Let’s Break some Rules

A few weeks ago, while I was driving several hours towards our camping holidays, I suddenly noticed this beautiful piece of data visualization right in front of me. Actually, I found it that beautiful that I had to remake it in Illustrator:

I was completely stunned by the clean and simple layout of this gauge chart. It shows everything I, as the driver, need to know such as: How fast am I driving at the moment, how far have I’ve been driving at all, when is it time to get a new car.

But then I realized that this tiny chart, despite its useful, intelligent design, violates some of the common rules of data visualization, so I thought it’s a good idea to write about it.

Why use a radial gauge chart at all?

Let’s face it, the current driving speed is not periodic data, so there should be no reason to use a radial layout. As we all know, humans are not as good in comparing angles as we are in comparing lengths. So why shouldn’t we use bar charts for displaying the speed?

One obvious answer is that it makes a lot of sense to re-use established metaphors. Everyone who’s driving a car knows how to read the driving speed in a gauge chart, and probably nobody ever needs to be taught reading them. Another possible answer is that we connect certain semantics to the different regions of the radial gauge layout. No need to tint the last quarter of the gauge in red, everybody knows that this is the danger zone. We don’t have similar embedded semantics in a bar chart.

Not more than three data points

According to Jorges Camoes recently published rules of data visualization, the speedometer I fell in love with isn’t data visualization at all. That is because it doesn’t show more than three data points. That’s true, there are only 3 data points I can read in the display, and, if we subtract the LCD that was added to the bottom, there’s only one number left. One single number? Do we really need a big gauge dashboard display for one number? Of course we do, because a chart never shows just a single number. More importantly, a chart puts the single number into context. If you ever had to drive a car with a dashboard like the Renaut Twingo I, you’ll never forget that difference.

For instance, in the gauge chart there are two red tick marks for important driving speed limits. Sure, I know those limits back from driving school, but I find it really helpful to see how my current speed compares to them. The other context is the capability of my car. If I’d be driving at 200km/h (which I never do), I’d instantly see that I almost reached the limit of my car.

Non-continuous scale

But now it gets even worse. As you might noticed, the speed scale breaks at 120 km per hour. Therefore comparing angles gets even harder. Without any doubt, that cannot be good data visualization! For comparison, here’s a different version of the same chart using a continuous scale:

Now we lost half of the magic of the original design. Using the non-continuous scale the tick for 100km/h, the speed limit on primary highways, sits right at the 12 o’clock position. Can you imagine driving for hours and hours watching the gauge needle standing at 11:30 as shown in the above image? It just don’t feels right, and it would always push you to drive faster.

Using the non-continuous scale allows to ‘stretch’ the speeds below 120km/h and thus makes them more easy to read. The difference between 30 and 50km/h in a populated area is more important than the difference between 130 and 150km/h on a German Autobahn. My car is a family car, not a sports vehicle. The designers probably wanted to emphasize the reasonable driving speeds, and that’s what I like most about the visualization.

When to break the rules?

So, you know, the rules are the rules, but you should know when and why to break them. Of course it is allowed to display just a single data point in a chart. And of course it is allowed to add fancy annotations to the chart wherever you like. And, yes, it is even allowed to use radial charts for non-periodic data, as it is allowed to reject a certain chart type, just because the audience is not familiar with it.

Whenever it makes sense.