Temporal Focus+Context for Clusters in Particle Data

Abstract

Time-dependent particle-based simulations are typically carried out by direct calculation of interactions between particles over time. The investigation of higher order effects of particle clusters helps understanding the system's dynamic. Existing methods for particle data analysis either rely on animation, where only one time step is visible, or abstraction, which is giving up on visualizing the data in its spatial domain. Inspired from illustrative techniques, we present an interactive focus+context visualization, based on flow ribbons, that combines both approaches. Our method jointly shows one time step in detail, as well as an abstract contextual visualization of past and future dynamics in one image. It allows to assess the time evolution of various cluster attributes around the current temporal focus. We show the usefulness of the approach on two exemplary case studies.