For our project, we used data from the OSU Department of Public Safety to look at the number of open container violations that occurred on OSU football home games from 2005-2013. Following the 2004 season, there was a significant uptick in enforcement of alcohol related rules resulting in over 1,000 incidents throughout the period of analysis (compared to a few dozen in the years before). We have mapped out the incidents, which were primarily focused in and around parking lots on Ag and West campus that are a part of the university parking system.
Initially, one of our biggest problems was the lack of continuity in the data entry of OSUPD in defining the site of each incident. We were very surprised that when data was entered into the OSU Public Safety database, the information was very unorganized. Essentially the officer giving each citation simply looked at their location and wrote a corresponding description of the site . When the incident data was input to the OSU Public Safety database, the descriptions used in the citations were entered as they were written on the ticket (rather than choosing from a list). We found several descriptions of the same location (i.e. Ag Ad Lot ,AA Lot, Ag Admin Lot, Ag Administrative Lot, Agriculture Administrative Lot, Agriculture Admin Lot, 2120 Fyffe Rd, etc.) which made the data consolidation process very tedious and required us to check and double check multiple campus maps. After downloading the source code from the OSU Public Safety website and converting the data to work as a .csv file, we had to resolve the issue of multiple names for the same locations. In streamlining the data, we consolidated these multiple descriptions to match and allow for easier sorting and mapping of points in a decimal degree coordinate format.
After we standardized the place names and locations of each incident, our next issue occurred when implementing the data onto the OSU map, which was in a projected coordinate system (PCS) not a geographic coordinate system (GCS) and did not match with the decimal degree format of our place names. To solve this problem, we set the data frame’s coordinate system to WGS 1984, which is a GCS and created lat/long fields in the tables for the OSU shape files. This allowed for calculation of the geometry based on X/Y coordinates of the centroid of each polygon using the coordinate system of the data frame and also allowed us to layer our incident locations onto the map.
After this change, users are able to see how and where the concentration of open alcohol containers have increased and shifted across campus. One constant observed is the significant number of incidents in close proximity to the Fawcett Center. The natural application of this work is to see where (if) there is a place that is “safer” than others to tailgate in preparation for OSU home football games. There is definitely a correlation between “big” games and an uptick of incidents. For example, the USC game in 2009 (a nationally televised night game when both teams were highly ranked) had more open container incidents than the first 4 games of the 2012 season combined. Analysis of the incident reports of OSUPD showed that the vast majority of offenders were not OSU students. This project would be most useful to those visiting OSU rather than students, who typically enjoy pre game festivities at their own residences near campus.