Exploring the Patterns in City’s Demographics from Heterogeneous Data
Analyzing and identifying patterns in multidimensional spatio-temporal data is challenging. In this work, we use time-series data exploration and brushing techniques to explore the financial journey of the city population in a spatio-temporal heterogeneous dataset. We also use force-directed graphs to investigate social isolation based on the financial status of the people in the city. The visualizations have been developed as an answer to the IEEE VAST 2022 Mini Challenge 1. We describe some interesting findings to be shared with the city's residents.
The work is accepted for publication in the IEEE VIS 2022 proceedings. To learn more about the dataset that is shown, visit IEEE VAST Challenge 2022.
Related links: Conference Paper | Demo | Observable Link 1 | Observable Link 2 | GitHub | Figma Design Board