Uniform Crime Report "SuperClean" Data Cleaning Tool

The analysis of UCR data provides a basis for crime prevention in the United States as well as a sound decision making tool for policy makers. The decisions made with the use of UCR data range from major funding for resource allocation down to patrol distribution by local police departments. The FBI collects and maintains the database of the Uniform Crime Reports (UCR), from 18,000 reporting police agencies nationwide. However, many of these data sets have missing, incomplete, or incorrect data points that render crime analysis less effective. UCR experts have stated that in the current form UCR data is unreliable and sporadic. Efforts have previously been made to design a software application to correct these necessary problems, but the application was deemed insufficient due to limited portability and usability. Software requirements restricted potential users and the user interface was ineffective. However, this previous work describes the functions needed to effectively clean and assess UCR data. This paper describes the design of an application used to clean, process, and correct UCR data so that ideal policy decisions can be made. Erroneous portions of the data will be found using the outlier detection function that is based on a statistical model of anomalous behavior. These methods incorporate sponsor specifications and user requirements. This project builds upon the GRASP (geospatial repository for analysis and safety planning) project's goal of sharing information between law enforcement agencies. Eventually this application could be integrated with GRASP to form a single repository for UCR and spatial crime data. This paper describes how the new stand alone application will allow users to clean, correct, and process UCR data in an efficient, user-friendly manner. Formal testing provides a basis to assess the effectiveness of the application based on the metrics of time, cost, and quality. The results are the basis for improvements to the application