March
23
2009
Recently, Tableau published a well-meaning blog post to highlight some of the inherent problems with geography-based visualizations under their tongue-in-cheek “Viz Police” heading. They take issue with a recent visualization published by Media Cloud, a Harvard Law project, showing how various news outlets cover various countries around the globe. The interactive graphic allows you to choose up to three news organizations and then 3 different data sets to compare (top 10 search terms, top 10 term pivot and world map – the visualization Tableau chooses to discuss).
I don’t necessarily disagree with Tableau’s argument, but I think they made several errors in how they chose to communicate it.
Error #1: Bad Blogging Etiquette: The post provides no link to the Media Cloud project and the specific item under discussion. There is no native way for the reader to go back to Media Cloud and investigate the visualization on their own. I wasn’t familiar with Media Cloud so I actually had to Google it to get there.
Error #2: Poor Graphic Use: Tableau chose to use just a thumbnail (the same thumbnail that is provided by Media Cloud) of the infographic. Furthermore, they covered it up with their “Viz Police” badge making it impossible to get a decent view of the graphic. Finally, the way they incorporated their badge into the Media Cloud graphic (it looks like someone screen-shot a layered graphic out of Photoshop or similar) presupposes the bad nature of the graphic. In other words, poor execution of including the badge on the Media Cloud graphic gives the reader the, possibly false, impression that the map is a bad graphic.
Error #3: Lack of a Full-Size Graphic: Tableau did not provide a full-sized version of the Media Cloud graphic. Now, I run hi-res (1928×1208) so I’d argue that the original graphic is too small anyway. But, when you look at the full-sized graphic sans “Viz Police” badge, the errors are not quite as egregious as indicated by Tableau. In the full-sized graphic the Area-bias still exists, but it’s clear that the UK is more saturated than the U.S. on the BBC graphic – when you spend some time looking at it.
Error #4: Misdirection. In attempting to show how Tableau’s solution (circles vs. density) is better, they bring in a completely different data set – “Net Internal Migration by State”. Now Media Cloud does not provide the data behind their graphic so if you wanted to create a comparative graphic in another tool you’d presumably have to jump through some hoops to either get them to provide the data or to estimate the data, but in either case you are not comparing apples and steel ingots ( apples & oranges are, in fact, too similar for the old adage to work) as Tableau is asking you to do in their post.
Error #5: Using area to encode value. In an error similar to the map-density one they are arguing against, Tabeau’s example uses the area of the circles to encode some value – which is not even explained via a legend (the legend only explains the color encoding)! For those that may not know, we humans are not good at estimating area, it’s not what our visual systems are built to do. We tend to over-estimate large areas and underestimate small areas – remember, this is the basic argument against pie charts.
Error #6: Chart Junk. At best, chart junk obfuscates your data making it difficult to understand. At worst, it causes bias or error in judgment of the data. Well, in the Tableau map, the circles have a light-colored border. This border is more evident on some of the plot points than others, creating the misrepresentation that those points are somehow more important. Is the migration to Maine somehow more important than the migration to Minnesota? I don’t really know because they are roughly the same size and color BUT the border on the Maine circle is much clearer than the one on Minnesota – what does that mean?
Error #7: Breaking map conventions. I can’t speak for the rest of the world, but here in the U.S. a circle on a map generally means a population center – a city – and the size of that circle may indicate how big the city is, or all circles are the same size (e.g. no value encoded on the area). So, when I’m looking at a map like this I/we expect the circles to reference a city and these circles do not, they reference a state – Tableau has just broken your mental model of a map! When you use a convention unconventionally and break the standard mental model you typically end up creating cognitive dissonance. I’m not saying that it should never be done, but you have to be very careful. If the confusion throws something into sharp relief that might otherwise be obscured, ok you’ve got a case to do it, but if all it does is create a buzzing between the ears that makes processing the information more difficult you are better off not doing it.
So what? Why am I all in a huff? It’s not because I dislike Tableau – quite the opposite, I am an avid user. I do dislike poorly executed arguments. If the argument is not made cogently, it has holes in it. It looks sloppy and therefore is less effective. Tableau has an excellent point about the pitfalls of area-based information graphics but they’ve shot themselves in the foot with how they argue it and that makes it less likely their readers will understand and trust the argument which well might lead them to not using the learning in their design efforts.
To be honest, I find the whole argument a bit disingenuous. The post argues against a specific type of area encoding – density encoding on geographic areas but Tableau not only allows area encoding on plot types up to and including the ignoble pie chart but their geographic visualizations allow density encoding via the data layers.
BTW, this is a follow-on to the comment I posted on Tableau’s blog. I wasn’t particularly happy with my comment so I rewrote it as a post here rather than editing the comment there.
Source: Media Cloud A Harvard Law | Berkman Center Project
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Source: Media Cloud a Harvard Law | Berkman Center project
Source: Tableau
Tags: geographic, Tableau, visualization, viz-police
I agree with your points, except for your reasoning in error #7. In your example link to Google Maps, I could argue that Tableau is sizing the circle marks very differently then the dots for cities in Maps. Unfortunately, the Tableau example was not well supportive of its case.
From personal experience, I have found that using country boundary polygons misrepresents the underlying data because of the area displayed. Cartograms are better with the area issue, but warps the boundaries excessively. I find that Tableau’s method of centering a sized mark of the center of a boundary area a wise compromise.
Also, one cannot see the true power of the Tableau viz without opening it in at least a reader; a screen capture of a Tableau viz is the tip of an iceberg. I am talking about the tool-tips that pop-up on hover, the selecting and drilling down into data, advanced filtering options, and so on. A Tableau viz is not a picture to only look at, but a data viz to interact and have a conversation with.
Sorry, I may have gotten off topic, but I too feel the “Viz Police” missed the mark on all the errors you pointed out and more.
Joe, thanks for adding to the conversation. Perhaps I wasn’t clear about my point in #7. The size of the dots in Google maps, true to the map model, are all the same size. In other words, they don’t encode any information in size of the dot, only the coordinates.
Any bounded area suffers from the area bias problem so I agree with you there. Cartograms are actually an excellent example of breaking the rules on purpose. The mental model of the map is broken in a specific way so that the new area is representative of the data more than the geographic boundaries in play.
I wouldn’t mind the dots so much (generally or specifically in the case of their blog post) if they did not encode data on the size and leave out the legend that explains what it is – poor form.
And yes, Tableau in static does not show how powerful a tool it really is.
Hear, hear. I absolutely love Tableau and think their blog has been consistently intelligent and well-reasoned. Which made the article you refer to all the more of a shock. I’d not have been bothered if it had appeared on a poor-quality blog, but this was way below their normal standard.
[...] Policing the Viz Police ยป Instant Cognition (tags: blogging advices) [...]
Clint, thanks for your comments here and on our blog. I’m sorry you found the argument poor. Some of your points are very valid, and on some I take exception. Here’s my reply:
1. No link to site: Very fair, and an honest mistake. I always try to link out to the source (you’ll see this throughout the Tableau blog) and in this case thought I had linked the image. But I had not. This is now fixed in the original post.
2. I used the image that was on their site, and covered up the parts that did not pertain to the argument. Since I was focusing on the BBC, I made sure to keep that clear. But placing the viz police logo on their graphic was out of line.
3. The largest graphic I could find even when I clicked into their site was 370 x 190 pixels, so there’s not much larger to go. And yes, you can see the color difference if you stare long at the graphic, but isn’t the point to communicate quickly and effectively without struggling with the data?
4. Re using a different data set: I couldn’t get the original data from the site, so I used a representative sample of one of our graphs. Re-creating the original data set would have been extremely error-prone so I chose to use a different set altogether.
5. While humans do have trouble comparing areas, I don’t quite agree that using areas for measurements is categorically bad. On maps, it can be especially useful. When all areas are relative to a common reference point, as in the circles, they are representative of the data. When they are relative to different quantities that are not being compared, such as the areas of countries on a map, they distort the data. In this example we double-encoded the information with color and size, and focused on the color with the legend. But your point is valid: we could have left size off altogether.
6. The border on the points is unobtrusive and is also consistent across all the points, so in my view it’s not chartjunk. Chartjunk is giant Santa clipped into a viz of Christmas gifts. But this point might be a matter of taste.
7. Again I must disagree- circles on a map, if encoded in color, can represent data well. The consistent placement of these in the center of each state, their size and color don’t lead me to believe they’re cities. And as I argued above, by making each data point relative to a common scale, it’s easier to compare the data.
In any case, thanks for reading and for policing the viz police. We do want to have a great blog that highlights good visual design, so it’s fair to call us on it when we fall short.
Best,
Ellie
Hey Ellie!
Thanks for getting back to me on this.
I don’t want to get into a heated discussion because I think we may be at an impasse.
I’d rather have our collective readers take up the debate and tell us which positions are more correct or incorrect.
(I’d REALLY love to have Stephen Few give his thoughts!)
That being said let me offer a couple facts and an concession.
#1. The thumbnail graphic for the Media Cloud (according to my handy-dandy Developer plugin in Firefox) is about 200W x 300H pixels for an area of 60K pixels. The original graphic (which you have to screenshot out of the webpage) is roughly 370W x 657H pixels for an area 243K pixels – that’s more than 4 times the size of the thumbnail.
#2. Stephen Few has this to say about chart junk, “…a term coined by Edward Tufte to describe visual content in an information display that serves only as decoration.” (“Information Dashboard Design” by Stephen Few, (c) 2006, p.185) And Tufte’s longer diatribe, “The interior decoration of graphics generate a lot of ink that does not tell the viewer anything new. The purpose of decoration varies — to make the graphic appear more scientific and precise, to enliven the display, to give the designer an opportunity to exercise artistic skills. Regardless of its cause, it is all non-data-ink or redundant-data-ink and it is often chart junk.” (“The Visual Display of Quantitative Information” 2nd Ed. Edward Tufte, (c) 2001, p.107) Some more info is available at Wikipedia.
I could concede on the area of the circles if your graphic provided the reference point. In other words, If I am judging the size of the circles in relationship to a standard reference (a la the standard kilogram) then ok, but since your graphic does not include the legend for size, there is no standard reference to judge the encoded areas against.