An exploratory data analysis protocol for identifying problems in continuous movement data

Movement datasets are often complex and require sophisticated processing and analysis. A thorough understanding of the dataset is needed to choose the right methods and to interpret their results. Misunderstandings and violations of assumptions about dataset characteristics can lead to flawed analysis results and wrong conclusions. To address this challenge, we propose a novel protocol for the systematic exploration of movement datasets. The individual protocol steps address the different types of movement data problems. The exploration tools recommended at each step are specifically tailored to identifying potential problems and avoiding common pitfalls when working with global navigation satellite system (GNSS) tracking data, commonly referred to as GPS tracks. However, the general steps should be transferable to continuous movement datasets with different characteristics, such as video trajectories. Furthermore, we provide an open-source implementation of our protocol in the form of a Jupyter notebook accompanying this paper.