than the norm.

Take care,

Until August 30, 2009, I knew little about Manual Lima and his work beyond the fact that he ran the data visualization website www.VisualComplexity.com. When he published his “Information Visualization Manifesto” on that day, however, I recognized him as a kindred spirit: someone who believed that data visualizations should be designed to enlighten. When I recently heard that he had written a book, Visual Complexity: Mapping Patterns of Information, I was eager to read it. I finally had my chance, and here are my thoughts.

It’s important to recognize up front that this book is not about data visualization in general but about network visualization in particular. This is also the focus of www.VisualComplexity.com, where Lima showcases hundreds of network visualizations. If you share his intense fascination with networks (their nature, ubiquity, and complex beauty) and the many ways that networks can be represented graphically (various display approaches, the history of their development, and their potential as art) you will probably enjoy the intellectual meanderings in this book, which ventures at times into philosophical speculation. However, if you want to understand how network visualizations work, what makes them effective, when to use one approach rather than another, or how well the many examples in this book perform as vehicles of insight, you will be disappointed.

I believe that the merits of a book should be judged by how well it achieves what the author promises. Authors of a non-fiction work such as this should always declare their objectives­ and do their best to fulfill them. In the introduction to Visual Complexity, two of the ways that Lima characterizes the book are not satisfactorily delivered: 1) he says that the book “looks at the depiction of networks from a practical and functional perspective,” and 2) he describes it as a “comprehensive study of network visualization [that] should ultimately be accessible to anyone interested in the field, independent of their level of expertise or academic dexterity.” Given the focus of my work, I was particularly interested in the book’s ability to live up to these two goals.

In a short section of the third chapter, Lima presents a few principles for the design of network visualizations, but he never applies those principles to the visualizations that appear throughout the book. How can we learn from those examples, many of which are incomprehensible given the brief descriptions that accompany them, without an explanation of the insights that they pursue and a critique of their effectiveness in capturing and revealing those insights? Network visualizations are notoriously difficult to fathom, often looking like giant hairballs of complexity. Even when they’re well designed, they usually require instruction and practice to decipher. A comprehensive treatment of network visualization must do more than showcase examples; it must help us fathom the depths.

In a section of the book that I found helpful, Lima categorizes network visualizations by differences in form (arc diagrams, area groupings, centralized burst, etc.), but makes no attempt to describe their various strengths, weaknesses, or appropriate uses. When we should select one form instead of another is never hinted.

Lima exhibits many network visualizations, breaks them into categories, and provides a wee bit of guidance, but spends most of the book’s 257 pages delving into history, philosophy, science, and art with the erudition of a museum curator. The breadth of his knowledge is impressive, spanning several fields, which he weaves into an interdisciplinary network of ideas. Academics in the field will find his tour thought provoking. While interesting, however, it feels like an intellectual exercise with no bridge to the real world. More and more today we need to understand networks, from the microscopic world of neurons in our brains to the macroscopic realm of social movements and the World Wide Web. I kept looking for content in this book that I could apply to these challenges in practical ways, but found little.

In the chapter titled “Complex Beauty,” Lima speculates about the causes of our attraction to “depictions of complex networks.” I found his speculation interesting, but couldn’t help wondering if its premise were indeed true. Are people naturally attracted to complex network visualizations? Who comprises the “we” that experiences this allure? I suspect that network visualizations are alluring to people like Lima and me who work in the field, but few others.

The final chapter of the book, “Looking Ahead,” seems out of place, a misfit as the book’s finale. It consists of four essays by others working in the field, but the topics of these essays don’t focus on network visualization and in two cases don’t deal with networks at all. Each essay is thoughtful but only peripherally relevant to the book.

Those with expertise in network visualizations will find this book engaging; a worthwhile addition to their library. Those looking for a comprehensive, accessible, and practical guide to network visualization must prolong the wait. Perhaps Lima will provide this book in the future. He is perhaps better qualified than anyone else. If so, I invite him to descend from the lofty heights of aesthetic musings to the realm where real networks wait to be revealed.

Take care,

I just finished reading Daniel Kahneman’s new book Thinking, Fast and Slow. If you don’t recognize his name, he along with Amos Tversky won the 2002 Nobel Prize in Economic Sciences for their game-changing work in psychology about decision making. Their pioneering work introduced our current understanding of the two systems that drive the way we think. According to the description on the inside flap of the book’s slip cover:

System 1 is fast, intuitive, and emotional; System 2 is slower, more deliberative, and more logical. Kahneman exposes the extraordinary capabilities—and also the faults and biases—of fast thinking, and reveals the pervasive influence of intuitive impressions on our thoughts and behavior…Kahneman reveals where we can and cannot trust out intuitions and how we can tap into the benefits of slow thinking.

This book distills a lifetime of work in a way that is readable, entertaining, highly informative, and incredibly important.

I won’t review the book’s contents here, but want only to mention one notion in particular that caught my attention in the last few pages. Kahneman describes organizations as decision factories. More fundamental and important than any other activity that goes on in organizations of all types is the making of decisions. A company that manufactures clothing, a government body that enforces policy, a hospital that cares for the sick, and a non-profit organization that feeds the homeless are all decision factories. How well they do what they do depends on their ability to make good decisions. How many organizations take this part of their work seriously and develop the skills to do it well compared to the thought and preparation that goes into manufacturing, enforcement, health care, or food distribution? How seriously does your organization take the quality of its decision making? Our universities ought to teach decision making, both in general and in ways that are specific to each discipline. Organizations should create cultures of decision making to promote ongoing development and a greater appreciation for the process, which can be controlled, rather than the results, which are often a matter of luck.

In the book’s conclusion, Kahneman issues a challenge:

Organizations are better than individuals when it comes to avoiding errors, because they naturally think more slowly and have the power to impose orderly procedures. Organizations can institute and enforce the application of useful checklists, as well as more elaborate exercises…At least in part by providing a distinctive vocabulary, organizations can also encourage a culture in which people watch out for one another as they approach minefields. Whatever else it produces, an organization is a factory that manufactures judgments and decisions. Every factory must have ways to ensure the quality of its products in the initial design, in fabrication, and in final inspections. The corresponding stages in the production of decisions are the framing of the problem that is to be solved, the collection of relevant information leading to a decision, and reflection and review. An organization that seeks to improve its decision product should routinely look for efficiency improvements at each of these stages. The operative concept is routine. Constant quality control is an alternative to the wholesale reviews of processes that organizations commonly undertake in the wake of disasters. There is much to be done to improve decision making. (p. 418)

I love this notion that the primary products of any organization are its decisions. Information visualization can play an important role in this process, but it is only one competency among many that are needed to improve our decisions. We who focus on information visualization will get better at what we do as we develop these other competencies as well. Reading this book will help.

Take care,