The City of Chicago publishes some rich crime data, available e.g. here:
The address of event crime is partly obscured, so as to read for example "010XX N CENTRAL PARK AVE". The data also provides coordinates and longitude / latitude data. These agree if you use the correct projection (in feet). I would have expected each coordinate to, for example, correspond to the middle of the block, but this is not so.
Screen shot from QGIS with OpenLayers as the basemap:
So what we see is clusters of events, corresponding to the correct block. What I find puzzling is that the mid-point of these clusters does not appear to be the mid-point the block. The pattern is repeated, seemingly, across the whole dataset (so in other parts of the city, with residential buildings on the avenues, you get north/south clusters, again, not centred). Could the centre of each cluster perhaps correspond to the centroid (projected onto the middle of the road) of all the buildings in the block?
From some messing about in Python, and simulation, the clusters look like they are normally distributed (not uniformly distributed).
Interestingly, I've now looked at the complete data set, from 2001 onwards, and the crimes reported in 2001 (only) seem to show a rather different pattern:
Frankly, this looks pretty realistic to me! Is it possible they only started obscuring the real coordinates after 2001?
Does anyone know the exact way the location coordinates are actually generated?