A web-based crime data analysis tool for Los Angeles, leveraging complex trend queries to analyze crime statistics. Built with JavaScript and SQL, the application uses Chart.js for data visualization and Google Maps API for location-based insights. Users can interact with the frontend to view crime trends, generate visualizations, and explore data-driven insights. The backend queries an Oracle database to retrieve and process real-world crime data, supporting both operational and complex trend analysis. The tool is designed to better understand crime patterns and trends in Los Angeles.

Quick Look

Datasets

Crime data is publicly available from the LA City website.

• Crime Data from 2010 to 2019
• Crime Data from 2020 to Present

Dependencies

• Node.js

Getting Started

1. Open Terminal on the backend folder and run the following command to install backend dependencies.

   npm init
   

2. Create .env file inside the backend folder. Then, input your UF CISE Oracle credentials into the file with the following structure:

   DB_USER=
   DB_PASSWORD=
   

3. Connect to Gatorlink VPN
4. Open the backend by running app.js from the backend folder with following command:

   node app
   

5. Run homepage.html inside /frontend/pages/ to use the website.

Disclaimer

This project is only accessible to those with access to the university’s database. If database tables are deleted, data will no longer be viewable and must be reuploaded.