SSCA: Situated Space-time Cube Analytics

Abstract

Spatio-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

Citation

Fouad Alallah, Shariff Faleel, Yumiko Sakamoto, Bradley Rey, and Pourang Irani. "SSCA: Situated Space-time Cube Analytics." (2022).

Bibtext Entry

@article{alallah2022ssca,
title={SSCA: Situated Space-time Cube Analytics},
author={Alallah, Fouad and Faleel, Shariff and Sakamoto, Yumiko and Rey, Bradley and Irani, Pourang},
year={2022},
publisher={The Eurographics Association}
}