Building a Visual Analytics System for Spatio-temporal Analysis

Ability to extract knowledge from complex spatio-temporal datasets is key for understanding events happening in our surrounding environment, such as forest growth, disease spread, climate change and socio-economics. However, there is a lack of efficient tools for analysing these complex datasets from a holistic perspective due to challenges such as data size, quality and multi-dimensional complexities. In this talk, we first briefly introduce our work on a visual recommender system for exploring large complex spatio-temporal datasets. We then touch on the tools and libraries, such as D3 and Vega, used for constructing an interactive and responsive front-end interface for visual analytics