3D Scientific Data Mining in Ion Trajectories

In physics, structure of glass and ion trajectories are essentially based on statistical analysis of data acquired through experimental measurement and computer simulation. Invariably, the details of the structure-transport relationships in the data have been mistreated in favour of ensemble average. In this study, we demonstrate a visual approach of such relationship using surface-based visualisation schemes. In particular, we demonstrate a scientific datasets of simulated 3D time-varying model and examine the temporal correlation among ion trajectories. We propose a scheme that uses a three dimensional visual representation with colour scale for depicting the timeline events in ion trajectories and this scheme could be divided into two major part such as global and local time scale. With a collection of visual examples from this study, we demonstrate that this scheme may offer an effective tool for visually mining 3D timeline events of the ion trajectories. This work will potentially form a basis of a novel analysis tool for measuring the effectiveness of visual representation to assist physicist in identifying possible temporal association among complex and chaotic atom movements in ion trajectories.