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The potential of Big Data for understanding human mobility patterns and other complex phenomena in transportation and movement research is significant. Many contemporary Big Data sources have clear spatiotemporal dimensions. However, Big Spatiotemporal Data is usually messy and presents numerous challenges to researchers and analysts trying to extract information and knowledge. Exploratory data analysis tools for massive movement data are necessary to gain an understanding of our data, its biases and messiness and how they might affect our analyses. This talk presents methods for the exploration of movement patterns in massive quasi-continuous GPS tracking datasets, with examples focusing on international maritime vessel movements.
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