Jumping Fox

We all know that data can tell different stories depending on how you spin it and the way data is visually represented can lead to assumptions by the viewer.

Nicholas Rapp has written a post over at his personal blog discussing the creation of a graphic on American vehicle carbon dioxide emissions. The creation of this graphic demonstrates how data can be interpreted in different ways depending on the method that it is displayed.

The first map showing emissions come from major cities

In his post you can see a map of the USA with two versions of the same data overlay; the first has the total emissions per county per year, the second has total emissions per capita per year. The interesting thing is the two stories that the data tell; naturally the first says that all the emissions come from the major cities. But when you look at the second map, there as a noticeable difference in the indicators.

The second map tells a different story

Cities like Los Angeles have a large emission marker on the first version (per county) but a basically non-existent in the second version (per capita). Where as places in the middle of the country have a much larger indicator in the second version. I’m not going to go into what the data is implying (like less people in the country and further to travel etc) but it does demonstrate that from the same data two different stories can be told.

I think it is important to know what story you want to tell when designing a visualisation around data, though sometimes it may not hurt to test the data against some different filters/categories to see if there is something else that maybe more interesting.

Update

Carbon emissions from road transport

Since this post is about vechile carbon emissions, you might like to have a look at a data set The Guardian has released on carbon emmissions from vechiles around the world. From this data they have also produced a really nice clean graphic with the 10 largest polluting countries.