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D. Sardana,  N. D. Chandrashekar,  R. SplechtnaT. HulkaK. Matković (2022)

Exploring the Patterns in City’s Demographics from Heterogeneous Data

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IEEE VIS 2022 - VAST challenge

Abstract

Analyzing and identifying patterns in a multidimensional spatiotemporal data is challenging. In this paper, 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 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.

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Keywords

Human-centered computing, Visualization, Visualization application domains, Visual Analytics Humancentered computing, Visualization, Visualization systems and tools, Visualization toolkits