In celebration of Barack Obama’s 100th day as the 44th President of the United States, the MIT SENSEable City Lab visualized mobile phone activity during the historic inauguration. What we see is a sense of the worldwide celebration and when and where people traveled to Washington, D.C. to get to the event. They call it Obama | One People.
For President Obama’s 100th day in office, the MIT SENSEable City Lab has created visualizations of mobile phone call activity that characterize the inaugural crowd and answer the questions: Who was in Washington, D.C. for President Obama’s Inauguration Day? When did they arrive, where did they go, and how long did they stay? The results of our advanced data analyses are presented in two dazzling visualizations that celebrate Barack Obama and the people who supported him from all over the U.S. and the world.
In the first of a set of two, mobile activity for the city was visualized. Each square represents changes in call activity in an area of 150 x 150 meters around the Mall and Pennsylvania Avenue; the charts on the left show activity by state; and on the bottom is a timeline for activity leading up to and after the inauguration.
Naturally the second is activity for the world. In this interpretation, packets represent increases in call activity from the previous hour, similar to the city piece.
A Little Misleading
The world visualization is slightly misleading however. You’d have to read carefully to know it though. Each packet in the U.S. represents 100 calls while packets that come from foreign countries represent only 10. For those who don’t want to do the math – that means the world visualization represents 10 times the increase in calls from foreign countries than it really should, so while beautiful, take it in with a grain of salt.
Data mistake aside, I’m continuing to appreciate the good stuff coming out of all the MIT labs.
So shouldn’t it be titled “Worldwide Obama Buzz Mis-Visualized”?
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The decision of using two different multipliers for US states and foreign countries was taken after evaluating the other solutions available. We could have visualized the two sets in two separate narratives, but we would have failed to convey the idea of people coming together as one. We could have used the same multiplier, but that would have not given enough prominence to the increase in activity by foreigners.
In the end we decided to represent the two data sets according to two different scales. This is not a mistake but rather a design choice, quite common when visualizing data sets that have different orders of magnitude. The text that accompany the visualizations explains this and also guide the viewer in understanding the meaning of what she is looking at. What would you have done instead?
Sorry bud, I was really just messing with ya. I understand what you’re doing – guess I shouldn’t have been so cynical in my response.
Have a good day.
I think Andrea’s response might have been more directed at me.
I know the design choice was deliberate, which is why I felt compelled to highlight it.
I don’t think it’s very common to represent variables of different magnitude simply my multiplying one. If that is common practice, it shouldn’t be.
For simplicity’s sake, let’s pretend we’re dealing with a bar graph instead of a map. We have bars for the U.S. and then bars for foreign countries. In our original bar graph, we see that growth for foreign is really tiny compared to the U.S.. Do we increase the foreign bars by 10 to make it look better and then add a footnote? No.
It’s the same idea with the map. It’s simply not a fair representation of the data.
I couldn’t glean any decent info from those visuals. It all looked a bit silly to me.
I think it’s also a bit pretentious to replace “cell phone traffic” with “emotional flow”. I might as well call Death and Taxes a Visual Guide to Presidential Desires.
@Nathan, to your point I don’t think it is that cut and dry. I think you need to factor the use-case of the visualization into the equation.
If the primary use case was to show rates of change (versus total volume) and you have one group of data that outlies other data then perhaps you use a log-scale versus linear…. is that violating the integrity of the visualization even if it distorts the data?
So to your case above, if the goal is to do a comparative analysis between country data, then no, don’t scale the other countries. But, if the goal was to do a comparative analysis of rate of change across countries, and then a finer level comparative analysis intra-countries then perhaps the approach Andrea took would be appropriate.
In those situations, where the “integrity” of the visualization may be questioned and/or distorted by the scales being used and it is an interactive visualization I often give users an option to toggle between scale modes so they can see the data both ways.
@Tom: Log-scale probably would’ve worked, but in this case, two scales are represented as one.
I think the main thing here is that most people are going to watch the video and think it’s the same scale, because there’s nothing in the actual viz that suggests otherwise.
@Nathan, agreed, that probably could have been called out better in this situation.
Some of this discussion assumes that the primary goal of this, or any visualization, must be to objectively and accurately understand the underlying data better. Though often the case, I don’t think that HAS to be the case, and there have been many examples on this blog where, I think, the primary goal was more artistic and less scientific.
Their primary goal was to celebrate Obama and to deliver a political message: the reinforcement of the “Obama is popular in the US and elsewhere” and “Obama is a uniter” narratives.
If one had focussed primarily on the goal of understanding the data better, rather than celebrating Obama, it probably wouldn’t have occurred to them to multiply the numbers to support the “one people” part of the narrative… but the fact that it was “not fair” as mentioned above, is secondary to making a pleasing visualization that delivers the intended message… even at the risk of misleadingly representing the underlying data.
They had different priorities. I don’t think one type of goal of a visualization is “right” or “wrong”… they each have their place. I hope at MIT they are learning the difference though… and not learning that it’s ok to start with a desired premise and then fit the data to… and then call it “science”. Perhaps that’s part of why we expect scientific rigor… simply because it came from MIT. Had this visualization been produced from some liberal think tank, would we have commented in the same way? Or would we have just enjoyed the visualization for it’s own sake?
If you want to criticize how well this visualization works from a scientific point of view, it seems there are bigger problems than “non-US traffic is overstated”.
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