Immersive visualisation for a large metrological data set

Abstract

A purpose of scientific visualisation is to facilitate the extraction of information within underlying data. Visualisation of a large data set requires an appropriate visualisation method where, instead of focusing on expected features, all acquired data are treated on an equal footing. Here, we identify critical differences between raw and processed data acquired from displacement measurements at the nanoscale. We illustrate the strength of immersive data visualisation in rapidly and intuitively identifying non-obvious data trends, supported by correlation with the associated measurement uncertainties. These insights can be directly leveraged for optimisation of instrumentation and measurement protocols, application of appropriate measurement corrections, and iterative experimental design changes.