Immersive Analytics 2.0: Spatial and Embodied Sensemaking

被引:6
作者
Ens, Barrett [1 ]
Cordeil, Maxime [1 ,2 ]
North, Chris [3 ]
Dwyer, Tim [1 ]
Besancon, Lonni [1 ]
Prouzeau, Arnaud [4 ,5 ]
Liu, Jiazhou [1 ]
Cunningham, Andrew [6 ]
Drogemuller, Adam [6 ]
Satriadi, Kadek Ananta [7 ]
Thomas, Bruce H. [7 ]
机构
[1] Monash Univ, Melbourne, Vic, Australia
[2] Univ Queensland, Brisbane, Qld, Australia
[3] Virginia Tech, Blacksburg, VA USA
[4] Inria, Paris, France
[5] Univ Bordeaux, CNRS, Bordeaux INP, LaBRI, Bordeaux, France
[6] Univ South Australia, Adelaide, SA, Australia
[7] Univ South Australia, Mawson Lakes, SA, Australia
来源
EXTENDED ABSTRACTS OF THE 2022 CHI CONFERENCE ON HUMAN FACTORS IN COMPUTING SYSTEMS, CHI 2022 | 2022年
关键词
Immersive Analytics; Sensemaking; Spatial User Interfaces; Embodied Interaction;
D O I
10.1145/3491101.3503726
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
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.
引用
收藏
页数:7
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