Alallah, FouadFaleel, ShariffSakamoto, YumikoRey, BradleyIrani, PourangAgus, MarcoAigner, WolfgangHoellt, Thomas2022-06-022022-06-022022978-3-03868-184-7https://doi.org/10.2312/evs.20221088https://diglib.eg.org:443/handle/10.2312/evs20221088Spatio-temporal visualization research has been capturing much attention in recent years. Space-time cube (STC) has been commonly used to visualize this data to support analytic tasks. However, the current STC visualization tools are currently not compatible with situated platforms since these tools are often designed for desktop computing. Thus, we propose a situated space-time cube analytics (SSCA) prototype that maps spatio-temporal trajectory data into the environment where the data was captured. Being situated in such an environment while exploring data can provide benefits, and further allows us to explore interaction techniques such as proxemics and embodied interaction. We are confident that with SSCA, and a new generation of augmented reality technologies, researchers can begin to better explore the potential of situated STC analytics.Attribution 4.0 International LicenseCCS Concepts: Human-centered computing → Visualization; Visual Analytics → Situated Visualization; Visualization → Visualization Systems and toolsHumancentered computing → VisualizationVisual Analytics → Situated VisualizationVisualization → Visualization Systems and tools10.2312/evs.2022108825-295 pages