Maps are big these days. Blogs and news sites (including this one) frequently post maps and those maps often go viral—40 maps that explain the world, the favorite TV shows of each U.S. state, and so on. They’re all over Facebook, Twitter, and Tumblr, and news organizations are understandably capitalizing on the power that maps clearly have in digital space: they can visualize a lot of data quickly and effectively. But they can also visualize a lot of data inaccurately and misleadingly.
A map is not just a picture—it’s also the data behind the map, the methodology used to collect and parse that data, the people doing that work, the choices made in terms of visualization and the software used to make them. A map is also a representation of the world, which in some ways must always be a little inaccurate—most maps, after all, show the roughly spherical world on a flat surface. Certain things are always left off or highlighted while others are altered, as no map can show everything at once. All of those choices and biases, conscious or not, can have important effects on the map itself. We may be looking at something inaccurate, misleading, or incorrect without realizing it.