학술논문
Grand Challenges in Immersive Analytics
Document Type
Conference
Author
Ens, Barrett; Bach, Benjamin; Cordeil, Maxime; Engelke, Ulrich; Serrano, Marcos; Willett, Wesley; Prouzeau, Arnaud; Anthes, Christoph; Büschel, Wolfgang; Dunne, Cody; Dwyer, Tim; Grubert, Jens; Haga, Jason H.; Kirshenbaum, Nurit; Kobayashi, Dylan; Lin, Tica; Olaosebikan, Monsurat; Pointecker, Fabian; Saffo, David; Saquib, Nazmus; Schmalstieg, Dieter; Szafir, Danielle Albers; Whitlock, Matt; Yang, Yalong
Source
Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems. :1-17
Subject
Language
English
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.