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coding theory, spatio-temporal, ion dynamics, streamline, colour scale, visual representation

Spatio-temporal dataset is a collection of datasets where data is vary in both space and time. Theoretically, such a datasets can be considered as a continuous and discrete. For example, specification of the function, : d n F E ×T ® R , where d E denotes ddimensional Euclidean space, T R { } * = Ç ¥ the domain of time and n R an n-dimensional scalar field. Examples, of such data sets include time-varying simulation results, films 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 data sets. In physics, ion trajectories has totally relied on statistical analysis from experimental and computer simulation results [1-5]. To help the physicists to identify and trigger the timeline and collaborative events in ion trajectory, we need the codes to distinguish the events according to timeline-based events. In coding theory, we need such a code that can represent each of the events in timeline series. Moreover, the code itself must help in identifying and trigger the events if there is a collaborative event among chaotic movements of ion trajectories. In particular, we propose a Colour Number Coding Scheme for depicting the time series of ion trajectories [6]. We discuss the method of depicting the time series in relation to the encoding series of timeline events in ion trajectories. We also point out some of the advantages of this method in terms of accuracy according to human observer.