Fig. 1: Novel representation of electrostatic interaction energy (in the middle) helps navigating the simulation by spatially resolving contributions to the integral measure traditionally represented by a timeseries (blue line in the bottom). It captures different modes of the simulation better than the timeseries and helps localizing changes in the configuration of the simulation by providing spatial context. The multiscale behaviour of the data is explored by seamlessly navigating the spatiotemporal scale-space. The selected timestep shows the ligand escaping from the tunnel, before it is sucked back in by the protein.Abstract-Understanding large amounts of spatiotemporal data from particle-based simulations, such as molecular dynamics, often relies on the computation and analysis of aggregate measures. These, however, by virtue of aggregation, hide structural information about the space/time localization of the studied phenomena. This leads to degenerate cases where the measures fail to capture distinct behaviour. In order to drill into these aggregate values, we propose a multi-scale visual exploration technique. Our novel representation, based on partial domain aggregation, enables the construction of a continuous scale-space for discrete datasets and the simultaneous exploration of scales in both space and time. We link these two scale-spaces in a scale-space space-time cube and model linked views as orthogonal slices through this cube, thus enabling the rapid identification of spatio-temporal patterns at multiple scales. To demonstrate the effectiveness of our approach, we showcase an advanced exploration of a protein-ligand simulation.