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Edward Tufte

Is Data Visualization Useful? You’ll Have to Prove It.

by Jorge

Great data visualization is hard to measure: you can’t prove you have a good chart. Unless you can convince your employer to deploy at least two different formats/layouts and are able to compare results, you can say “this is a good chart” but that’s an act of faith, not an act of science.

It’s True Because It Rhymes

Information visualization experts like to evaluate a chart based on its compliance to some more or less accepted standards (Tufte’s data-ink ratio, for example). That’s like saying “it must be true because it rhymes”: the truth is defined by the language itself, not by the real world. Now, please close the curtains of our ivory tower…

I know, it’s not easy to assess the efficiency and effectiveness of good displays. They look natural and obvious, undeserving of praise and, probably, boring and uninspiring. Compare these charts:

Bubble charts

This is a true story: users wanted to evaluate sales territories, one at a time. Color-coding each bubble (Example A) was pointless, while Example B provided context without distractions. Guess what chart they would choose if they were allowed to… (happy ending: they reluctantly accepted Example B). (A word of advice: if you are looking for a promotion, a kindergarten chart variety always outperforms a “serious” chart.)

If your chart is doing a good job at helping people, no one will actually be aware of the chart’s role at making sense of the data. That’s why it is so hard to find good examples of data visualization using standard charts. If people actually like them, they like them because of their usability and/or interactive features.

When Stephen Few asks the readers “true stories about the benefits of data visualization” that’s almost an admission of impotence.  He should have hundreds if not thousands of good examples to share with us, right? Well, I know there are many examples out there, but I can give you none, sorry. Is data visualization some kind of astrology? I know it works. Why? Because I have faith. (On second thought, he is not asking for good data visualization examples. It really doesn’t matter if you use Tableau or Xcelsius, and that’s a relief.)

Opening the Pandora Box

Ultimately, what makes a good chart is how it resonates with your audience. Assuming that your are not unethically distorting the data, a chart that forces people to act is better than another one that only makes people aware of the subject.

If a single chart can save the world, it will not be a Few’s or Tufte’s 100% compliant chart. It will be a glossy Xcelsius pie chart.

(Wow, that’s depressing…)

If you read this blog that’s a clear sign of intelligence and sophistication :) . Unfortunately, you are not representative of the typical data visualization user and/or producer. The real world loves pie charts and doesn’t understand scatter plots.

Here is my Pandora box: give the audience what it expects and understands, even if that hurts your data visualization soul (OK, give it 90% of what it expects and use the remaining 10% to educate it.)

Cultural Relativism? Not So Fast.

Please don’t misrepresent these arguments. I’m not saying that all charts are born equal. There is a reference point and some misconceptions should be avoided A chart that maximizes insights, removes clutter, uses color wisely and clearly shows the patterns hidden in vast amounts of data, that’s probably a good chart and that’s what you should aim for. And yes, you should avoid pie charts.

If you present some sophisticated charts to your unsophisticated audience you’ll lose it. Relax. Draw a line but don’t forget the candies. You can take a horse to the water, but you can’t make him drink, unless you give him some sugar cubes…

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God and Moses? The Differences Between Edward Tufte and Stephen Few

by Jorge

I have a confession to make: my past is paved with chart-making sins, including some capital ones (yes, 3D pie charts, too). But years ago I saw the light in Edward Tufte’s The Visual Display of Quantitative Information and since then I’ve been avoiding eye-candy temptations. Now I do my best to pursuit the path of data visualization virtue.

Every God Has His Moses: Edward Tufte and Stephen Few

Some time after that first revelation, I stumbled on Stephen Few’s Show Me the Numbers and I though: “wow, Tufte for business!”. As a father of twins, I know that good things come in pairs, and now I had two great role models to help my recent conversion.

Or should I say one and a half?

Edward Tufte and Stephen Few are often cited together, as if they were a single entity. For many of us, simple mortals, Stephen Few is some kind of translator of God’s voice. Given Few’s background, that wouldn’t be completely inappropriate…

For some time that’s how I looked at Few’s work on charts and data visualization. But I was wrong. They do share similar views about basic data visualization principles. And they seem to share the same level of stubbornness, too. But there is a major difference.

Tufte, the Artist vs. Few, the Engineer

Tufte is an artist. His data visualization principles derive from Ludwig Mies van der Rohe’s minimalism, and in that sense, he approaches charts from an aesthetic point of view. His charts are as beautiful as a chart can be, if you happen to like the aesthetic minimalism.

I don’t know how and when Few became aware of the need for better data visualization. But he embraced Tufte’s principles not because he is an aesthete like Tufte, but because he values efficiency and those principles happen to improve it.

Stephen Few would never title a book “Beautiful Evidence”. He doesn’t mind to use Excel to create his chart examples, while Tufte needs full control of details like kerning (and he uses a designer’s tool, Adobe’s Illustrator).

On the other hand, Tufte would never write a book about dashboards (Beautiful Dashboards? brrrr…). From an actionable, business visualization point of view, Tufte is The Visual Display… Almost everything else is beautiful, yes, and perfect for the coffee table.

And while Tufte escaped Flatland for good, Few still keeps both feet firmly on the ground, discussing BI tools, pie charts or irregular time series (and I don’t think his new book changes that).

The Need for a New Business Visualization Model: the Emotional Link

Both approaches are very consistent and they give you a set of guidelines that you can apply to all your charts and adopt as a general framework.

What I am not comfortable with is their positivist attitude, specially in Few. Because Tufte’s charts are aesthetically pleasing, we can derive some emotion from that. In Few’s case, his charts are purely functional.

I still don’t know where to draw the line between purely rational/functional visualizations and the eye-candy. Let’s see this pattern:

Boy meets girl, boy gets girl, boy loses girl, boy gets girl back.

Do you feel emotionally overwhelmed? No? Do you even care about the story? Do you even care about the boy and the girl? Let’s try again:

John fell in love with Anna the moment she spilled coffee on his shirt.

This sounds much more interesting. Add three more sentences and you’ll complete the boy-meets-girl pattern. Both versions share the same pattern, but the second one adds some (perhaps irrelevant) detail and creates an emotional link between the audience and the characters.

You need that in data visualization, too. You don’t have to cry because you chart shows a market share drop in Alaska, but you must connect with the reality behind the chart and the data.

The Need for a New Business Visualization Model: Interaction

Jacques Bertin says that knowledge is built by the user when interacting with the chart. Why interaction (and animation) is absent from Tufte’s and Few’s books is something I don’t really understand.

Although I respect Tufte and Few, I feel that there are pieces missing in their theories. We can borrow some pieces from Bertin’s work (and Tukey’s?) and that will surely help, but the real issue here is to find the balance between the need to correctly (bureaucratically?) display the data and the emotional response that helps to keep the audience interested.

Back to you, a very simple question: what are Tufte and/or few missing? What pieces do we need for a XXI century visualization?

Photo credits: ~L. and David Zellaby.

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Can Edward Tufte Do Business Charts?

by Jorge

1. Tufte, the Father of Eye-Candy Charts

Tufte’s The Visual Display of Quantitative Information, published in 1983, is probably the most influential book in the history of data visualization, and it is likely to remain so for some more time.

In his book, Tufte outlines for the first time a consistent theory of how a chart object should look like and why it should look like that. His guidelines are easy to understand and very quotable, not buried under six feet of abstractions. Think of well-known concepts like “data-ink ratio”, “data-density” or “chartjunk”: they all come from The Visual Display…

However, too often these principles are taken as self-evident, somehow “discovered”, not invented. A fundamental clarification must be made: these are aesthetic principles that Tufte transposes (brilliantly) from Ludwig Mies van der Rohe’s minimalism to the field of data visualization. These are not universal principles backed up by scientific evidence. Some studies find them helpful, some studies say they are irrelevant, but their effectiveness is hard to measure and they should not be taken as indisputable laws (I call this the “what-would-tufte-say syndrome“).

Unlike other authors (Jacques Bertin, Tukey, William Cleveland), Tufte recognizes that only an aesthetic framework can structure the image (color management, the role of non-data objects, how to emphasize/de-emphasize elements in a chart…). This is clearly the realm of graphic design.

Using aesthetics to improve function is probably the major contribution of Edward Tufte to the display of quantitative information. Unfortunately, this idea that a chart can be an aesthetically pleasing object (“Beautiful Evidence”, the title of his latest book, says it all) went astray and gave birth to a whole industry of eye-candy visualization tools.

From Tufte’s positivist point of view, a chart is defined by how well it makes a pattern stand out. It may be boring but, if that is the case, then “you’ve got the wrong numbers”. His faith in human rationality is both charming and frightening…

2. Patterns, patterns, patterns. And something else.

There are so many misconceptions  to discuss about data visualization that we often forget to emphasize this simple true: data visualization is about pattern discovery, finding useful, actionable visual patterns hidden in the data and make them stand out. Let me repeat: it’s all about visual patterns.

Tufte would agree, but here is the fun part: there is nothing wrong with using 3D effects, textures, and all the decoration in the world. Use them! It is your good taste against Tufte’s. You don’t have to like minimalism. Add color, clipart, anything that you think can engage your audience.

I am not kidding. It’s you, not Tufte, who defines your aesthetic program. Almost anything goes. But, whatever you do:

  • Don’t design technically incorrect charts: do not distort a circle, do not use more than one series in a pie chart, do not make an object variate in two dimensions when you are using a single series, etc. Just common sense, really. And, of course, if you want to break the rules, know them first.
  • Don’t hide the patterns: find the patterns and make them visible. Remove everything except the series themselves. Now start embellishing your chart. But remember: every little thing you add multiplies the clutter and makes the patterns harder to see. You’ll have to find that point where the impact of eye-catching decoration on pattern visualization goes beyond an acceptable threshold.

Please note that minimalism was not randomly chosen. Not only it makes pattern discovery much simpler but also creates a framework to evaluate what belongs to the chart and what doesn’t belong. You can reject it, but if you don’t have a different framework you must decide on an ad hoc basis. Unless you are an accomplished graphic designer (and even then), a minimalist approach is a good start and it should help you to find your own style.

3. Emotions, Emotions, Emotions

Let’s face it: you don’t have much choice. If you do not want to sacrifice patterns, the amount of of decoration that you can actually use is very limited.

So, what do you do with that limited amount of decoration? Essentially you’ll try to create the right emotional response. This is not what you would expect from a over-positivist chart that you end up with by choosing the minimalist path.

Refusing to acknowledge the role of emotions in data visualization is a bizarre thing, considering that you can’t remove aesthetics from the equation, and we all have an emotional sense of Beauty. What many hardcore Tufte fans may consider chartjunk can actually keep the audience from turning the page.

4. Edward Tufte and Excel

Throughout his books, Tufte often refers to the higher resolution of paper, and how it outperforms the current screen resolutions. His sparklines are meant to be printed, because only then the fine details can be observed.

In Edward Tufte’s vision, each chart is unique, and deserves the attention of a work of art. He despises PowerPoint and hardly mentions Excel. His charting tool is Adobe Illustrator, where he is in full control of each small detail. He admonishes against patronizing the readers, but he never really discusses the audience as something that should be taken into account when designing a chart.

5. Knowledge Is Built by the User

matrixpermutator

Much as changed in the last 27 years and you may think that Tufte’s The Visual Display… emphasizes the use of paper just because the extraordinary changes in information technology were still in their infancy back in 1983.

Thing is, that’s not the reason. The real reason is that Tufte always thought of a chart as a final product to be printed and handed to the audience, not something that could be manipulated by the audience.

There is a striking difference between Edward Tufte and Jacques Bertin. Bertin’s “reorderable matrix” is dynamic by definition, and and one of my preferred quotes summarizes perfectly his views:

“It is the internal mobility of the image which characterizes modern graphics. A graphic is no longer ‘drawn’ once and for all; it is ‘constructed’ and reconstructed (manipulated) until all the relationships which lie within it have been perceived.”

This was written in 1967, long before the PC was even imagined. Edward Tufte wants to design an efficient but elegant chart, Bertin wants to solve a business problem. There is no contradiction, one is not better than the other. They just serve different masters. (The image above is from Bertin’s Graphic Semiology and shows how a “dynamic chart” looked in 1967…)

Forty years have passed, but a vast majority of data users have no access to dynamic charts, either because they don’t have access to the right charting tools or they are unable to create those charts using their current tools (it is not that easy for a beginner to create a dynamic chart in Excel).

6. The Life Span of a Business Chart

In his essay “The Cognitive Style of PowerPoint” Edward Tufte argues that the tool itself is intrinsically flawed. I agree with him. Tools are not neutral. They can be forced to do things against their will, but that’s never easy. You can create a dynamic chart in Excel, but it is difficult. You can even force Excel to work like Tableau, but that’s like reinventing the wheel. You can create good chart in Crystal Xcelsius, but that’s against its nature.

The point is, you can apply Edward Tufte’s principles by the book, but that means spending hours perfecting a chart in Illustrator and then printing it. I’d love to. Unfortunately, that’s not exactly how things work in a business environment. The life span of a business chart is short and the time to create it, even shorter. We cannot use Illustrator to create business charts.

7. Take-Away Points

Break away from Edward Tufte, but make sure you know why. Add emotion to your charts (rationally). Decide if the level of eye-candy your audience needs goes beyond what you are willing to add. Other things been equal, an interactive chart should need less eye-candy than a static one. Above all, show the patterns (but make sure your audience wants to see them).

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Pie Charts – A Devil's Advocate Point of View

by Jorge

In what seems to be a post-vacation syndrome, I am in the mood for pie charts. I see them everywhere, even in car logos.

Actually, I am more in the mood to defy current “crowd wisdom” about pie chats.

Search the web for “pie chart” and you’ll get more than one million results, and a depressing picture of human knowledge. Browse the first 100 and what do you get? Some educational(?) sites (poor kids), tutorials (Excel, php, java, Illustrator), humor (here, here, here), bad (here, here, here, here, here or here) or just plain stupid examples. You’ll also find them in in court or fighting government (who could ever imagine that?). I’ll leave for another post what the Wikipedia and the pie chart thread in Tufte’s Ask E.T. say about pie charts (Stephen Few’s Save the Pies for Dessert is not listed within the first 100 results).

An old litany

Some of these sites discuss the use of pie graphs, but they usually recite the same old litany: our perception is bad at judging angles, you should use no more than five or six categories, don’t use them to compare series, Cleveland’s findings, etc. (there also is at least one unfair comparison between pie and bar graphs and one very aggressive rant against them).

If there is something that I would like to have written about pie graphs it is this Expert notes at ManyEyes:

Pie charts have a mixed reputation. They are popular in business and the media but many information designers have criticized the technique. Some claim that the pie slice shape communicates numbers less exactly than other possibilities such as line length. But this remains unclear in the context of proportions: for example, we have seen no studies that looked at the task of judging whether an item is more or less than 50%. It’s also unclear whether exact communication of numeric values is the only evaluation criterion; at least one study indicates that use of a pie chart for analyzing a problem as opposed to a bar chart changes the way people think about the problem.

This is clearly more constructive than saying that “they are as professional as a pair of assless chaps” (less funny though).

Not all charts are born equal

Current wisdom presumes that bar graphs and pie graphs are equivalent. For that reason, bar graphs should be used, always. After all, they are more efficient, right? But if they are not equivalent, as the above quote suggests? Take a time series, for example. If you want to see trends, you’ll choose a line graph; if you want to compare data points you’ll use a column graph. They are very similar, but by choosing one or the other, the designer is making a choice of how he/she’ll  look at the problem. Bar graphs and pie graphs are very different, so shouldn’t we think twice before selecting a bar graph because of its presumed superior efficiency?

This disdain for pie charts has its roots in Cleveland’s work and in Tufte’s and Few’s writings. Their positivist view towards information visualization may be as relevant as the classic economic theory and its presumption that consumer always take the rational decision, but are we not all predictably irrational? I agree with Robert at EagerEyes when he says:

There is no doubt that we need to be careful about the choice of visual representation, and that we need to encourage the use of good charts and criticize the bad ones. But that doesn’t mean we can get lazy and squeeze everything into a few standard charts types we’ve been using for decades. That is especially true if we want people to actually care about what we’re trying to show – and not bore them to tears.

We should probably try to be more rational and circumspect in a decision-making environment and do not use the media as our role model, otherwise business visualization may become useless. However, ruling pie charts out is not the wisest decision.

Simple rules are made for beginners. Let’s break some. How about this one:  “you should use no more than five or six categories in a pie chart”. Are you sure?

(Before that, we must re-read what Cleveland said and what others said about Cleveland. That’s the next post.)

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Minard, Tufte, Kosslyn and Godin (and Napoleon)

by Jorge

Do you prefer the full report:



Or the executive summary?

napoleon



For Tufte’s fans, Minard’s map plays a central role in Tufte’s iconography, and the way he praises it (“best statistical graphic ever”) is quoted endlessly (974 results in Google as of today, to be precise). Tufte discussed The Map in his first book (The Visual Display of Quantitative Information) and in Beautiful Evidence he uses it to illustrate six Fundamental Principles of Analytical Design:

  1. Show comparisons, contrasts, differences
  2. Casuality, Mechanism, Structure, Explanation
  3. Multivariate Analysis
  4. Integration of Evidence
  5. Documentation
  6. Content Counts Most of All

But, of course, they violate Seth Godin’s Principle of Make a Point in Two Seconds for Lazy People (here, about minute 17:30):

…this is one of the worse graphs ever made. He [Tufte]’s very happy because it shows five different pieces of information on three axis and if you study it for fifteen minutes it really is worth a thousand words. I don’t think that’s what graphs are for. I think they try to make a point in two seconds for people who are too lazy to read the forty words underneath. And to make me spend fifteen minutes studying it doesn’t make sense.(…) The kind of person he wants to reach they want to read a complicate, difficult to understand graph and get the satisfaction of figuring it out, because then they get it…

In this post he uses pie charts to further illustrate his principle:

Pie charts are a great example of how people go wrong. [First pie chart, eight slices] It’s accurate. It shows more than a half a dozen places that traffic come from. It’s also useless. It’s ungrokable. It doesn’t have a point. [Second pie chart, three slices, one of them exploded] Here’s the same data, grouped to make a point. “We get our traffic from three sources, one dominates the other two, but only one of them is under our control in terms of our ability to scale it directly. So let’s talk about how we grow that slice.”

Godin is not alone. Minard’s map also violates Kosslyn’s Principle of Capacity Limitations and Principle of Compatibility:

The hazards of not respecting the limitations of human mental processes are nicely illustrated – ironically – by one of Tufte’s favorite graphics. (…) This display has never captivated me for the simple reason that given human processing limitations – I needed several minutes to figure it out. (…) I can’t agree that this is an effective way to communicate; the display doesn’t present the facts so that they’re clear or easily absorbed. If you are in the mood, you may enjoy taking the time to study the display for the fun of solving a puzzle, pondering intricate details, or appreciating the graphic devices employed. But if you want the facts and want them in a clear, easily understood way, this display is not the solution.

So, in order to design a better graph, Kosslyn proposes a new design that could take advantage of the Principle of Salience, Principle of Relevance, Principle of Perceptual Organization and Principle of Discriminability e makes a better use of the Principle of Compatibility. The end result doesn’t seem much better than some revisions of Minard in Michael Friendly’s Gallery.

(By the way, I’m also posting a series on design principles for better charts…)

I find all this slightly absurd.

The divide here is, of course, the level of detail you need or are prepared to accept. A good/bad chart is not defined by the time it takes to read it, it is defined by the insights you get from it and how efficiently it tells the story. Minard’s map is much better at this than the typical dashboard or presentation slide we are used to, a War and Peace in a single image against a boy-meets-girl-boy-loses-girl-boy-gets-girl plot in fifty slides.

Tufte says “to clarify, add detail”, but detail is a dangerous thing. It is the detail you choose that defines how you interpret reality, and it exposes your biases. Minard adds detail to explicitly link deaths to cold temperatures during retreat, but around 75% of men died on the way to Moscow and he doesn’t tell us why. You can seriously undermine your analysis by adding detail to the wrong places.

No details for Godin, please. He contradicts himself, but I suspect he couldn’t care less. He wants less data and a chart that makes a point in two seconds. But then he needs “to talk about how we grow that slice” and that means more data. Wouldn’t it be nice to have in the same chart something that helps him? Of course, that would require more than two seconds to read the entire chart…

At the end of the day, what really matters is how you manage your data. If your skills are poor, your charts will always reflect that, even if you are a Tufte fan and no matter how much detail you add…

So, do you believe that this is “the best statistical chart ever” or that’s something that we shouldn’t take too seriously?

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The "what-would-Tufte-say" syndrome

by Jorge

An alarming level of the “what-would-Tufte-say” syndrome can be found in this post and some of its comments discussing a New York Times’s infographic. This syndrome has some recognizable features like the extensive use of “chart junk”, “lie factor” or other terms and expressions coined by Tufte that reveal a somewhat misunderstanding or abusive usage for legitimacy purposes (argument by authority).

You can spot the syndrome as soon as you land on the page. In spite of what the author claims, there is no “Chart Junk in the New York Times”: there is no grid, there is no moiré, there are no “decorative forms or computer debris” (Tufte, The Visual Display…), there is no Duck.

A never-ending story: the glamorous scale break discussion

The real problem in the chart is the scale break, but that is not “chart junk”. It could be “the data-ink ratio”. It could be “the lie factor”. But is it? The never-ending discussion over the use of scale breaks is almost as absurd as the one over pie charts. And the answer is, as always, the definitive “it depends”.

A scale break should be obvious, explicit, prominent. You must be sure that the reader will notice it. And it should not be used lightly. But if zero doesn’t make sense with your data or the variation is so small that you get an empty chart with an almost straight line at the top you should use a scale break to improve resolution.

As a rule of thumb, you can use scale breaks in line charts but not in column charts. Or at least that’s what Stephen Few believes:

“You should generally avoid starting your graph with a value greater than zero, but when you need to provide a close look at small differences between large values, it is appropriate to do so.

(…)

Never eliminate zero from the quantitative scale, however, when bars are used to encode the values. Why? Because a bar encodes quantitative value primarily through its length, and, without zero as the base, the length will not correspond to its value.”

But Kosslyn expresses a different opinion:

“Unless the zero value is inherently important, make the visible scale begin at a value slightly lower than the smallest value in the data, and the upper value slightly larger than the largest value.”

(His example uses column charts…)

Tufte would be proud

Hermeneutics enjoys a long and noble history, so it comes as no surprise those 3.230 results that you get if you google for “‘Tufte would be proud’”.

I would be proud of myself if I could fully understand and practice his design ideas and understand also at what point they stop working. Because they do. And sometimes…

  • pies can be used;
  • you are not lying just because you broke the scale;
  • even the “above all, show the data” principle can be disputed;
  • an excessive dosage of a minimalist design can be perceptually wrong;
  • the audience doesn’t get your cleverly designed chart;
  • people just don’t like it;

Want a simple receipt for better charts? Mix Tufte’s principles with some emotional design, add perception and, if you work in a corporate environment, learn how to use the kitchen tools.

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