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In many scientific fields, the analysis of distributions is essential to unveil patterns in order to set up, confirm or reject hypothesis. However, the application of specific visualization techniques may introduce uncertainties along the analytical pipeline. These so-called visualization mirages lead to cognitive biases and misinterpretations during the analysis, which users are often not aware of and which may lead to incorrect decisions. Complementary interfaces are a reasonable solution to uncover and address these uncertainties without disrupting the analysis workflow. Cross-reality allows to integrate various technologies along the reality-virtuality continuum (RVC) to augment visualization systems. This facilitates users to interact naturally and intuitively with a 2D system, such as augmented reality (AR) devices, and be aware of the relationship between data and its representation, avoiding misinterpretations through uncertainties.
Gall et al. (2023) studied this question.