What is the ultimate goal of data visualization? A recent post on Jan Willem Tulp’s blog outlines some of the controversies in how, and why, you communicate data visually. Writing about the Dutch InfoGraphics Conference 2011:
The keynote was presented by Gert K. Nielsen, the founder of VisualJournalism.com. Though he is a great speaker and had some valid points, I also disagreed with many of his views. His opinion was that most infographics and data visualizations actually tell you nothing, give no information and remove the truth and emotion from reality (He illustrated this with ‘bad’ examples on visualcomplexity.com, including my World Economic Forum visualization 🙂 ) He wanted to make his point by showing movies of people committing suicide, people being blown up by bombs etc., and then showing an infographic that only shows an explosion symbol on a map as a representation of these events. I agree that over simplification may not be right, but it really depends on what you are trying to communicate, to what audience, and with what purpose. So, although interesting, I also thought his views were actually to simplistic. (see the full post here)
Nielson recently posted a somewhat cynical critique of Moviebarcodes, a one-man project that processes the dominant colors of movies frame by frame and then presents them side by side like a color-coded barcode.
(Bambi, 1942. One of my favorite movies)
It’s kind of neat looking, and maybe would be cooler if it was not marketed as an analytic tool for film analysis (it is a dark film because it is mostly shot in dark colors, e.g. V for Vendetta , versus a more surreal movie like Amelie).
(V for Vendetta, 2006)
(Le Fabuleux destin d’Amélie Poulain, 2001)
Beyond its limited uses, however, Nielson makes a more general point that I think is quite apt. He notes in criticizing Moviebarcodes that the general trend in data visualization today is ‘Complex phenomemon -> Beautiful pattern.’ To him, the problem is not the images can convey information efficiently but (as Edward Tufte likes to argue), that they can tell a story.
Nielson also goes after Jan Willem Tulp’s visualization of linkages between issues and contries during the World Economic Forum:
Here I think he is a little off. Going back to my post on hierarchical edge bundles (a similar idea seems to have been employed by employed by Tulp), I think that there is a good justification for compressing information through visualization when the situation is right; here, given a large amount of survey data on a complex subject with many linkages. This is further emphasized by the interactive part of the graphic–which I suggest you check out–that shows the individual linkages between issues.
This actually gets to the main agreement I have with Nielsen’s argument, namely that infographics sometimes fail at conveying emotional impact. Although I think that infographics can convey scale, which does have emotional value:
they are best at quantifying something that otherwise would exist on a more visceral level. The problem as I see it here is more structural or even philosophical; it is that many of us working with data visualization, knowledge mining, etc. tend to see data and the display of information as inherently transformative in itself. We often see data as powerful because it displays truth, and truth carries alot of weight. Being able to authoratitively make a claim to knowledge is a powerful tool.
And sometimes that claim and the mere presentation of data is in fact transformative (see my post on W.E.B Du Bois infographics). However, I think sometimes we put a little too much faith in the power of data. Without fudging the numbers we can manipulate it to say what we want as easily as we can plug it in to a statistical program, as easily as we simplify it in order to send a message to the viewer. Beyond that, though, it still has to be used, and that is where things get complicated. What do we do with data? Often it goes into journals where good visualization doesn’t really accomplish anything. Visualization methods are important, but more or less get us nowhere in terms of having an effect on society. Where should our data visualizations go? To the government; to academics, or the internet? Where does it do the most work?
Maybe this is the real issue that Nielsen is pointing to. We have yet to resolve the paradox of what to do with, and whom to show, the vast amounts of information we now have access to. Obviously different audiences have different needs (the visceral/emotional vs quantitative dicotomy that Nielsen suggests), but it is hard to determine exactly what fits the audience best and what those needs actually are. I think many graphic designers and academics (and those who fall in between) are grappling with that now.
And this is a good thing. The sooner we can get a better grasp on where to put our data, the more power it can have to do good.
- Communicating Through Infographics (noupe.com)
- AAAS Visualization Challenge (seeingcomplexity.wordpress.com)
- Visualization vs. data mining (seeingcomplexity.wordpress.com)
- 3 Views on the Difference Between a Data Visualization and an Infographic (readwriteweb.com)
- Video Scribing, Infographics and Data Visualization (capturetheconversation.com)
- Data Visualization References (dashboardspy.wordpress.com)