Data visualization describes the graphical art of representing data and information. The application of different data visualization elements helps in providing an accessible way of seeing and understanding data patterns, outliers, and trends (Jacobsen, 2019). Data visualization creates visual art that grabs people's interests and keeps their eyes focused on the message. Therefore, it becomes easy to internalize information and interpret it. This paper provides a detailed discussion of the different types of data visualization, how they are applied in public safety agencies ad hoe they reflect best practices.
The public traffic safety is one of the critical areas that apply data visualization to analyze safety systems in transportation. One example is the speed data visualization that offers anonymous and aggregated data concerning transportation movement to local administrations to improve traffic organization (Jacobsen, 2019). Such a dataset provides people, road users, with traffic speeds in diverse regions of towns over different periods. Secondly is road crash data visualization that helps in providing updates on some of the most dangerous traffic intersections, roads, and streets (Mehdizadeh et al. 2020). Road crash offers real-time information on the vehicle and fatal crashes, thus helping in avoiding such routes.
Data visualization is also applied in law enforcement agencies. One of the examples in this sector includes the Automated License Plate Readers (ALPR). Security agencies across the globe are using this technology in applying optical recognition to vehicle photographs (Miles, 2020). Through optical recognition, agencies can extract the number-plates in readable formats, which can be analyzed to develop connections between the vehicles, owners, and locations in case one is stolen. The second type of data visualization used in law enforcement is offender360 software. The software is applied to identify and manage people in a correctional facility or jail (Haisler, 2017). Through this approach, law agencies can manage the offender lifecycle, thus reducing the paper-based processes.
Conclusion
The above examples of visualization and data analytics tools offer the capacity to recognize threats at the system level. Therefore, these tools help develop approaches that will contribute to new and life-saving tactics that prevent fatalities on roads and improve management in correctional facilities.
References
Haisler, D. (2017, April 4). Ten ways public safety agencies are using data to innovate. Government Technology State & Local Articles - e.Republic. https://www.govtech.com/em/safety/10-Ways-Public-Safety-Agencies-Are-Using-Data-To-Innovate.html
Jacobsen, C. (2019, May 19). Visualizing traffic safety with Uber movement data and Kepler.gl. Uber Engineering Blog. https://eng.uber.com/kepler-data-visualization-traffic-safety/
Mehdizadeh, A., Cai, M., Hu, Q., Alamdar Yazdi, M. A., Mohabbati-Kalejahi, N., Vinel, A., ... & Megahed, F. M. (2020). A review of analytic data applications in road traffic safety. Part 1: descriptive and predictive modeling. Sensors, 20(4), 1107.
Miles, C. (2020, June 26). Graph visualization and law enforcement data. Cambridge Intelligence. https://cambridge-intelligence.com/applying-graph-visualization-law-enforcement-data/
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