Sangam: A Confluence of Knowledge Streams

Immersive Analytics 2.0: Spatial and Embodied Sensemaking

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dc.creator Ens, Barrett
dc.creator Cordeil, Maxime
dc.creator North, Chris
dc.creator Dwyer, Tim
dc.creator Besançon, Lonni
dc.creator Prouzeau, Arnaud
dc.creator Liu, Jiazhou
dc.creator Cunningham, Andrew
dc.creator Drogemuller, Adam
dc.creator Satriadi, Kadek Ananta
dc.creator Thomas, Bruce
dc.date 2022-10-19T16:57:13Z
dc.date 2022-10-19T16:57:13Z
dc.date 2022-04-27
dc.date 2022-10-19T15:08:20Z
dc.date.accessioned 2023-03-01T18:51:38Z
dc.date.available 2023-03-01T18:51:38Z
dc.identifier http://hdl.handle.net/10919/112220
dc.identifier https://doi.org/10.1145/3491101.3503726
dc.identifier.uri http://localhost:8080/xmlui/handle/CUHPOERS/281532
dc.description 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 identifed 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.
dc.description Published version
dc.format application/pdf
dc.format application/pdf
dc.language en
dc.publisher ACM
dc.rights In Copyright
dc.rights http://rightsstatements.org/vocab/InC/1.0/
dc.rights The author(s)
dc.title Immersive Analytics 2.0: Spatial and Embodied Sensemaking
dc.type Article - Refereed
dc.type Text


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