I watched the fancy OpenStreetMap Year of Edits 2012 video, which shows a data-driven animation of all the map edits happening around the world from thousands of contributors. It certainly makes the project look busy!
BUT it's not the kind of data-viz that particularly wants you to understand the data. If you watch the video, can you tell which was the busiest part of the world? Which bit was least busy -- where should OSM's next recruitment drive be?
So here's what I wondered: can we visualise the density of map edits for a place, relative to the population of the place? You see, if we assume that the population density of one part of the world should be roughly proportional to the number of things-that-should-be-mapped in that part of the world, then a low value of this ratio (edit rate divided by population density) indicates a place that needs more mapping.
So how to do it? I downloaded the OSM changesets from http://planet.osm.org/ and piled up all the bounding boxes from the 2012 changesets, converting that into a grid giving the edit density. Then I was lucky enough to find this gridded world population density data download from Columbia University.
Then I wrote a Python script to divide one by the other and plot the result. Here it is:
Blue areas have a relatively high number of edits per head of population, red have relatively low. White is average.
(BTW, here's the plot of the edit density, before taking the ratio.)
This is only a rough sketch, since it relies on some assumptions (e.g. every "changeset" was an equally important edit; also the map-features-per-population assumption I already mentioned). But the general story is: we need more mappers in South-East Asia (especially China) and Africa, please!
The plot clearly shows a general pattern connected with relative wealth / access to tech, so maybe initiatives like operation cowboy are the way to do it - get places mapped on behalf of others.