@quaid
I've worked with similar data for another state and unfortunately the political interests over racial issues outweighed the desire to produce anything truly valuable.
Where I ended up (for internal use only) was a web presentation that simultaneously displayed a set of six time-series animated .gifs arranged in 2 columns with 3 .gifs in each column; each base map had a frequency chart nested next to the map.
The 2-columns represented :
1. all traffic stops
2. traffic stops that progressed to vehicle search.
The 3-rows reflected:
1. white driver
2. black driver
3. other
All of the traffic stop data were geocoded (given lat/long coordinates) divided into 3 data sets (white/black/other) and then each subdivided into 12 sets with each set reflecting the 2-hr time-of-day bucket into which the traffic stopped occurred.
Then a hi-res density map (i.e stops per sq. mi.) of each subset was created (6 subjects x 12 2-hr time-of-day buckets = 72 surface layer files) and saved to .gif
The .gifs were brought into photoshop - 1 at a time and updated with the time, count by time-period, and total count for each of the 6 col/row combinations and the 6 animation .gifs were created showing surface density of stops by race with/without searches in 2-hr increments.
I'm sure flash action script can do this better/faster now -- then it was still Macromedia and wasn't an option for my office at that time.
The density layers were created with ArcGIS software with a spatial analyst extension. I would look at CrimeStat3, GeoDa (?), or GRASS and the R-project for the similar function if ArcGIS is not available. The model builder function in ArcGIS could automate the entire process much faster than a manual process.
There are so many ways to slice and dice this type of data - by season, by day of week, by ordinal class of car, etc --- then there is the correlation analysis with the area population in which the traffic stop was initiated ...
It's dubious if any of this may be of value :-) - but rest assured, someone out here feels your a)joy at having such a rich data set b)the inevitable pain of finding the best way to present the data that makes someone else happy.
