Supporting Spatio-temporal Data Sensemaking using Embodiment in Immersive Environments

This thesis leverages immersive technologies to support the sensemaking process in spatio-temporal data analysis with layered space-time cubes. We simplify the sensemaking process into three aspects: data understanding, data exploration, and analytical reasoning, and investigate how to support these aspects in immersive environments from three perspectives: visualisation perception, user interaction, and analytic provenance. We explored the effectiveness of different data representations, developed a prototype to investigate the use of embodied interactions for data exploration and proposed a concept of embodied provenance. This work contributes to the establishment of a design space for a spatio-temporal data sensemaking process in immersive environments.