Extracting knowledge about the movement of different types of mobile agents (e.g. human, animals, vehicles) and dynamic
phenomena (e.g. hurricanes) requires new exploratory data
analysis methods for massive movement datasets. Different types of moving objects share similarities but also express differences in terms of their dynamic behavior and the nature of their movement. Extracting such similarities can significantly contribute to the prediction, modeling and simulation dynamic phenomena. Therefore, with the development of a quantitative methodology this research intends to investigate and explore similarities in the
dynamics of moving objects by using methods of GIScience in
knowledge discovery. This paper presents a summary of the
ongoing Ph.D. research project.