A Process for Visualizing Disordered Molecular Data with a Case Study in Bulk Water

Abstract

Existing molecular visualizations do a good job of illuminating well-defined structures, but are ill-suited to visualizing subtle organization when the data is almost entirely disordered. We introduce a process to explore these subtle structures by visualizing an abstraction of the data. The process includes a quantitative verification step to mitigate the ambiguity induced by abstraction. We perform a case study using molecular dynamics simulation data of bulk water to demonstrate the efficacy of our process. The visualized abstractions show molecular behaviors which only happen amongst aggregates, and which would be occluded or indiscernible in a direct visualization. The effect is shown across multiple data sets with different temporal and thermal parameters. In conjunction with domain experts from the Chemistry department who performed the simulation, we confirm our observations using the quantitative verification step of our process.