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A Novel Interaction Paradigm For Exploring Spatio-Temporal Data

Sabine Cassat, Marcos Serrano, Emmanuel Dubois, Pourang Irani

Year
2018
Citations
2
Access
Open access

Abstract

Complex spatio-temporal data is difficult to visualize and even further to interact with, especially by several users at the same time. However, visualization and exploration of such data are essential for experts to understand complex data environments, such as for mitigating the adverse effects of disease spread. This paper presents an alternative approach to that of current spatiotemporal data visualizations to access, interpret, and manipulate spatio-temporal datasets as a single user or as a team. Our approach uses tangible and visual tools such as mini-robots, tabletop displays and augmented reality tools, to facilitate the data exploration and interpretation. We also introduce a simple use case that illustrates one of the possible utilization of the system. While tangibles have been introduced to represent information, we are investigating manners in which we can depict even more complex datasets. Our system will provide a novel approach to manipulate 3D and 4D datasets that classic tools such as a 2D mouse or a tactile screen would not allow.

Keywords

Computer scienceVisualizationHuman–computer interactionData visualizationRobotData explorationAugmented realityData scienceArtificial intelligence

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