Spatio-temporal datasets are a collection of datasets where data can vary in both space and time. Theoretically, such datasets can be considered as continuous and discrete. For example, specification of the function, F: Ed T Rn, where Ed denotes d-dimensional Euclidean space, T = R* ∩ {} the domain of time and Rn an n-dimensional scalar field. Examples of such data sets include time-varying simulation results, film and videos, time-varying medical datasets, geometry models with motion or deformation, meteorological measurements, and many more. It is therefore highly desirable to use visualisation to summarize meaningful information in higher dimensional spatio-temporal datasets. Our aim is to conceive an efficient visual study to facilitate scientists in identifying temporal association among complex and chaotic atom movements in ion trajectories. An application that uses a streamline for spatial motion of ion trajectories and Colour Number Coding Scheme for temporal encoding of high degree of timeline events among mobile ions is proposed. With an anthology of the visual examples, it was revealed that this application would be beneficial for scientists to visually mine any 3D spatio-temporal dataset.