Business intelligence expert Stephen Few goes on another rant about information graphics — mainly about the work of David McCandless, designer of The Visual Miscellaneum. Few’s post is in response to another from Teradata marketing director Mario Bonardo, praising innovation and new ideas, etc for business intelligence.
Bonardo wrote: “Being asked about the differences between traditional information graphics and his own ones, McCandless said he is aiming to remove as much irrelevant information as possible to get to the core of things, discover new correlations and challenge traditional views.” My dismay does not stem from McCandless’ words, but from his actual practices, which don’t deliver what he claims and certainly don’t point the way to a productive future for analytics.
Normally, I take the let’s-agree-to-disagree route, as these types of arguments always end up going in circles, but I actually agree with Few. Not because I don’t like David’s work (I do), but because David’s work is a cross between news and entertainment. Business intelligence, which really is just statistics for business, is analysis. It’s not entertainment.
Few ends with:
Rather than trying to innovate in the realm of analytics without the required expertise, it’s time for BI companies, consultants, and thought leaders to first learn the basics of data sensemaking and communication—analytics—and only afterwards to try their hands at creating something new.
It’s the nature of technology to highlight and bring hype to bright and shiny tools, but in the end, the tools are just that. You still have to learn data. Whether a tool works or not depends on the purpose and context.
[Visual Business Intelligence | Thanks, Jan]
You agree with the content of my blog, yet you call it a “rant.” You might disagree with my position at times, but in all cases I write well-reasoned, articulate, and thoughtful pieces in my blog, articles, and books–I speak directly and passionately, but I never rant. To characterize my work as rants is dismissive and undeserved.
I’ve critiqued McCandless’ work previously, as well as that of other infographic desingers, and I always do so with substance, as you know. These arguments will indeed “always end up going in circles”, as you point out, if they are not rooted in reason and evidence, rather than opinion alone.
I’m a fan of infographics. I recently served as a judge and keynote speaker at Malofiej 19, one of the premier journalistic infographics summits and competitions in the world. I was invited to do so specifically because many seasoned infographic’s professionals share my concern that infographics often fail to inform because they don’t present information in ways that our eyes can perceive and our brains can easily comprehend. McCandless’ work is often an example of this. Several top infographics’ designers share this concern with me.
My concern is not rooted in opinion, but by a large body of research into visual perception and cognition. I care a great deal about the aesthetics of data visualization, but believe that form and function, aesthetics and usability, are not in conflict with one another. Data can be displayed in beautiful ways that draw people into the information, rather than distracting them from it. To sacrifice meaning, accuracy, and comprehension for the sake of beauty is an act of lazy, unskilled design. Good data visualizations merge beauty and function without sacrificing either.
I’m traveling and on phone so I’ll have to be short. I meant no disrespect by calling your post a rant. A “strong critique” might have been a better choice of words. Other than that I’m going to agree to disagree.
At some point when you’re no longer traveling, I’d like to hear what it is that you are agreeing to disagree with me about.
It’s important to ask why McCandless’ approach has been growing in popularity. Clearly, something about his visualizations resonate with a large number of people outside of the infographics/BI professions. This is either because A) people like his approach, finding it informative and visually appealing (whatever it’s shortbacks may be), or B) people are not smart enough to realize when they’re being hoodwinked in the name of style over substance. B) seems to be the implicit assumption made by many of McCandless’ detractors who note, with dismay, his growing legions of followers. But this is far too cynical for my liking. We live and work in a free, open marketplace of ideas. It stands to reason that ideas gaining widespread popularity in this marketplace are doing so deservedly.
Stephen: Articulate blog? You pose as a magician on it! It’s clear you love to bath in your own thoughts. Your breadth of understanding data is limited to analytics. While this is very relevant in some fields, especially when time is limited and decisions must be made quickly, you completely disregard the relevance of story telling, yet you spend a majority of your time bashing it. And to make your points relevant, you point out your book or that your appointed to judge on some panel. The reality is that no matter how loud you bark, it’s the story behind data that people are seeking more and more. Yes, the fluffy pictures. Rather than fighting it, you should try and find more constructive ways to work with it.
Rather than basing your assessment of my work (and my character) on a photo, which you’ve misinterpreted (it is actually from a photo of me teaching, gesturing with my left hand to words on a whiteboard, which have been removed because they aren’t relevant to the blog), I suggest that you take the time to become familiar with it if you wish to engage in useful dialog. Contrary to your assumption, most of my work does not focus on analytics, but on telling the stories that dwell in data using graphics. Because people do need to hear the “story behind the data”, I bark loudly. Why should anyone spend their time finding ways to work with “fluffy pictures”? As you point out, the goal is to understand the story the dwells in the data, not find a way to co-exist for fluffy pictures. It is for this very reason that I critique McCandless’ work.
Your comments don’t actually help McCandless, nor do they further this discussion. Your response illustrates the point that I made when I said to Nathan: “These arguments will indeed “always end up going in circles”… if they are not rooted in reason and evidence, rather than opinion alone.”
Thanks for responding with reason. I’ve spent a great deal of time trying to understand why approaches like those of McCandless gain popularity. It is true that infographics of this type resonate with a large number of people. I want to challenge your line of reasoning, however. The list of potential explanations does not boil down to the two options that you present: (1) that it actually works (that is, people find it informative) or (2) that people are stupid.
Setting aside the second option for the moment, I doubt that you really want to argue that popularity necessarily indicates merit. Paris Hilton is quite popular, perhaps for some of the same reasons that McCandless’ work is: viewing gives pleasure. There is no question that his work is fun to look at, but that’s not the ruler by which we measure the effectiveness of data visualization. The relevant question is, does it do a good job of informing. If you haven’t already, please read my article “Our Irresistible Fascination with All Things Circular” and then let me know if you find fault in my assessment of McCandless’ work.
Now, let’s consider your second option: that people are stupid. The fact is, people are often drawn to things that don’t serve their best interests. This does not mean that they’re stupid, but rather that they are often irrational. A number of fine books have been written in recent years to point this out and back it up with a great deal of empirical evidence. Experience has taught me to trust less than you in the wisdom of crowds. In time, the free, open marketplace of ideas usually produces good results, but it goes through a lot of nonsense before getting there.
Every time a new group becomes interested in data visualization, their exploration of it repeats many of the same old mistakes that we made in the past. As the business intelligence industry has recognized it’s potential as a new way to sell their products, data visualization has been dragged back into the silliness of 3D pie charts and a host of other bad practices. As people trained in the arts have recently discovered data visualization, many of them have forgotten that it is about information. In time, this will pass, but for now, we should stay focused on the goal: to explore, make sense of, and communicate information as effectively as possible in an effort to make better decisions based on evidence. Why? To build a better world. To the extent that McCandless or anyone else does this, I’ll support them with all my strength. As long as they fail, I’ll critique their work and promote practices that get the job done.
I have not read his blog, but just from the replies here, including the defense against ranting, I feel the use of the word ‘rant’ is likely appropriate, as well as the suggestions of a certain quality of self importantce.
Whatever his ego (I don’t know him personally), Few’s book “Information Dashboard Design” is the best I’ve read on the topic so far.
And you can like or dislike him, but you can’t deny that he is arguing with facts rather than opinions.
Do yourself a favor and read Stephen’s books and his blog, before you make such an uninformed comment.
“Wisdom of crowds” and/or the choice of the majority often results in less than optimal. Why? All too often because the level of wisdom appeals to the lowest common denominator. With the lack data visualization training in mainstream education, it should not surprise us to see that less than informative displays appeal to the masses.
Story telling may be an interesting way to get a point across, but Mr. Few deals with tools that should allow you to find and create the story, not with tools that allow you to tell a story you already know. These tools should allow you to experiment with the data, find patterns, and then gather information from it. In the second phase you can choose to present this information to others: maybe as a story, with compelling graphics if you want to.
We only see the second part of this when we look at the work of Mr. McCandless. That is the reason I submitted this article to FlowingData: because it draws a distinction between visualizations that tell you only one, pre-selected story and tools that allow you to find the information that matters the most to your situation. “End-user infographics”, like those appearing on the NYTimes, can be of both types: the best are of the latter type, where the journalist maybe elaborated on one part of the story, but you can explore that data further and find another part yourself.
Sometimes infographics can be art, exploring possibilities. But in the world where Mr. Few works, infographics are tools, where proven approaches are more useful than experiments.
English is not my native language, and in my understanding the definition of the word “rant” got broadened to mean “any expression that is not mainstream”, without the implication that it would be nonsense or not argumented. Maybe that is also what Nathan meant here?
I wholeheartedly agree with what Few has said and I’m a firm believer that data visualisation is not about who can visualise data more beautifully but who can deliver the message through it. I’m not rejecting aesthetics at all but I think aesthetics come after your graphic is good enough to communicate with user and user can capture the message from it.
Few says: “The relevant question is, does it do a good job of informing.”. I think that that’s true, but only if that is the purpose of your visualization. There are also cases where you could just create beautiful graphics based on data, but not necessarily to inform, but just to present (data-art). But the goal should be clear in the first place.
I also agree with Few that purely informative visualizations can be very aesthetically pleasing: form and function, aesthetics and usability are indeed not in conflict with each other.
Now McCandless, I think that what he tries to do is to inform. But if you want to inform, at least what you should do, is to be clear, and quite often the visualizations of McCandless, though engaging, give me more questions than that they answer them. If your purpose is to inform, I think you should not create confusing visualizations.
Let me give you an example: recently McCandless created the Radiation Dosage Chart: http://www.informationisbeautiful.net/2011/radiation-dosage-chart/ . It is quite obvious that this is a visualization that should inform you about radiation, and to put all the news about radiation in context. But although the colors look nice and vibrant, the triangle and it’s colors appear to be just randomly chosen. It causes me to question: why these colors, what do they represent? What does the triangle stand for, and how and why doesn’t it match with the numbers? The numbers themselves seem to scale as well, but with a different ratio, so does that mean anything? And if so, what?
I like McCandless work mostly just for inspiration, but the way he combines data driven visualizations with just randomly chosen visual elements confuses me too much to be really informed. And combining data driven visual elements with randomly chosen visual elements is tricky I think.
I prefer that form follows data (or function), whether you create highly effective visual analytics tools or data driven art or anything in between. But if your goal is to inform, you should not confuse.
What do you think?
I undertand what you mean by (data-art) but I think data visualisation is not the right platform where you show your art. To me data visualisation is quite a serious business as we are dealing here with facts and one should do the justice with it by presenting it properly. Its not easy to gather data, and people who put their effors in putting it together dont expect someone to play with it but to present it in a way that the audience understand it and make sense of it.
To show skills in “Art”, I think there are other platforms available to do it.
@Waqas I understand what you mean, and it is obvious that we’re talking about situations where a visualization should inform.
But with regards to ‘data-art’, I think it really depends on the definition of data visualization you use (and there is no definite one as far as I know). I think one of the broadest definitions you can find of data visualization is “the visual representation of abstract data”. And in that sense I think data-art can belong to that definition.
On the other hand, if you take the definition by Friedman (2008): “main goal of data visualization is to communicate information clearly and effectively through graphical means. It doesn’t mean that data visualization needs to look boring to be functional or extremely sophisticated to look beautiful. To convey ideas effectively, both aesthetic form and functionality need to go hand in hand, providing insights into a rather sparse and complex data set by communicating its key-aspects in a more intuitive way. Yet designers often fail to achieve a balance between design and function, creating gorgeous data visualizations which fail to serve their main purpose — to communicate information” then I guess data-art is not really part of that.
I think there’s a place for anything between “data visualization to inform” (which is serious business) and “data visualization as data-art” (which is not necessarily serious business :), as long as your purpose is clear, and you don’t mix up the two.
I think most of the agressivity in the discussion towards either Stephen Few or David McCandless is unjustified. Again we are using the same words to describe two different things.
From clarity come story.
data visualization can be very accurate and rigorous, and yet from this economy of means come understanding, especially if the right questions have been asked before creating a visualization. This would be the Few approach, if I read the books right.
From story to data
the opposite approach starts by graphic design and trumps best practices rules. by delivering an enticing form the designer draws her audience to dig deeper and open up about the subject, although the way the data is encoded is not simple. That approach (mcCandless and others) is still based on mathematical transformation of data and is neither erroneous nor designed to deceive.
so both parties can argue that what they are doing is the proper way to visualize data and to tell stories and both would be right although they are talking about things which are opposite in nature.
That said, I find it an exaggeration to put the work of McCandless in the same box as 3D pie charts, if only because he is a designer who picks the appropriate form for what he is trying to achieve with his visualizations, whereas 3D pie charts and the like are usually generated by faulty systems.
also, I understand the reaction of Stephen Few on the word rant.
I think Jerome strikes the right balance exactly.
In my perception:
-Few approaches from a much more rigorous, data-is-the-story frame of reference.
-McCandless approaches from a tell-a-compelling-story-with-the-help-of-data frame of reference.
Neither are wrong in my opinion – they’re just different. However to accuse McCandless of being misleading is (I think) to admit that you’ve never tried to capture people’s broad interest. Often, to appeal to a broad audience you need to simplify. And I don’t think there’s necessarily anything wrong with that. A “correct” graphic nobody sees is worthless. An “incorrect” (in Few’s definition) (but not misleading!) graphic that is seen my millions is valuable.
And adding my opinion…
Given my skillset, I find it very easy to produce something Few-like, but difficult to produce something McCandless-like. Browsing Few’s examples of work is like browsing an excel library. It’s “right”, but I move on pretty quickly. Browsing McCandless’s work is like browsing an art gallery. I’m drawn in and find something to think about. Right or wrong, I can tell you which I find more valuable in my work as a data-vis guy…
You’re quite mistaken about my work. Most of my work involves teaching people how to tell the story once they’ve discovered it in the data. My work is not defined or limited by particular tools. I teach data visualization principles and practices that can be applied using any decent tools available. In fact, I often use the same software tools that McCandless uses when creating infographics.
People have been telling stories with graphical displays of quantitative data since the days of William Playfair in the late 18th century. Until the advent of the PC, these visualizations were created by hand, perhaps with the help of draftman’s tools. The work of McCandless and others with training in the arts that do similar work is a recent addition to a long history of data visualization, not the advent of visual storytelling. Contrary to your assertion, in my world infographics are definitely not tools—they are graphical representations of data meant for the purpose of informing. They can be designed to serve other purposes as well (to teach, persuade, etc.), but to qualify as infographics, they must at a minimum inform, and ought to do it well.
Jan Willem Tulp,
I appreciate your comments, but wish to correct a misunderstanding. Visualizations of data can be used for many purposes, as you say, including expressions of beauty without any intention of informing. But when visualizations are used primarily for artistic purposes, they are not what we call data visualizations or infographics, which are terms that have been in use for a long time with particular meanings. I’ve often argued that, to avoid confusion, a different term should be used for expressions of data that are used primarily for artistic purposes, such as “data art.” I’ve seen beautiful art that is based on data and have appreciated it as such. I cannot appreciate it as data visualization or an infographic, however, unless it informs and does it well.
The approach of McCandless and other graphic designers who do similar work does not begin with design and then proceed to data. Whenever a story is told with data, you begin by understanding the data, then create a design that presents the stories that live in the data as clearly as possible. What I and many others teach as data visualization best practices are not arbitrary, but have been developed from an understanding of visual perception and cognition, based on a large body of research. Ignoring these practices produces visualizations that cannot be easily or accurately interpreted. McCandless often fails by choosing forms of visualization that are inappropriate, because they cannot be perceived easily or accurately. When techniques of the graphic arts are applied to data visualization in ways that draw the audience into the data in a meaningful and enlightening way, they work wonderfully. When they are used to decorate data and entertain people in a way that distracts them from or obscures the data, they work poorly.
By the way, I did not equate McCandless’ work to 3D pie charts. I referenced 3D pie charts as a by-product of the software industry’s perversion of data visualization (especially business intelligence).
The test of any data visualization, including infographics, is the outcome that it produces. Does the viewer walk away from the experience well informed? My concern with McCandless’ work is that it often does a poor job of informing. No doubt people are drawn to the pretty circles and curves, but were they well informed in the process? I love the work of graphic artists who manage to apply graphical beauty in a way that draws people into the data. People are drawn to candy for obvious reasons, but it fails to nourish the body. A finely crafted dish, however, produces both ecstasy and nourishment.
I’ll cease commenting now until Nathan, who began this discussion, responds. I’m still interested in hearing why Nathan characterizes my words as a “rant.”
Just a follow up – since I like your metaphor:
“People are drawn to candy for obvious reasons, but it fails to nourish the body. A finely crafted dish, however, produces both ecstasy and nourishment.”
McCandless may be too much candy. But you have to be careful on the other side too. A plate of kale might be healthy, but I’ll be damned if I’m going to sit down and eat it.
So if that’s our spectrum (kale to candy) I think some part of this argument comes down to where on that spectrum you’re comfortable. At the risk of being presumptuous – you lean toward being a kale guy (basing this purely on the work you highlight on your website which I hope to be a fair measure), and that is just fine. McCandless leans toward candy. Also just fine. I simply see them as appealing to different audiences.
But I suppose I disagree with your assertion that McCandless does a “poor job informing”. I think the net result is a positive flow of information. There could be more information flow, but it may be at the risk of turning to kale (in McCandless’ view).
Despite my plan to withhold further comment until Nathan responds, I feel compelled to respond to your thoughtful remarks. You are absolutely correct when you say that, according to the food metaphor that I used, my work leans more toward the kale part of the menu (though simmered in a simple but tasty miso broth, perhaps). This is true for two reasons: (1) I focus my work primarily on uses of data visualization by people who are naturally interested in the data, for they use it to inform better decisions. For this reason, I pursue clear, accurate, and information rich displays. (2) I have no formal training in the graphic arts. There are times when I would love to display information in ways that are more aesthetically appealing than my abilities enable. Fortunately, by following a few fundamental principles of graphical design, I am able to display data in a way that is pleasing to the eye. This, combined with designs that are fully and easily usable by human eyes and brains, I am able to support the level of engagement and nourishment that my audience requires.
Remember that this discussion stems from my recent blog about a Teradata event (a data warehousing/business intelligence vendor) that featured McCandless’ work as an approach that analytics ought to adopt. I warned that McCandless’ work does not apply to analytics and should not be adopted as a desirable model. I did not critique McCandless’ work in general as I have done previously. The discussion has gone in a different direction, opening the old form vs. function debate once again. The point that I’ve been trying to make is that form and function are not at odds with one another. People with McCandless’ training have a wonderful opportunity to display information in ways that can draw an indifferent audience into a rich interaction with the data, without sacrificing meaning, clarity, or accuracy. Some people with this training are doing this; McCandless is not. I would rather see people with a fine appreciation for aesthetics and an interest in the stories that live in data embrace better exemplars of beautiful information.
Hi dataviz companions,
We had a similar discussion at SEE+ a week ago with Moritz Stefaner, Andrew Vande Moere, Benjamin Wiederkehr and more. That discussion was about story telling vs. exploratory designs. Outcome was undecided ofcourse, but the topic sure enjoyed a heated discussion. Funny to see it here again.
This topic interests me because I’m a pretty hardcore functional, keep it simple guy, basic graphs and stuff. But I can’t ignore the huge flow of supercool looking (interactive) designs on the web. I have to say that the amount of really useful ones (give information, do not have to search for meaning, do not have to figure out how it works, etc.) is not that big. This ‘experimenting’ though will probably have a huge impact on innovation within this field.
In my view I think McCandless work has its role, it sure gets data visualization a lot of attention, it makes data look sexy. But the danger is that this sort of data visualization is seen as the new standard/example of data visualization as Stephen states what somewhat happened at the Teradata event. So it has its place, we know that. But does the rest of the world know this too? Probably not.
Sure certain parts or concepts can probably be used to get information across to professional users (keep experimenting!). But as Stephen states it has to be build on a foundation of visual perception knowledge and let’s not forget knowledge of (basic) statistics.
The sexy looking data visualization could draw attention of people who want to make sexy data stuff, but forget to look at ‘boring’ stuff like visual perception and statistics. This could lead to a pretty picture with a beautiful message, but wait a minute that is not the way to calculate the employment rate…….. (ok this is an actual example I witnessed)
The people who ultimately use the data visualisation to make decisions do (mostly) not know a thing of statistics and visual perception, they just make decisions based on a picture…..(can you see the murky scenario?).
The above has also a lot to do with for whom you are making the vizualisations. A lot of data visualizations on the market are made to inform the broader audience. As we all know data is as boring and tedious as it can get (personally not my opinion :) ). So visualizations let’s the average Joe get drawn into the data, which is a brilliant thing. Eye candy helps a lot to do this job. I still think the data has to be represented as accurate as possible, but eye candy has its role here.
The professional users of data already want the data, they need the data even if they don’t know it. By using functional, yet good designed data vizualisations the impact and use of the data gets multiplied by a factor x. They don’t need eye candy, they need good structured design to be able to make decisions as easy as possible.
Great debate started by Stephen Few. The simple/simpistic debate got me thinking: how would McAndless rework Charles Minard’s Napoleon 1812 graphic:
A somewhat related article by Wattenberg and Viegas on CNN today: How to make data look sexy: http://edition.cnn.com/2011/OPINION/04/19/sexy.data/
As Stephen already has pointed out that “McCandless’ work is certainly not designed for analytical purposes”, I’ll focus on his assertion of the “ineffective” “design choices”.
I am not aware of any proof that McCandless work is any worse than a more ‘effective’ representation, in terms of its real impact on a lay audience. Effectiveness, here, is only argued from the viewpoint of human cognitive and perceptual science. What is assumed is that users approach these infographics with high expectations, data-driven analytical questions, or highly detailed tasks in mind (e.g. “find the color for ‘mourning’ in Native Americans”), which must be solved as quickly as possible, and as accurately as possible. They don’t. And I bet a huge majority of people still prefer the circular diagram over the matrix depiction, regardless of not being able to figure out the color for mourning.
What we should do is learn why people actually prefer the less ‘effective’ infographic, and apply this knowledge to further the field (e.g. people prefer circular graphs). What we should not do is critiquing a talented designer because a panel seemingly frames his work incorrectly as having complex analytical value.
The scale between function and beauty is continuous, and yes McCandless work sits way more towards beauty, but it is perfect there, with the world’s best, considering all the intentions and purposes it was created for: to inform and entertain people.
It would be quite easy to prove that McCandless’ diagrams (to use Alberto Cairo’s term) do not communicate as effectively as visualizations/infographics that take human perception and cognition into account. I routinely demonstrate the differences in degree and speed of comprehension with examples in my courses. What is probably true is that if you only want to communicate a single simple message that could be stated with words in a short sentence, and you don’t care about accuracy or a richer understanding of the story contained in the data, then McCandless’ diagrams do the job.
Although my primary intention in the original blog piece that spawned this discussion was to point out that McCandless’ work is not an appropriate direction for analytics, it is quite appropriate to also critique his work for what it claims to do. I don’t think that McCandless’ work is considered to be among the “world’s best” of its kind. He describes his work in the following way on his website:
“I specialise in information design, data visualisation and infographics. I love taking all kinds of information – data, numbers, ideas, knowledge – and making them into images. When you visualise information in this way, you can start to see the patterns and connections that matter. Then I like to take it one step further – and design that visual information so that it tells a story, or conveys a message, or focusses only on the information that’s important or interesting.”
When comparing McCandless’ work to the “world’s best” examples of data visualization and infographics — even when limited to those that are designed to tell a story — I don’t believe that they don’t rise to the top. In my opinion, although his diagrams are eye-catching, they are rarely beautiful. What’s certain, not just my opinion, is that they communicate little (not many “patterns or connections can be seen”) and what they say they don’t say in a way that people can easily decode beyond a single point such as “Wow, that’s a lot” or “That’s really big.”
I’m not saying that McCandless’ work is without value. Clearly many people find it fascinating and it prompts useful thinking and discussion. What I’m saying is that, just because he’s receiving a lot of attention from the media right now, we shouldn’t assume that his work is an appropriate model for how data visualization and infographics ought to be done.
I personally do not believe it is fair to compare a general design philosophy with a few individual works. It would be better to contrast the explicit design rationale of a single piece, with its physical outcome. But regardless, let’s go for it!
What you call “they communicate little”, McCandless calls “focusses only [!] on the information that’s important or interesting”. It is his deliberate design choice to limit his infographics to a “simple” / “simplistic” core message, regardless of whether that is considered good practice by others. He actually is very successful doing it in this particular way. I think both your and his statements have a relatively similar meaning, but are seen through different lenses. Where your concern is to make a depiction as effective and efficient as possible, his concern is to create an iconic design that attracts as many viewers as possible, and get them to engage at least with one main data-driven message. This design rationale should answer your questions below about the circle and matrix metaphors as well.
I am sure you do not mean it in that way, but McCandless is not claiming in any way or form that his approach is the “appropriate model for how data visualization and infographics ought to be done”. Who actually does? Should we not blame the ignorance of those people, instead of criticizing his work?
I agree with your points Andrew that there is plenty of room for art based data projects that engage the audience. However, to the original point of the article, I feel a problem arises when companies like Teradata suggest that this is type of visualization is what’s missing from business intelligence and analytics.
What’s missing from BI is a deep understanding of what the end user needs to know and provision of tools that promote design to deliver that understanding. The BI vendors should be educating users about what value could be delivered, rather than focusing on the usual graphical tricks.
Then let’s not call McCandless’ work “infographics” or “visualizations” as they neither inform nor enlighten and are purposely difficult to read. Let’s call them “illustrations” and the debate will be over.
I think that Stephen Few is right when he makes the point that McCandless’ illustrations don’t work as analytical tools, and Andrew Vande Moere is right as well when he says that they should not be approached as aids to cognition, but as entertaining and light pieces whose only goal is to grab your attention towards a highly edited and simple handful of figures or facts. Similar to many illustrations at GOOD magazine (that some call also “infographics”, incorrectly, I believe).
This has been one of the more constructive discussions about this topic to date and the best part is that it’s unfiltered and there is actually a good mixture of comments (i.e. rather than a bunch of one-sided slams).
I think the best way approach this is not what is the proper way to visualize information, but how do people process it. And one place to look at is how we communicate with each other. We often speak using metaphors. “You are pushing my buttons” or Mike’s comment “You bath in your thoughts” are good examples. Obviously, we have no buttons to push and thoughts cannot be bathed in, but the usage of such words creates mental visuals that help us better understand the message being communicated. Sure, you can use purist words: “You are starting to frustrate me” and “You are arrogant” and the meaning would be there, but the metaphorical usage draws a deeper connection to the meaning. We have communicated like this since the dawn of man. Are these “misinformed” usages of words wrong? If you think so, have fun convincing the world to stop talking in metaphorical “lies”.
People prefer more visually stimulating graphics because our brains process images with far greater stimulation than they are by simple and familiar graphs. Our brains are capable of holding such images in our memory for far longer periods of time than just numeric values. And this is something research has proven. Instinctively, we are curious. We want to explore new things. I feel it can only be good to try to find new ways of exploring information. However this does not apply to BI. Trying to argue DM’s work from a BI perspective is trying to argue an orange from an apple’s perspective.
The method of visualization that you choose to use depends on many factors and to say that there are specific rules that must be applied before you even start is simply short-sighted. From everyone’s comments, I will say that nobody here is wrong. We all have our opinions on this topic. But one thing is for sure: Stephen is going to have his work cut out for himself in the future. The interest in new ways of visualizing information is swelling exponentially every year.
You seem to assume that I am not interested in new ways of visualization information. Nothing could be further from the truth. I spend a great deal of my time following research and development efforts to produce new, more effective means of data visualization. My own “bullet graph” was a new form of display that I created for dashboards to solve problems with the silly circular gauges that had become popular because vendors took the metaphor of the automobile dashboard too far.
Based on what I’ve seen, McCandless is not visualizing information in new ways. Every example that I’ve seen is based on existing methods. For the most part, he is using old methods that have been proven relatively ineffective. My concern is not with invention, but with ineffectiveness. I support experimentation, but believe the results of those efforts should be put to the test. Do they work? If so, I’ll promote them wholeheartedly, which I have done on those occasions when I encounter innovations that add real value.
I agree with you that metaphors can be quite powerful for communication. When metaphors are used in ways that help people connect with and better understand information, they work wonderfully. I actually don’t see McCandless taking much advantage of this. What is the metaphor of a bunch of circles that we are supposed to compare? What is the metaphor of a matrix of colors by meaning and culture, arranged in a circle rather than columns and rows so they can be scanned and compared?
show data variation
not design variation
If I may jump in here and provide an outsider perspective: I am not a studied designer but rather a semanticist, so I do have some insight into conveying meaning but the theoretic background is spotty with regard to visual communication.
Here is what I gather from this and similar discussions: Where design choices of information display are not strictly functionally motivated, that is wherever they do not tailor content in such a way that human pattern recognition can find the “story” in data sets it would miss in raw columns of numbers, the communicative power of data visualization is missed. These things are not infographics in a strict sense to many practitioners it seems.
Also, some disagreement arises out of the definition of “story.” If you would follow my reasoning that a story in itself is merely a pattern that the mind enjoys deciphering and that the term “story” is a rather loose frame for various patterns that have become culturally salient over time there might be some llway to find common ground perhaps? Finding the functional constraints in story patterns would place a wider tool set in the hands of information designers, so this surely an opportunity to find even better express highways into the human brain.
Story in this regard very much differs from decorative fluff. It is not a means to an end of making the reader more responsive to boring data. It is the essence of one meaning of the data. However, this mean to making the reader more responsive should be taken into account none the less!
In linguistics there is a long established tradition of analyzing several layers of meaning, speech act theory being just one example. Sometimes the meaning on those level is in conflict with each other – as are human actions: Do I want to berate somebody so I feel relieved I could vent my anger or do i want to persuade him to compensate me for his errors, swallowing my pride? Even if we want the latter, we oftentimes do the former.
The use of decoration might be merited after all! Not on the level of meaning that most faithfully depicts the data but rather on a level of meaning that does draw an audience to recognizing data who would otherwise not pick up the information at all. A social meaning, if you will, about being inviting or about “appealingness” with regard to cultural aesthetic preferences. Again, if you discover functional constraints for this it would empower you to make informed decisions rather than being dogmatic.
Then it just becomes a question of weighing those constraints for each design decision. Some tradeoffs might need to be made, but at least now there is a conscious decision behind weighing one part of meaning over the other.
I get a little sick in my mouth when I see how Venn Diagrams are abused in web “infographics” by people who obviously have no clue about set theory (at least that much you learn in semantics). And yet I have come to the realization that some bitter pills need to be swallowed, if only for you to learn from the experience. Incidentally I created an “infographic” about this when I realized that people love fast food. http://blog.jochmann.me/post/4205261648/not-an-infographic-change-of-heart
I agree that McCandless would respond to my statement that his diagrams tend to “communicate little” by saying that he “focuses only on the information that’s important or interesting.” My response to this is that he must not find much that’s important or interesting in the data, based on the resulting diagrams. My point is that he often goes too far in reducing the message, discarding much of the richness in the data that could have been shown to a broad audience in a readily accessible and thought-provoking way. There are certainly occasions when only a single, simple message from a richer story is all that should be presented, given a specific audience and its needs, but McCandless seems to believe that this is always the case. My other concern is that he takes an extremely simple message and makes it unnecessarily difficult to comprehend by choosing forms of display that are hard to perceive. My concern about his use of circles to encode quantitative values, which people cannot easily compare, when he could have used forms of display that are easy to compare (for example, the lengths of bars that extend from a common baseline), is not assuaged by his communication goals or “design rationale”.
When McCandless presents data in a particular way – when any of us who are perceived as experts show our work – we are in fact suggesting to the world that it is worthy of emulation. People trust us to point the way to practices that work. None of us are responsible for the misunderstandings of others about our work unless we encourage them, but we cannot shirk responsibility when people follow our lead (both explicit guidance and that provided merely by example) and fail as a consequence. McCandless promotes himself as an expert in information visualization and infographics. He is receiving a great deal of attention right now as a leader in the field. For this reason, he has a responsibility to do his best, which includes listening to, thoughtfully considering, and responding to the concerns of others. I too have this responsibility, and take it very seriously.
Beauty is very clearly in the eyes of the beholder.
But where are the beholders in this conversation? Do they want to be entertained? Informed? Inspired? Provoked? I would bet they don’t even want the same thing all the time.
Maybe we should be more focused on what our end user are really asking for and doing our work with that as a guide rather than telling them what they should have?
If we give our customers only what they know to ask for, we won’t effectively serve their needs. This is especially true when most of what they see is poorly designed. They need to see how much better it can be. This is how any field of endeavor progresses. Over time, the field matures as practitioners turn from what appeals superficially to what really works. This happened in Web design and it will happen in data visualization as well, but only if we keep our eyes on the goal and fight for it.
Agree we can’t just deliver what people want (ie. Ford’s example of a faster/mechanical horse). This is actually what I meant by using their desires as a guide.
Ignoring the needs and desires of of customers – the people who give turn our work into actions – and assuming that we with our views of correct analytical methods know better is, I think, a step in the wrong direction.
The people who are able to best able to surprise and delight their customers know what their customers want and then extend their world based on what they (often don’t know) they need.
Would it be different if McCandless would say: “I am an expert information visualization and infographics because I do know the research, and I know the principles. But I found that stepping away from these research findings and creating less effective visualizations results in more engaging pictures that are appreciated by a broader audience, so that will help get the message across”
If McCandless would say something like that, making deliberate choices, would that make a difference? Is it about creating ineffective graphics? Or is it about creating ineffective visualizations and claiming that they are? Is there any research on why ineffective visualizations apparently appeal to a larger audience?
It would certainly be interesting to hear McCandless say that he chooses to display information in less than optimal ways for a particular purpose, and then to explain how his designs actually serve that end effectively.
I’m not aware of any research offhand that specifically attempts to explain why some people (certainly not all) prefer forms of display that don’t effectively provide what they need from the information. What’s clear, however, is that in all walks of life people often prefer what doesn’t serve their best interests compared to other choices. As I mentioned previously, research has clearly shown that our choices are often irrational.
I do believe people who consider McCandless’ infographics just “art”, do not take him seriously. On his website there is an example of a redesign of a heart disease test report. Would you put “art” that catches your attention, but does not communicate the results clearly and easily in such report? If there is a place where effective communication and clearly displayed data is needed, surely a heart disease test report must be it.
My main problem with infographic as art is that it considers its readers dumb and not interested in the data or the story it tells; the reader needs some sugar-coated eye candy to even bother reading the article. It’s all part of the trend of de-intellectualizing in the media (and maybe the society as a whole).
You want something eye catching? Put in a strong photo, relevant to the case, next to your text. Or do a smart design of the layout or header of the article, which catches the interest of the reader and guides the eye to the relevant text. If you want to elaborate data, make a chart or inforgraphic if that yield a deeper or quicker understanding.
I wouldn’t claim to have a deep knowledge of Mr. McCandless’ work, but I’ve seen several of his graphics and scrolled through his blog from time to time. The graphics in question (which is actually interactive online) illustrates some of the common problems with McCandless’ work. First I have to spend time figuring what the graphic is trying to tell me. Then I need to let my eye go back and forth to the legend and try to remember what the different colors are coding. I see that some are really big peaks (like the swine flu), but since there is no scale on the y-axis I really can’t relate this to something. How big is big? The more or less useless info this graphic displays, is a timeline when the swine flu (and other fears) peaked in media. It does not correlate that with some interesting data, such as when was the first case/ death reported, when the first vaccine was administered, etc, etc. So where is the story? After studying the graphic for a while, I do believe it tries to convey the relationship between the number of deaths and the number of media mentions, since the numbers of deaths are given in brackets (which isn’t a good indicator of how “dangerous” each of the fears are, since not all of them are deadly, e.g. autism. But that’s another case). The way the reader can compare this is to look at the graphic and read the numbers, or switch between mentions and number of deaths as y-axis. Nether does tell the “story” very well, since they don’t correlate the data in a single display. The graphic is also 3D which makes it difficult to compare height of the different “fears“, but can be leveled in the interactive chart. But since this is a area plot, data in the back is hidden, e.g. it’s not possible to see Asteroid collisions from early 2007 to 2010.
In my opinion: The “infographic” above may work to catch the readers’ attention, but I do believe a photo of “fear” would be more effective. It does not display the data effectively and it does not tell the story very well at all, if the story has anything to do with how much media attention a specific fear gets compare to number of deaths or if it correlates to important events in the world (like the outbreak of swine flu, an asteroid passing the earth closely, etc, etc). In short, I find it to be a pretty weak outcome from all the work and effort that went into making the graphic.
It would have been nice if Mr. Few allowd Mr. McCandless had the opportunity to share his point of view in advance.
Why this discussion without or any contact with the creator (MrCanless).
This is not very effective i.m.h.o.
We would all benefit from McCandless’ involvement in this discussion. Just as I jumped into this discussion of my own volition in response to Nathan’s original comments, McCandless is welcome to join in as well. McCandless was supposed to participate in the recent Malofiej 19 conference in Spain with me and several others, but pulled out. I was hoping that we would have an opportunity to become acquainted and discuss these issues there. Face to face discussions are always more productive, but not always possible.
One thing is clear: Stephen and David should collaborate on a project, ideally one in the public interest, like the health chart example. What say you Stephen? (I’ll email David who I believe is on holiday, which might explain his absence from this discussion).
I doubt that a collaboration is in our future, but I’d certainly welcome an opportunity to share my concerns with him directly and hear his perspective firsthand.
The conversation here and on your website has been constructive – so kudos for continuing it.
I think there’s a nuance…an “x factor” that you’re not fully acknowledging in McCandless’s work. Everything you say about accuracy, and providing more information in an equally attractive package is absolutely true. His designs do not always convey information well, and they may even detract from the information being presented.
Nonetheless – in the PDF you linked to in your latest comment on your website (http://www.perceptualedge.com/blog/?p=935#comment-212760), you take issue with McCandless’s “colors in culture” chart. I went to his website so I could see it in it’s intended form (http://www.informationisbeautiful.net/visualizations/colours-in-cultures/) , and guess what? I just spent 15 minutes looking at it. Yes – the first 3 minutes were spent decoding it – trying to understand what it was showing. But the next 12 minutes were spent exploring. That circular chart is a horrible way to present that information in a lot of ways. But I still stared at it – found a pattern or two – compared a few things – stepped back and thought “it just looks cool” – got close again and stared at it. I then went to your reinterpretation in the PDF. And yes, I could “find” an item much, much faster. But, though I think I gave it a fair chance, I lost interest after about a minute. The data is there, it’s easier to decode, but it’s not interesting. (You may argue that the *data itself* is not interesting, but that’s a different point.)
“Time needed to decode” is one metric for a graphic, but it is not necessarily the most important metric. If a piece of information takes 2 seconds to communicate, great – you’ve given me the information and I’m on my way. But you haven’t made me stop and think. You haven’t made me turn my head sideways (yes!) and contemplate a new relationship I wasn’t aware of. I want to be stopped in my tracks by something compelling. Make me think – make me find the associations – then, and only then, will I remember them and integrate them into my broader thinking. It turns out, I don’t want to be told, I want to discover.
You’re working very hard to justify a dysfunctional display. You admit that it is difficult to get useful information from McCandless’ circular arrangement of the information, yet you prefer it. Why? Because you find circles more engaging than rectangles? In my world, people long for information. They want the form of a data display to support its optimal use. The form is simply a delivery mechanism, which should recede into the background, as we are drawn into the data. What you’re saying, essentially, is that for you, form trumps function and content.
If your goal is to discover, not to be told, then McCandless’ displays are definitely not for you. They say little, and are usually designed to make a specific statement, not for exploration and analysis. Arguing that McCandless’ circular display of culture’s colors better supports the process of discovery than my matrix of columns and rows suggests that you prefer to explore with your feet in shackles and blinders on your eyes. Just think how much more successful you could be if you overcame your preference for circles.
With that, I think we shall agree to disagree – you’ve taken a natural human response (shared by many) and referred to it as “shackles and blinders”. Perhaps this should trigger some introspection on your part?
I’ve agreed with all of your objective points. It’s the recognition of the subjective where we diverge. In my experience, whether we like it or not, subjective, emotional response trumps the objective almost all of the time. If you can’t capture my imagination, nothing else you have to say matters. But if you have grabbed me by the shoulders and shaken me first (metaphorically…), then I will forgive a lot of indiscretions in the rest of the conversation.
In my world, people long for experiences.
Further, you say: “The form is simply a delivery mechanism, which should recede into the background..” I couldn’t disagree more!
The form is your opportunity.
I was the developer working with David on the Snakeoil? interactive vis and have found this conversation very interesting, I can agree with points on both sides of the debate, but I have to say you have totally lost me here Stephen…
You seem to be ignoring the fact that you are basing ‘success’ on a different metric to other people regardless of how many people say it or the different reasons given. You are disagreeing with people over their opinion, not facts.
I could probably forgive that as I do think it’s coming from a position of genuine passion for the topic, but the tone of this response has put me right off. I can’t remember the last time I read something as blatantly condescending as your last sentence here.
Andy, while shackles and blinders may be a bit strong, question for you – which one is more popular, Green Tea or Folic Acid? They’re both circles, and both appear to be about the same size, but when I go to the spreadsheet, Green Tea has a popularity=26.1, Folic Acid has a popularity = 10.5? My initial point was going to be how it’s hard to tell *small* differences in circle areas, but wow.
I am not ignoring the fact that you must certainly define success in data visualization differently than I do. I define it as practitioners in the field have defined it since the early work of William Playfair over 200 years ago. A data visualization is successful to the degree that it informs. The better, more clearly and accurately it helps people understand truths that reside in the data, the more successful it is. These criteria for assessing a data visualization’s effectiveness are more than opinion, they are a fundamental assumption that has been applied to data visualization historically. If you define success in a significantly different way, perhaps you should call what you’re doing by a different name. If you called it something else – perhaps data art – then I and others who have worked hard to promote and advance data visualization would not critique what you’re doing. I welcome new ways of expressing data visually that inform as well or better than the methods that have been developed over years through careful study. I do not welcome methods that reintroduce mistakes that were abandoned long ago.
Just few words expressing my opinion, which may not add anything really new. I read most of the messages coming from experts and people who I truly admire. I come from the analytic part, specifically from the business intelligence world, so I started studying data visualizations as a real need for my job. Therefore, I always look for more, not for a single message delivered in a well designed interface. I am sorry, but for me, this is not information visualization, I can hardly imagine how you are able (in case you are) to figure out a single story coming form that type of visualizations. I believe the D.McCandless’s job could be placed in the infographic world, which I (sorry if anyone feels bothered) think is really far from the analytic visualization world in being able to ask questions, find patterns, understand the variables and hidden links. Under my view, D. McCandless chooses right the aesthetics (basically geometry and color) and the topics he covers. Last but not least, I think he found somehow a way to connect with people delivering very simple messages using drawing… and here comes the golden key, he avoids people to “analyze” a chart, is far more easy to interpret a figure of a tomato big/small than to interpret a bar, line etc… (although I am not sure about this, but I think people strongly believe in this principle). The first time I saw D.McCandless job (at TED) I felt sad because he was presenting something wich was in the opposite way of what I’ve been studying (and believing) the last five years, that means (among others) the work done by Edward Tufte, Stephen Few and Jacques Bertin. Enrico Bertini recently posted asking about scientific studies demonstrating the power of information visualization. I think that up to know, there is no enough scientific to prove and defend the principles on which we believe and apply to our day to day job. Why don’t we try to perform a scientific study and have strong arguments to defend/sell our ideas?
Call me naif or whatever, but i will always prefer any chart done by hand by Bertin in the late 60’s than one done by McCandless using Adobe/whatever.
I don’t mean to be pedantic, but I feel that I would be remiss if I didn’t question your reasoning. Desires, preferences, and inclinations that seem natural are not necessarily beneficial. The natural inclinations of people often do themselves and others harm. This is one of the reasons that we have a system of laws that define harmful behaviors to curb natural appetites when they threaten the good of society. Also, because a natural desire, preference, or inclination is useful in some ways doesn’t mean that it is useful in all ways. I love circles. I find the symmetry and containment pleasing. I have learned, however, that circles do not serve all purposes well. Research has clearly demonstrated that they rarely encode data values in an effective way, so I avoid using them in data visualizations except in those circumstances when they can do the job.
You assume that when I say that form serves content in data displays intended for exploration, analysis, or communication, I don’t sufficiently appreciate form. This is far from the truth. I appreciate form for its own sake in works of art. When the purpose is to help people understand information, however, I attempt to use both form and content in a way that enables understanding. I choose the content that is needed to support this goal and present it in a form that best supports the clarity, accuracy, accessibility, and context that are needed to produce understanding of the truth contained in that content. Form is indeed an opportunity, and I strive to use it well.
You also seem to assume that I insufficiently appreciate human emotion. This too is not the case. I know that facts alone are rarely persuasive in and of themselves. I teach this in my work. People’s emotions can be engaged in ways that open them to the facts, however, without obscuring the facts. This is the challenge that we face when using data visualizations to promote enlightenment and change. How can we touch the heart without disrespecting the mind or misleading it? This isn’t easy, but it is nevertheless the goal for which we should strive.
Do you think David’s design could be improved by making it interactive? Using an example from your critique in “Our Fascination with All Things Circular”, what if you could select the option to only highlight the colors within the wheel and the two columns of text descriptors that corresponded to Native Americans? From your test to find the Native American color for “Mourning” a viewer would quickly be able to discern that this color/text descriptor match does not exist for Native Americans. It would be similarly easy using this method to solve your other test to find the color with more meanings than any other for African cultures. Additionally an enhancement could be made to reverse this interactivity to select only text descriptors of a certain type, such as only mourning, revealing all cultures that have colors for mourning. Taken further interactivity could be added to allow such selections for color.
An interactive display with the functions that you described would certainly make the information more useful, but it shouldn’t be necessary to use include such interactions to overcome problems that could be easily solved through better design. Useful interactions could be enabled in my re-design of this information also, but would only be needed to enhance comprehension and efficiency in ways that could not be addressed by a static display alone.
I need to correct an error in my description of David McCandless’ background, which was based on an assumption that turns out to be incorrect. McCandless does not have a background in design. Apparently he has worked for most of his professional life primarily as a programmer. This clarification explains a lot. McCandless has probably never studied human perception or cognition, which is not a surprise given the typical failures of his designs. What has always puzzled me about his work, however, is how that, even from a graphics design perspective, his visualizations are often not particularly pleasing to the eye. For example, his color choices often seem arbitrary and not particularly well matched. I now understand why.
His work as a visual designer is recent. He has much to learn. In the meantime, however, he has been popularized as an data visualization expert, which is where the problem lies. His diagrams should not be seen as exemplars of data visualization, but as the learning exercises of a relative novice. While being promoted as an expert, however, will he take the time to develop the skills that he lacks, or will he spend all of his time producing more of the same and presenting it to the world? For his sake and the sake of the world that’s influenced by his work, I hope for the former.
I need to correct an error in my description of Stephen Few’s background, which was based on an assumption that turns out to be incorrect. Few does not have a background in art. Apparently he has worked for most of his professional life primarily as a business intelligence consultant. This clarification explains a lot. Few has probably never studied psychology or art theory, which is not a surprise given the typical failures of his designs. What has always puzzled me about his work, however, is how that, even from a cognitive and perceptual perspective, his visualizations are often not particularly pleasing to the eye. For example, his color choices often seem only scientifically motivated and do not particularly well match the appeal of the masses. I now understand why.
His work as a business graphics and information dashboard expert is well established. However, he has still much to learn. In the meantime, however, he tries to criticize popular and artistic visualization, which is where the problem lies. His diagrams should not be seen as exemplars of visualizations that provide joy or encourage interest, but as optimization exercises of a person who puts everything in function of effectiveness. While being promoted as a well-rounded expert, however, will he take the time to develop the skills that he lacks, or will he spend all of his time producing more of the same and presenting it to the world? For his sake and the sake of the world that’s influenced by his work, I hope for the former.
Few’s graphics may not be “artistic” (whatever that means) but they are functional, they respect cognitive rules and constraints (to the extent that there is research available), and they are suited for the task they are intended to fulfill, which is to gain insight when analyzing data sets. And they are beautiful in an elegant, very restrained, way. Sure, I agree, they are not simplistic eye-candy, or wow-inducing in a primary, emotional level. There’s a reason for that: they are tailored for specific audiences that don’t need to be “engaged” by bells and whistles.
As I understand this conversarion so far, Few is not critical with MacCandless’ work because it is artistic. He criticizes his projects because they are not presented and sold as nice-looking illustrations (some of them are), but as data visualizations that allow you to interpret and accurately explore data (they are not, for sure).
On a side note, working in a news organization, I can tell you that we can learn much more from Few’s books than from treaties on “art theory” which, as far as I have read (I am being unfair here, so let’s say that there are exceptions), are funnily useless rethorical mumbo-jumbo.
I’m always wary of people who comment on blogs without identifying themselves. I suspect that you are withholding your identity for a reason.
You are absolutely right when you say that I have much to learn. Beware of anyone who believes otherwise.
Rather than trying to turn my description of McCandless’ against me — mere wordplay — why not address the issues instead? If you wish to defend McCandless’ work or critique mine, attempt to do so with actual evidence and reason. You might also want to get all of your facts straight, especially about my background and studies.
And I am always wary of people to spend an exhaustive amount of time defending themselves.
Whoever wrote that comment: well done. Should you ever identify yourself, you have a beer waiting for you. Stephen, you had it coming.
This entire blog post forum debacle is not just about your expertise vs. McCandless’ work. You have attacked others work too, including mine. Frankly, I couldn’t care less about your opinion on our work. I think you have a good mind for how to display data in a functional sense and there is some definite value in that (as I’ve always said). However, there are more ways to tell that story and it’s apparent that you are hell-bent on refusing this. I find your work about as exhausting as reading your posts here and I’m happy that my clients ask me to build engaging visual stories and that they understand the benefit of our work.
The controversy and discourse surrounding innovation in data visualization is great, but your attitude is quite dismissive and arrogant in your blog posts as well as here. You try to encourage discourse the same way someone who is trying to make you worship Jesus invites a discussion (“Prove to me that Jesus does not exists. Oh, you can’t? Oh, well I must be right.”)
Your claims are backed up mostly by your opinion rather than research. And you seem unwilling to see some of the research out there that goes against what you are saying. Like this: “Useful Junk? The Effects of Visual Embellishment on Comprehension and Memorability of Charts” http://hci.usask.ca/publications/view.php?id=173
As I’ve said before, your work is not “wrong” and we often build visuals that would follow your philosophy. However, being able to captivate a greater audience with a visual story has immense value as well and I enjoy finding ways to visualize complex relationships that an x- and y-axis cannot show us. And people will disagree with me, including you, and I’m totally fine with that. It’s not going to stop me though.
This debate has been going on for some time and I seriously doubt it will end anytime soon. It would be great to have this topic as a panel discussion at a conference that caters to both worlds (like Strata).
I agree wholeheartedly that this isn’t about my work vs. McCandless’. It is about using data visualization to better understand the truth that lives in information so we can use that knowledge to make the world a better place. Like you, I too am wary of people who are constantly defending themselves. Read my comments again to assess if that is what I’ve done. What you’ll find, if you’re open and honest, is that I have consistently promoted data visualization best practices that have emerged from a large body of research and have been honed through years of experience helping real people use data more effectively. When my colleague Bryan Pierce of Perceptual Edge critiqued your “2009 US Federal Contract Spending” diagram in my blog (http://www.perceptualedge.com/blog/?p=799) and you responded at length, were your defending yourself or advocating what you believe to be true? I’ll assume the latter, but I could easily claim that you “protest too much.”
Asserting that I ignore relevant research when it suits me by citing a single study that you believe conflicts with my work is not good argument. I am quite familiar with the study by Scott Bateman, et. al., that you cited. I have corresponded with Scott, who was kind enough to send me the data and other materials that were missing from his published paper so that I could examine it thoroughly. I spent most of today working on my next newsletter article in which I will report my findings regarding this research in great detail. The valid findings of this study do not conflict with my work in the least, as I’ll explain, nor are they surprising.
You say that I discourage discourse by being dismissive and arrogant. If I believed this to be true, I would feel horrible, because such behavior would undermine what I’m trying to accomplish. In fact, I take great care to encourage constructive discourse. I don’t critique work lightly, either negatively or positively. When you wrote comments in this blog about my work previously on April 19th, I took the time to respond thoughtfully and ask questions. I was neither arrogant nor dismissive. You did not respond in kind, however. Why was this, if you wish to encourage discourse?
Interactive adaptation of David McCandless’ original circular design graphic:
Interactive adaptation of the grid view from Stephen Fews’ original article:
I have to say, I for one would be interested in any information coming out of a Few/McCandless collaboration, if only to see how (or if) any viewpoints between the two of you were to change.
My take on this is simple (and probably simplistic): when I look at Few’s work, it helps me to do *my own* analysis of the data. When I look at McCandless’ work, I see what he wants me to see, but have to work to see what *I* want to see.
I do not think that there should be some sort of rivalry or “choosing of sides” or dismissing of any of the people in this thread, but that the discussion should continue and we should work to evolve our presentation of data in a way that is both useful and beautiful.
this is a great discussion and much needed. i’d like to add my thoughts and hopefully contribute something useful. there hasn’t really been any proper mention of audience – those on the receiving end of the visuals – or the appropriateness of visual interpretation of data for a specific audience. for the most part the trend for so called ‘infographics’ has taken place in the mass media, where people are not prepared to engage for very long, nor are they prepared to work too hard to extract meaning – if they are even interested in meaning. it’s an audience which mostly wants to consume, and quickly. if a visual is too complex many will not even engage. so what may work in a focused, professional analysis may not work in a newspaper article.
people are by their nature irrational. and so, if in a fast moving consumer context you present them with highly complex images needing a lot of decoding, they are unlikely to engage. this is exactly why David McCandless’ work is so very popular. it reduces things to simple shapes and catchy colours, precisely like candy. ‘eye candy’ is the perfect term for what he produces. what Stephen Few is getting wound up about is partly the lack of respect for the accuracy of the information being expressed, but mostly i suspect for the fact that it places style so far above content to the extent that meaning is sacrificed, as does much work which calls itself ‘infographics’. it’s all about how good it looks and not so much about what it’s telling us.
responsibility lies with those of us who produce graphic interpretations of information to make that information clear and accessible. however, we also have a responsibility to make it attractive to gain the interest of the audience. effectively striking that balance is what we should be striving toward, with respect to context and audience.
We should leave “playing doctor” to the children.
In considering this great debate, perhaps we should step back and consider another field for a moment, medicine. For centuries, medicine was guided by wishes, fantasy and misguided ideas of what would heal people. One of my favorite examples is “trephining” (drilling holes in your head) to release the evil spirits that have made the patient ill. Of course, for a very small percent of patients, this proved helpful. However, most ended up no better and typically much worse for their procedure.
I feel that McCandless work is “fun” and vibrant, but also misguided if new understanding and insight is the expected outcome. There is actual science and research behind how people perceive and read visuals. In my experience, Stephen has an extremely solid grasp on this body of work. He has even added to this body of work with his own invaluable contributions to the field. His contribution, bullet charts, are consistently a big hit with many of my Tableau training attendees.
I think we should ask whether we are going to “play doctor” or actually try to heal the patients? Do we seek to make art or is our primary goal to inform people about the state of the world around them? Also, do we consider that people’s time and attention spans are valuable and limited? Are we so vain to choose that aesthetics trumps the key information in our data when valuable questions are at hand?
While I don’t think it is wrong to add a small amount of fun to any story, my first-hand experience with many executives in business and government is that there is a yearning for information that will make their decisions better informed. Most decision-makers want to grow revenues, increase profits, save lives or make their job easier. This all points to a need for data doctors who harness data to quickly and clearly inform. We should leave playing doctor to the children.
Faculty- American Marketing Association
Principal Analyst, Freakalytics, LLC