This paper presents a rendering framework for the visualization of massive point datasets in the web. It includes highly interactive point rendering, cluster visualization, basic interaction methods, and importance-based labeling, while being available for both mobile and desktop browsers. The rendering style is customizable. Our evaluation indicates that the framework facilitates interactive visualization of tens of millions of raw data points even without dynamic filtering or aggregation.

The visualization of trajectories and their attributes represents an essential functionality for spatio-temporal data visualization and analysis. Many visualization methods, however, focus mainly on sparse 2D movements or consider only the 2D components of movements. This paper is concerned with true 3D movement data, i.e., movements that take place in the three-dimensional space and which characteristics significantly depend an all dimensions. In this case, spatio-temporal visualization approaches need to map all three spatial dimensions together with required mappings for associated attributes. We describe visualization approaches for true 3D movement data and evaluate their application within 3D geovirtual environments. We also identify challenges and propose approaches for the interactive visualization of 3D movement data using 3D geovirtual environments as scenery.