CHI Data Map is an interactive interface that connects to a web server through which various queries on a large dataset of bikeshare trips in Chicago can be made and visualized.
The intention is to allow the user to browse, control and observe when and where people are cycling in the city of Chicago without the hassle of dealing with big data. The user can view relationships between different stations as well as make comments/leave reviews on each station.
The goal of this visualization is to study the behavior of a city in transportation infrastructure language - connecting bike stations with bike trips to represent the flow of people. The count of tips is visualized to represent the vitality of each bike station and the count of trips from each origin is translated to the thickness of lines connecting these stations.
This is a final project for Applied Database course. Relational databases in various capacities, from managing data to optimizing datasets and creating web applications were explored.
Team: Alireza Karduni, Noushin Radnia
Backend Logic: Python Flask, MySQL
Interface Design: HTML, JavaScript, and CSS
Interactions: D3, Leaflet
