The document discusses dynamic transportation data visualization. It defines dynamic data as being time- and space-sensitive, including real-time traffic data feeds, mobile GPS trajectory data, and simulation model outputs. It describes using open source tools like Google Earth, Python, and HDF5 databases to visualize this dynamic data through interactive maps and plots. Specific examples shown include GPS trajectories, origin-destination desire lines, traffic simulation outputs comparing build scenarios, and visualization of travel patterns across large regions. The document emphasizes that as transportation data grows, visualization is key to exploring and understanding travel behavior patterns revealed in the data.