Grand Challenges in Immersive Analytics
Haga, Jason H.
Szafir, Danielle Albers
Grand Research Challenges
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AbstractImmersive 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.
CitationEns, Barrett, Bach, B., Cordeil, M., Engelke, U., Serrano, M., Willett, W. J., Prouzeau, A., Anthes, C., Büschel, W., Dunne, C., Dwyer, T., Grubert, J., Haga, J. H., Kirshenbaum, N., Kobayashi, D., Lin, T., Olaosebikan, M., Pointecker, F., Saffo, D., ... Yang, Y. (2021). Grand Challenges in Immersive Analytics. In "CHI Conference on Human Factors in Computing Systems (CHI’21), May 8–13, 2021, Yokohama, Japan". ACM, New York, NY, USA, 1-17 pp. https://doi.org/10.1145/3411764.3446866
University of Calgary
University of Edinburgh
University of Toulouse
University of Applied Sciences, Upper Austria
Technische Universität Dresden
Coburg University of Applied Sciences and Arts
National Institute of Advanced Industrial Science and Technology (AIST), Tokyo
University of Hawaii at Manoa
MIT Media Lab
Graz University of Technology
University of Colorado Boulder
PublisherACM : New York, New York
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