Immersive Analytics 2.0: Spatial and Embodied Sensemaking

意会 具身认知 计算机科学 分析 文化分析 人机交互 虚拟现实 可视化 数据科学 视觉分析 领域(数学) 增强现实 数据可视化 混合现实 语义分析 万维网 人工智能 数据网 纯数学 Web服务 数学
作者
Barrett Ens,Maxime Cordeil,Chris North,Tim Dwyer,Lonni Besançon,Arnaud Prouzeau,Jiazhou Liu,Andrew Cunningham,Adam Drogemuller,Kadek Ananta Satriadi,Bruce H. Thomas
标识
DOI:10.1145/3491101.3503726
摘要

Immersive Analytics is now a fully emerged research topic that spans several research communities, including Human-Computer Interaction, Data Visualisation, Virtual Reality and Augmented Reality. Immersive Analytics research has identified and validated benefits of using embodied, 3D spatial immersive environments for visualisation and have shown benefits in the effective use of space and 3D interaction to explore complex data. As of today, most studies in Immersive Analytics have focused on exploring novel visualisation techniques in 3D embodied immersive environments. Thus far, there is a lack of fundamental study in this field that clearly compares immersive versus non immersive platforms for analytics purposes, and firmly delineates the benefits of immersive environments for analytic tasks. We feel that it is time to establish an agenda to assess the benefits and potential of immersive technologies, spatial interfaces, and embodied interaction to support sensemaking, data understanding, and collaborative analytics. This workshop will aim at putting this agenda together, by gathering international experts from Immersive Analytics and related fields to define which studies need to be conducted to assess the effect of embodied interaction on cognition in data analytics.

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