Interactive Ranking Uncertain Multivariate Ordinal Time Series

摘要

This work proposes a visual analytic technique to interactive rank uncertain multivariate ordinal time series for situational awareness. We use normalized entropy to quantify the uncertainty of the discrete survey data. The heatmap summarizes both the survey data and qualified uncertainty in a compact manner. Besides, the distributions of votes in neighborhoods are visualized using hexagons. This work presents the result of applying the solution to the VAST 2019 - Mini-Challenge 1 dataset, which led to the Award for Excellent Quantification of Abnormalities.