Grand challenges in immersive analytics

Images from 10 different Immersive Analytics systems in use.
Illustration of several recent Immersive Analytics systems.
Abstract
Immersive Analytics is a quickly evolving field that unites several areas such as visualisation, immersive environments, and human-computer interaction to support human data analysis with emerging technologies. This research has thrived over the past years with multiple workshops, seminars, and a growing body of publications, spanning several conferences. Given the rapid advancement of interaction technologies and novel application domains, this paper aims toward a broader research agenda to enable widespread adoption. We present 17 key research challenges developed over multiple sessions by a diverse group of 24 international experts, initiated from a virtual scientific workshop at ACM CHI 2020. These challenges aim to coordinate future work by providing a systematic roadmap of current directions and impending hurdles to facilitate productive and effective applications for Immersive Analytics.
Materials
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Authors
Barrett Ens
Benjamin Bach
Maxime Cordeil
Ulrich Engelke
Marcos Serrano
Wesley Willett
Arnaud Prouzeau
Christoph Anthes
Wolfgang Büschel
Tim Dwyer
Jens Grubert
Jason H. Haga
Nurit Kirshenbaum
Dylan Kobayashi
Tica Lin
Monsurat Olaosebikan
Fabian Pointecker
Nazmus Saquib
Dieter Schmalstieg
Danielle Albers Szafir
Matt Whitlock
Yalong Yang
Citation
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Grand challenges in immersive analytics

Barrett Ens, Benjamin Bach, Maxime Cordeil, Ulrich Engelke, Marcos Serrano, Wesley Willett, Arnaud Prouzeau, Christoph Anthes, Wolfgang Büschel, Cody Dunne, Tim Dwyer, Jens Grubert, Jason H. Haga, Nurit Kirshenbaum, Dylan Kobayashi, Tica Lin, Monsurat Olaosebikan, Fabian Pointecker, David Saffo, Nazmus Saquib, Dieter Schmalstieg, Danielle Albers Szafir, Matt Whitlock, and Yalong Yang. In Proc. CHI Conference on Human Factors in Computing Systems—CHI. 2021. DOI: 10.1145/3411764.3446866

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