Data maps are everywhere. And it's not just the conventional ones that use Google Maps, OpenStreetMaps or Bing Maps to show the underlying geographical information. Cartograms, "maps" with land masses resized based on data, are quite popular. I'm not a big fan of them because they require us to judge magnitudes based on the relative sizes of some peculiar and many-sided shapes. Generally, we're not very good at this. However, I do think distorted, simplified or unrealistic maps can be useful. In the recent UK general election several mediaoutlets chose to eschew conventional choropleth maps in favor of ones in which all constituencies were equally sized hexagons. The resultant maps were still reminiscent of the United Kingdom, but the amount of any given color became directly proportional to the number of seats won by a particular political party. Maps of the USA with square states have also been used by media outlets to show data. For example here, here, and here. But what if, instead of distorted borders, we don't show any borders at all?
In the last year or two I've seen an increasing number of what may be termed "minimalist maps". Specifically, I'm referring to the display of geographic or geopolitical data in such a manner that the underlying geography can be seen, perhaps roughly, without ever drawing conventional features of a map like land/sea, country or state borders. Below is a simple example I made. I'm sure you don't need me to tell you it is a "map" of the world. You may even recognize it makes use of the (in)famous Mercator projection. It shows the locations of all urban agglomerations with 300,000 or more inhabitants in 2014 (data published by the UN's population division). Each circle is scaled according to its population in 2010 (data for 2014 wasn't specifically available). I'd normally add a scale to a chart like this, but here I'm primarily concerned with the locations of large cities and so some concept of relative size is enough.
From the map I'm sure you can make out the location of the USA, the thin band that is central America, the Eastern protrusion of Brazil, the Cape of Good Hope at the bottom of Africa and the Indian subcontinent, without requiring any lines. Conversely, there's little detail about the shape of Canada or Australia and the Southern tip of South America is completely missing. There's nothing in the desert area of North Africa, while the cities on its northern coastline are hard to pick apart from those of southern Europe.
It's probably fairly obvious why the map does look familiar despite the lack of sea/land borders:
- 1) we don't build cities in the oceans;
- 2) we do build cities by the sea;
- 3) we're familiar with maps of the Earth, particularly ones that use the Mercator projection.
But it doesn't need to be the whole Earth to look familiar. The next map is clearly of East Asia.
We can still pick out the Indian subcontinent easily in the map above and the eastern coast of China is fairly obvious too.
How about the next example?
Hopefully you identified that was the USA (plus northern Mexico and southern Canada).
This last one reminds me of the night sky on a cloudless night...
Some labels may be needed here to help you get your bearings:
Europe has a large number of large urban agglomerations, but they're frequently not found near the sea.
Of course, we could tell that many European cities weren't built near the sea if we added the land/sea borders. So one obvious question might be: "Is there really any point to this minimalist approach to mapping data?".
For the maps shown here the answer to that question may well be "no". At least, probably not in terms of data visualization best practices. I did, however, find it an interesting test of my geography knowledge trying to label the cities in the last example without looking at a "proper" map.
One small advantage with minimalist maps is that you don't have to worry about the size of the map files you're using, which can be large when maps are highly detailed. If you're using vector images on a website that is certainly a positive thing. But sacrificing clarity in favor of reducing file size is never a great idea.
More important than file size, however, is that other people have made more elegant and more effective minimalist maps than the ones I created above. This article by James Cheshire includes several great minimalist maps that also show where people live. Arthur Charpentier has created several nice examples of minimalist maps with other types of data. And in terms of letting the data speak for itself, I think Michael Pecirno's "Minimal Maps" are exceptional.
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