Encountered Haptic Feedback for Data Analytics in Immersive Environments

This thesis investigates encountered-type haptic feedback to enhance immersive analytics (IA), addressing the over-reliance on visual modalities in VR/AR and scalability limitations of data physicalization. Four objectives guide the research: (1) developing reconfigurable haptic tools for precise 3D data manipulation, (2) mitigating spatial navigation challenges via focus-and-context techniques with haptic guidance, (3) enabling collaborative workflows using autonomous physical proxies, and (4) systematising a design space with 11 dimensions to unify multi-sensory visualisation strategies. By integrating tactile feedback into IA, this work bridges gaps between digital and physical interaction paradigms, expanding foundational visualisation models to prioritise multi-sensory encoding for future analytical workflows.