Optimizing Local Police Practices with a Data Visualization Dashboard
In Charlottesville, various criminal justice agencies collaborate to form the Evidence-Based Decision Making (EBDM) team. One member of this organization is the Charlottesville Police Department, which seeks to optimize its processes to ensure efficiency and accountability. This paper explores the implementation and features of a dashboard designed to aid CPD’s internal evaluation with a particular focus on identifying disparity amongst demographics. This dashboard aims to improve decision-making, enhance resource allocation, and secure effective policing strategies by providing key performance metrics. The process began with developing relationships with local crime analysts to gain insights into the datasets and align expectations with the broader mission of the police force. The initiative then required data collection, cleaning, and integration among multiple organizations to perform jurisdictional comparisons. Using PowerBI as the primary data visualization tool, data modeling techniques were implemented to create meaningful relationships between data points, enabling comprehensive and holistic analysis. To track success, the dashboard monitors user engagement and how often particular visualizations are accessed. Additionally, client interviews provide qualitative feedback on its utility, and evaluation metrics will be assessed and presented. It is evident that through this analysis, innovative tools such as this data dashboard can advance the field of criminal justice by positively impacting public safety and police development.
Authors
- Matthew Vitale
- K. Preston White (ORCID: https://orcid.org/0000-0002-2426-5754)
- Michael C. Smith (ORCID: https://orcid.org/0000-0002-1136-0250)
- Loreto Peter Alonzi
- Isabella Lu
- Rachel Seo
Institutions
- University of Virginia (US)
Publication Details
- Published
- 2025-05-02
- DOI
- https://doi.org/10.1109/sieds65500.2025.11021141
- Primary Topic
- Data Visualization and Analytics
- Type
- article
- Field-Weighted Citation Impact
- 0.00