Analyzing, Fixing, and Improving OpenStreetMap
We’re looking at new ways to find out how and where OpenStreetMap needs improvement. The collaborative mapping project that provides the street data in our world map MapBox Streets is remarkably complete, as well as open and free, but it is continually unfinished as roads are built and borders changed.
Foursquare’s adoption of MapBox Streets and OpenStreetMap and Apple’s likely usage have directed many more eyes at the project - all users who are likely to spot missing roads and features, and be able to give incredibly valuable feedback. This feedback has been one of the guiding elements of our tracing efforts over the past few weeks, but we’re working on ways to get global, fine-grained priorities set.
One of the tools we’ve been using is simply an overlay of social checkins on the map. Often city centers are well mapped, but completeness falls off quickly from the center and there’s still a lot of population and activity in the outskirts.
Of course social network activity isn’t an absolute indicator of where general populations are or what areas important to map, but it’s a useful heuristic - and one that can be derived on a global level.
But it’s not just important where people are - we need to know where the map doesn’t cover. For this we’ve been working on finding the street density, measured by the file size of tile pyramids, of MapBox Streets. I talked about that analysis at NodeDC on Monday, a presentation that’s available online.
This is just one angle of finding and improving data gaps and flaws in OpenStreetMap - the community has created many other methods, and novel ideas like fixing routing between cities have been used to drive improvements. The fact that OSM’s data is available in its entirety and freely licensed enables all of these approaches.