In this study, we describe a method to construct a correlation map that captures the evolution of species-specific dynamic information through the spatial correlation of high-dimensional time-series molecular dynamics (MD) simulation dataset for a series of borosilicate glasses. The correlation is based on 'displacement' between a pair of atomic configurations determined by the root mean square distance (RMSD) metric. We implement the correlation map as a quantitative visualization tool that provides a compressed representation of a high-dimensional molecular dynamics dataset to inspect various physical aspects and capture distinct atomic dynamics-from large fluctuations to small local oscillations-for high-temperature melt, linear cooling, and low-temperature equilibration processes during molecular dynamics simulation of glasses. We capture species-specific dynamics using this method that show different cooling dynamics for different glass formers and modifiers, especially the onset of slow dynamics and the variation of atomic dynamics at high temperatures. Furthermore, we show that the species-specific atomic dynamics have structural origins that depend on the composition of the simulated borosilicate glasses. The correlation map serves as a visualization tool to rapidly survey changes in atomic configurations during different simulation conditions.