Drawing code: Bret Victor's visualization dreams

Drawing Dynamic Visualizations from Bret Victor on Vimeo.

If you haven't watched the video above, do yourself a favor. As a journalist and designer who has a hard time when forced to code something, a tool like the one showcased in it would be a dream come true. I think in words and pictures, and I like to design with words and pictures as well, by manipulating* them, by dragging, dropping, moving, and scaling them, rather than by defining their features through obscure programming languages, which feel unnatural. At the same time, I acknowledge that learning to code is liberating (it is appropriate to mention Douglas Rushkoff's famous book here), so I would like to find a way to reconcile what I feel with what I need. Bret Victor defines himself as a "purveyor of impossible dreams" in his website, by the way. I really hope that this label will be proved inaccurate.

*The verb to manipulate comes in part from manus, which means hand in Latin. Read more.

A few notes about Nathan Yau's 'Data Points'

In his generous review of The Functional Art, Nathan Yau wrote that he sat behind me when I visited The New York Times in 2007 to help with an animation about Rafael Nadal. I'm extremely absent minded and have a feeble memory. I'm sure that I was introduced to him, but I am embarrassed to admit that I didn't remember it. I believe that he was an intern at the infographics department at the time. We have not seen each other again ever since, unfortunately. I was looking forward to his talk at Malofiej 2013, but he canceled at the very last minute, probably because he was busy both with his PhD dissertation and the final editing of Data points: Visualization that Means Something. I've been reading and enjoying it in the past few weeks during trips, so here you have some notes that I wrote (in a Moleskine notebook, mind you; I'm getting old):

Data Points is a more solid work than Visualize This! Nothing against Nathan's first book, but I found it disappointing because it read like a disjointed programming handbook, rather than like a true “guide to design, visualization, and statistics”, which is what its subtitle promises. I don't want to be unfair, though, so I'll admit that perhaps I'm not its target audience. Its many reviewers in Amazon praise it almost unanimously, after all.

The subtitle for Data Points matches its content better: Visualization that means something. The first part of the book is mainly a showcase of creative and inspiring visualization projects. To envision what it looks like, think of the FlowingData blog on steroids, but with deeper and more informative comments by the author. I'm not fond of all the examples, but I found this portion very valuable anyway. My main complaint is that the first chapter, titled 'Understanding Data', doesn't really deliver a systematic overview of statistical methods that visualization designers need to be aware of, but just some slightly random (although useful, don't get me wrong) notes on what to do or what to avoid. Given Nathan's background on statistics, perhaps I expected too much in this regard.

The second part of the book is a fine collection of visualization techniques, strategies, graphs, and data maps aimed at beginners. This half is the strongest of the two. It's refreshing to see that Nathan discusses graphic forms that are uncommon outside academic and scientific circles, such as the parallel coordinate plot and the scatter plot matrix. It is also encouraging that the book outlines some rules of thumb on how to make visual displays look better based on classic principles of Graphic Design. Finally, Nathan's insistence on correctly labeling and annotating graphics should be useful for visualization designers with a background on statistics and computer science who wish to communicate with the general public. This part is so good that it left me craving for more.

Therefore, there's plenty to praise in Data Points, but also a few important things to disagree with. For instance, some of Nathan's recent comments —reflected in the book— are bizarre, textbook examples of the straw man fallacy. Nobody that I know approaches visualization as an “unyielding” —an adjective repeated several times in Data Points— tool, not even the most ardent efficiency crusaders. And it is inexact to say that there are folks out there who think that “almost every graphic would be better as a bar graph.” To put it bluntly, I believe that remarks like this are too simplistic and don't belong in an otherwise worthy book whose aim is to give designers clues about how to deal with complexity.

Anyway, my two cents. Read a complete chapter of Data Points here, and don't miss its promotional video. Finally, get the book.

'The Atlas of Science': Visualization at Indiana University

I just got back from a short trip to Indiana University, Bloomington. I was invited by Katy Börner, from the School of Library and Information Science, to present at the Networks and Complex Systems talk series. It was fun, as we had students from different departments, including many from the school of Journalism.*

I was already familiar with Katy's work. For instance, I signed up for her MOOC on information visualization after teaching mine, although I didn't have time to participate, unfortunately. Also, Katy's Atlas of Science: Visualizing What We Know has been in my reading list for quite a while. She generously gave me a copy as a present. It's a gorgeous book full of inspiring, beautiful, bizarre, quirky, and enjoyable maps (geographical and conceptual) and diagrams. Not to mention quotes like this one, by George Santayana:

Noise becomes data when it has a cognitive pattern. Data becomes information when assembled into a coherent whole, which can be related to other information. Information becomes knowledge when integrated with other information in a form useful for making decisions and determining actions. Knowledge becomes understanding when related to other knowledge in a manner useful in anticipating, judging and acting. Understanding becomes wisdom when informed by purpose, ethics, principles, memory and projection.

However, the fact that I had visited Katy's website in the past didn't prepare me for what I saw. Katy's team at the Cyberinfrastructure for Network Science Center, a healthy mix of curators, scientists, engineers, artists, and designers, produces a huge amount of impressive scientific and data visualization projects. Sometimes people in presentations and workshops ask me about academic departments to conduct advanced graduate and postdoc work. Bloomington is at the top of my list already.

Visit the map gallery of the book and browse through all its images.

* Thanks to Bonnie and Steve Layton for encouraging their multimedia journalism undergrads to participate.

Success in visualization: Perhaps we worry too much

Enrico Bertini, Andy Kirk, and others have been asking themselves recently why we don't see more examples of 'success' in visualization. Here's Enrico:

Why I never stumble into an article or blog post showing, I don’t know, for instance, how visualization helped a group of doctors doing something remarkable with visualization?

He proposes three reasons:

1. Impactful visualization is hidden.
2. Visualization is just a fragment of a much larger process.
3. Visualization impact has yet to come.

I don't have time to participate in this conversation right now —it's the end of the semester at UM and my schedule for next month is simply insane— so let me just say that this is a relevant topic to analyze, but perhaps we are worrying too much for no good reason. There are thousands of little success stories related to visualization and infographics every single day. There's success every time that a statistician sees connections between variables thanks mainly to a scatter plot matrix; whenever a reader realizes how horrible unemployment is in Spain today; or when a magazine is able to visually display the increasing concentration of college graduates in certain areas, like The Atlantic did in these maps (I wrote about them in this other post):

And do you want famous examples of success? You may argue that Hans Rosling and Al Gore don't count, as their power of persuasion depends on their expertise as showmen, and not so much on the graphs they use, but what about Michael E. Mann's famous hockey stick graph, which I labeled as 'dangerous' here? No matter what you think about that graph, it is undeniable that its success at igniting debate has been huge. And don't you think we may be onto something when even the White House's website has an infographics section?

On a side note, I have finished writing my second long article for Peachpit (read the first one), which will be published in the next few weeks. It's about John Snow and his cholera map, which Andy mentions in his post, but I took a quite unusual approach. Anyway, before I sat in front of the keyboard, I revisited Tom Koch's magnificent Cartographies of Disease and Disease Maps. There are plenty of success stories in them. Check them out.

Who doesn't love a good infographic about great white sharks?

As many of you know already, my classes at the University of Miami —both at the undergrad and MA/MFA levels— don't deal just with data, graphs, and maps, but also with traditional infographics, 3D, and animation. This means that —yes!— I teach my students some tricks to draw stuff in Adobe Illustrator. Even those without a background in art and design (the overwhelming majority) end up doing a pretty decent job at the end of the semester. Data visualization is trendy nowadays, but I strongly believe that some notions of classic, old-fashioned visual journalism and graphic design will always be valuable, regardless of the career you plan to pursue.

Anyway, in the past few days I've been grading the second project of my Infographics class this semester. We collaborated with the RJ Dunlap Marine Conservation Program at UM. A while ago, scientists from the program released a series of papers about hunting patterns of great white sharks in South African waters. My students read the papers and participated in a press conference with the leading researcher, Dr. Neil Hammerschlag. Our goal was to produce tabloid-size posters that summarized the findings without dumbing them down. Think about it this way: There's a lot of amazing research going on at UM right now; you're a scientist: How do you communicate with the public? Perhaps by partnering up with a student from the School of Communication.

I'm showcasing some of the graphics above. None of them is a full A —sorry, folks; I'm tough—, and they still need to be edited and corrected, but they are satisfactory overall. After all, as I've explained before, these students began learning about infographics just three months ago.

L'Arte Funzionale and Leonardo da Vinci's Science Museum

Two weeks and a half from now I will be flying to Milan, Italy, to speak here and present the Italian edition of The Functional Art, whose cover you can see on the left (see it also in Amazon.it). Among the travels planned for the next few months, this is the one I'm more excited about. Not because the other ones aren't interesting —they certainly are!— but because I've been able to arrange an entire day off to visit art galleries and museums. That's unusual.

The main landmark of the visit will be the Leonardo da Vinci National Museum of Science and Technology. which holds a collection of Leonardo's technical drawings and of models built based on his notes. Take a look at them. Non vedo l'ora di vedere tutto questo! (I don't know if Google Translate has done a good job here...)

Update, April 18: Sign up for my talk here.

Making your message visible: Trend lines in scatter plots

If you teach infographics and visualization, here's an example to use when explaining the differences and similarities between designing for your peers (or for analyzing your data) and designing to communicate with broader, nonspecialized audiences. An hour ago, while reading The New York Times*, I came across a lovely scatter plot, the first picture above this paragraph. I read its headline and deck: "Mirth and Taxes. A study of 54 nations (...) found that those with more progressive tax rates had happier citizens, on average."

Then, I took a look at the graph and felt startled and puzzled. I tweeted:

Does this scatter plot clearly support the message mentioned in its intro? nytimes.com/interactive/20… #dataviz #infographics
— Alberto Cairo (@albertocairo) April 14, 2013

I couldn't see a solid relationship between the variables. In fact, a lot of countries are "more progressive but less happy" than the United States.

A minute later, Stuart Allen sent me the link to the research paper the NYT graph is based on. It showcases a similar scatter plot in which the line of best fit is kept. It also discusses several correlation coefficients the researchers calculated, and they don't look trivial, to say the least (see third screenshot above: r=.41). Isn't the line a critical element here, as it highlights the upward trend? Doesn't dividing the space of the graph in four quadrants make its message murkier, as the positive slope is not that visible? Or is it just me?

*In The Functional Art and also in previous posts in this blog I've mentioned that I am old fashioned. I still get the print paper every morning

Webinar on April 24th

On April 24th, 8-9 P.M. (EST) I will conduct a Webinar through my publisher, Peachpit. Registration is free, but space is limited. The Webinar has the same title as my book, but I won't talk just about it, as that would be very boring (I'd bore myself to death, actually.) Instead, I will try to offer a glimpse of the ideas that may show up in some of my future projects, which I discussed in this other post. On a side note, today Peachpit is promoting the first article I wrote for a series about data visualization and infographics. Check it out if you wish.

A bubble chart or a hairball would be better

Nathan Yau echoes an amazing interview with New York Times' Amanda Cox at Harvard Business Review. I tweeted about it the other day. It's a joy to read. What worries me a bit is the quote that Nathan highlights with big type and uses as a headline. Among the many interesting things Amanda points out, Nathan picks this one:

"There's a strand of the data viz world that argues that everything could be a bar chart. That's possibly true but also possibly a world without joy"

I guess that she was thinking about folks like Kaiser Fung. I understand that this was said during an informal conversation; that comment would be more nuanced if made in a different context. Just to give you an idea of how unfair it sounds, read the following made-up sentences, which are inspired by the work of some designers Nathan showcases in FlowingData:

"There's a strand of the data viz world that argues that everything could be novel, unusual, and fun. That's possibly true but also possibly a world without insight."

Isn't that absurd? Of course it is. It's a gross misrepresentation of what those designers believe, a wicked simplification. Fortunately, Nathan also brings up this other quote:

"If you make a fantastically interesting chart and some poor design decisions, the data will still come through. If you make a bad chart with a beautiful design, what have you done, really?"

It's true that there should be a beauty component in any visualization, and that trying new stuff every now and then (yes, even radar graphs) should be mandatory, as doing so may help expand our vocabulary. But it is also true that —if you want to call yourself a visual journalist or an information designer, at least— most of the time you may need to stay in the safe zone and stick to bulletproof shapes. You know: Bar graphs, dot plots (which are a good alternative to bar graphs,) line graphs, scatter plots, etc. If you shape your data in an innovative way just because it looks cool, or because it expresses the complexity of your inner world, you may be in the wrong business.

New column, videos, international editions, presentations, MOOCs, and other news

Some news after an exhausting month:

• I have started writing a series of monthly articles about infographics and visualization for my publisher, Peachpit Press. The first one is out: 'Emotional Data Visualization: Periscopic's "U.S. Gun Deaths" and the Challenge of Uncertainty.' In the next one I will probably write about John Snow and the short movie that was made about him a while ago. I've already interviewed the director, Isaac Ergas.

• On April 24th I'll conduct a Webinar, also at Peachpit. You can register for free here.

• I am teaching a workshop with Naomi B. Robbins in New York City in June. Registration is open.

• During the summer I will finally launch the long video tutorial I've been working on for the past couple of months. It's titled Creating Maps, Charts, and Infographics With Adobe Illustrator. The package, around 12 hours of video, will help you learn almost everything I know about Illustrator.

• There will be several international editions of The Functional Art coming out eventually. The first one is the Italian one, which will be published in the first weeks of May this year. I will fly to Milan to talk about it. I got word that the book is been translated to at least three other languages at the moment.

• Several people have sent me e-mails asking if I am planning to teach a third Intro to Infographics and Visualization Massive Online Course (MOOC). The previous ones were very successful, so the answer is yes. I don't have dates yet, but it will be at some point after August.

• I will visit several countries in the next few months (Brazil, Mexico, Switzerland, New Zealand, Finland.) If you are in any of those places and want to stop by to say hello, I will love to meet you. 

• Finally, yes, there will be another book, a follow-up to The Functional Art. Publication date? Not sure yet. But I am working on it.

Keep infographics weird: Panel about visualization in Austin

'Make infographics clear' is an ideal that lies at the core of my own design philosophy. However, I may consider updating it temporarily to 'keep infographics weird' right before the discussion I'm going to moderate at the International Symposium of Online Journalism two weeks and half from now. The program of the conference is impressive, and so is the list of participants in the graphics panel, titled "Data visualization: creating a new language to communicate big data."

Here they are:

• Chiqui Esteban, graphics editor, Boston Globe
• Hannah Fairfield, senior graphics editor, The New York Times
• Scott Klein, editor of news applications, ProPublica
• Kim Rees, partner & head of data visualization, Periscopic
• Lisa Strausfeld, global head of data visualization, Bloomberg

See you in Austin.

'Visualizing Information', workshop in New York, June 11-12

On June 11th and 12th, Naomi B. Robbins and I will conduct a 2-day workshop in New York City. It will take place at CUNY's Graduate School of Journalism.

The umbrella title is Visualizing Information: Storytelling with graphs, maps, and diagrams. My session, on the 11th, is titled 'The Insightful Art'. Naomi's will be on the 12th, and it's titled 'Communicating Data Clearly.' This is the first time that we teach together, so it will be an interesting experiment of integration of two very different —but complementary— approaches to infographics and visualization.

You can register for just one the days or for both if you want to take advantage of the reduced price. Space is limited. Participants in both days will get complimentary copies of our books, The Functional Art, and Creating More Effective Graphs (which is being reprinted right now.) If you come just one day, you will get the corresponding instructor's book. Lunch is also included.

Download the flyer with all the information (PDF)

Register here

I hope I'll see you there. On a side note, it will be also be a great opportunity to visit so many good friends who live in NYC. I'm looking forward to it.

Speaking at Harvard University

On April 4th and 5th I will be speaking at Harvard University. If you study or work there —or if you live in the area— and want to attend, send me an e-mail (alberto.cairo@gmail.com) and I will give you some details. The talks are open to the public, but they told me that space is very limited.

My first presentation will be at 2.30 p.m. on the 4th. I will be at Hanspeter Pfister's class. In the morning of the 5th, I will meet with the Nieman journalism fellows.

(To see other events, visit my calendar.)

Nigel Holmes' 'The Book of Everything'

Nigel Holmes is sitting close to me right now while we both listen to Juan Colombato's presentation at the Malofiej infographics conference. The book on the left is his latest, The Book of Everything (Lonely Planet), which was recently launched.

If you have read his elegant Wordless Diagrams, you know what to expect: The Book of Everything is a visual feast, a delight. It is a book to browse and to go back to for inspiration and fun every now and then: Coming from Nigel, you can expect a good amount of (mostly British) humor. I have quickly shot some pictures of it. See below.

Jaime Serra at Malofiej21: The best infographic of the past 20 years

While writing this I am listening to Jaime Serra deliver the keynote presentation at the 21st Malofiej Infographics Summit. Jaime is the infographics director at La Vanguardia —a big newspaper in Catalonia, Spain— and has a long career in the field.

Jaime's most famous piece, an infographic about the frank whale published by Clarín almost two decades ago, was named the most influential infographic of the past twenty years in the previous edition of Malofiej. To honor Jaime and his project, the organization has published a special facsimile edition of it, limited to 100 numbered copies signed by the author. The box contains a high-quality copy of the graphic itself, plus reproductions of the original sketches, articles, etc. I've shot some pictures of everything so you can get a sense of what to expect if, eventually, you manage to put your hands on this thing of beauty.

What makes an excellent infographic

If you follow this blog, you know that I've ranted more than once about marketing and PR infographics. The reason? Even if I believe that there's a lot of potential in these areas for well-designed pieces, much of the work we're seeing isn't built to facilitate understanding, but instead to "bring eyeballs" and "go viral" (I am borrowing their jargon). It usually shows an annoying disregard for the quality of the information and for basic principles of visual presentation. I am not against eye-catching infographics —quite the contrary— but honesty, efficiency, substance, and structure must come first.

What worries me the most, though, is that these bad practices —and the language they are based on— are leaking into other areas. If you don't believe me, read Infoactive.co's website and watch their promotional video. "Numbers are boring," they say? Sometimes, perhaps. But transforming them into useless, formulaic, cutesy graphs is unlikely to help.

I've discussed this in a recent interview with Edelman Digital, and in an article by Arnie Kuenn, who asked what constitutes a great infographic. Here you have my answers —read the entire piece, it includes the thoughts of other seven designers:

• What makes an excellent infographic? Good data properly and rigorously processed and organized, structure (narrative or otherwise), copy, and finally, visual style. An infographic should be thought of as a cognitive tool for understanding, an extension of our visual system: a consequence of this is that its form (or forms) should match the tasks it is supposed to help me complete. The first step any designer should take before even switching on the computer is to ask herself: “What do I want my reader to get from this graphic? What will the reader try to do with it?”.
Then, she should choose graphic forms accordingly: Do you want to show the geographical pattern of scattering of a variable? Then, you may need a bubble or choropleth map. Do you want readers to be able to accurately compare values and rank the regions? Then, maps or bubbles are inappropriate and you need to use a bar graph or a dot plot. In other words, think about function before you think about aesthetics.
• What should my expectations be for an infographic? An infographic is a visual presentation of evidence, not just a pretty picture. Therefore, you should look for accuracy, depth, and a presentation that matches what the human visual brain can and cannot do. This is something many designers don’t really get: the goal of a graphic is not to make numbers “interesting,” but to transform those numbers (or other phenomena) into visual shapes from which the human brain can extract meaning.
As I wrote in The Functional Art, a graphic should not be something to be seen, but something to be read and understood. It is not a presentation that you passively absorb, but a visual device you should be able to manipulate and analyze to better comprehend a story.

Malofiej Infographics Workshop and Summit: First photos

These days I am in Pamplona, Spain, teaching at the Show Don't Tell! infographics workshop, which is part of the Malofiej week. The Malofiej Infographics Summit will begin on Wednesday night.

Participants in the workshop, designers who come from around ten different countries, are working on an exercise right now. I've shot some photographs of the tables, the high-tech materials they are using (Pencils! Paper! Glue!), and of the other instructors, John Grimwade, Geoff McGhee and Juan Velasco. The first project of the workshop is a visual explanation of how a modern hotel operates.

Continue reading to see a sample (you can see more pictures in Malofiej's Facebook account).

Video of my presentation at the Journalism Interactive conference

Here's the video of my presentation at the recent Journalism Interactive 2013 conference (Gainesville, Florida). I talked about journalism, the risks of storytelling, data, infographics and visualization. Go here if you prefer to read a recap and see just the slides that I showed.

Getting ready for IC213 (the Netherlands), Malofiej (Spain), and other events about infographics and visualization

You won't read many updates in this blog for the next month. The reason is that my schedule for March and for the beginning of April is quite busy. In a few days, I am flying to the Netherlands to be the keynote speaker at the IC2013 and run an infographics workshop. IC2013 will be a great opportunity to see old friends (John Grimwade, Remy Jon-Ming, Michael Stoll) and meet people who I admire in person (Jan Willem Tulp, among them.)

After that, I will be in Malofiej 21st (see the details of the workshop and of the summit), and teaching a couple of classes at El Mundo's MA in Investigative Reporting, Data, and Visualization. On the first week of April, I will be at Harvard, speaking at the Nieman Journalism Lab and in Hanspeter Pfister's visualization class at the School of Engineering and Applied Sciences. I may need a break after all this!

The Sketchnote Handbook: Drawing is Thinking

All my students have heard this over and over again from me: "Draw tons of sketches before you commit to any specific shape or layout in your infographics and visualizations." I am hardly alone in offering this advice: Both John Grimwade and Moritz Stefaner, who lie in opposite extremes of the infographics-dataviz spectrum, suggested the same idea when I interviewed them for The Functional Art. I also devoted a great portion of a chapter in the book (the 8th) to explain how sketches fit into the creative process.

Some take this advice as old fashioned and useless. Perhaps they think that a sketch is a wasteful step that lies in between the time-consuming initial research and planning and the exciting finished graphic. But sketching is much more than a formality endorsed by academics and experts: When you give your visual mental images a physical shape —when you put them on paper, no matter how rough their execution is— hidden connections become visible and a deeper understanding of the information you're dealing with will arise. A sketch is an instrument for clear thinking. I don't draw sketches just to plan for my graphics, but to explore the story I want to tell. Call this learning by drawing, if you wish.

The bibliography about sketching and sketchnoting is growing quickly. The latest addition is the notable The Sketchnote Handbook: the Illustrated Guide to Visual Note Taking, by Mike Rohde. If you liked McCloud's Understanding Comics, Roam's The Back of the Napkin, and Kleon's Steal Like an Artist, this book should be part of your reading list.

The Sketchnote Handbook doesn't cover principles of visual design, as the sketches Rohde is interested in are not intended to be shown to anybody else, but to be used by the authors themselves as mnemonic devices. A sketchnote "is a memento, not a reference" (p. 120) and will help you focus while listening to a lecture: Sketching and taking notes force you to avoid distractions and pay attention at what's been said.

The book is organized in seven chapters that outline simple rules of thumb, strategies, and techniques. Many of them are excellent. Reading that "sketchnoting is about ideas, not art," for instance, may lead many people to overcome their fear of drawing. "I don't know how to draw!" is a deeply-rooted concern that is heard all the time in classes and workshops. Well, neither does my 7-year-old son, but this doesn't curb his artistic enthusiasm. School will do that for him, unfortunately, as Rudolf Arnheim explained in his magnificent classic Visual Thinking. It is appropriate to quote him here (highlights are mine):

"The prejudicial discrimination between perception and thinking is still with us. (…) Our entire educational system continues to be based on the study of words and numbers. In kindergarten, to be sure, our youngsters learn by seeing and handling handsome shapes, and invent their own shapes on paper or in clay by thinking through perceiving. But with the first grade or elementary school the senses begin to lose educational status. More and more the arts are considered as a training in agreeable skills, as entertainment and mental release. As the ruling disciplines stress more rigorously the study of words and numbers, their kinship with the arts is increasingly obscured, and the arts are reduced to a desirable supplement. (…) The arts are neglected because they are based on perception, and perception is disdained because it is not assumed to involve thought."

Visual Thinking was published in 1969. More than forty years later, perhaps it is time to take Arnheim's words seriously and recover our inner visual thinkers. That's what books like The Sketchnote Handbook are trying to do in a fun, engaging, and ultimately thoughtful way. Let's praise them.