YouieCho-LookingOutwards-07

The animated map allows to see the big picture in train movements and to spot systemic effects. Peak Spotting by Christian Au, Moritz Stefaner, Stephan Thiel, Christian Laesser, Gabriel Credico, Lennart Hildebrandt, and Kevin Wang

The computational information visualization that I looked at is “Peak Spotting.” This is a means to combine machine learning and visual analytics methods to help manage the passenger loads on trains in Germany. It has a futuristic elements in the web application that integrates millions of datapoints over 100 days in the future to make predictions, and custom developed tools such as animated maps, path-time-diagrams, and stacked histograms create a vast range of types of data. The clearly color-coded visualizations point out what the critical bottlenecks are within the traffic difficulties. I think that the overall aesthetics is very helpful for understanding the data because it is subtle and readable with highly effective key colors. I can immediately know what kind of data I am looking at, and what time period the data are relevant to. Navigation also gives a good guidance.

Peak Spotting Preview

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