Grand Challenges in Immersive Analytics

Research output: Contribution to book/conference proceedings/anthology/reportConference contributionContributedpeer-review

Contributors

  • Barrett Ens - (Author)
  • Benjamin Bach - (Author)
  • Maxime Cordeil - (Author)
  • Ulrich Engelke - (Author)
  • Marcos Serrano - (Author)
  • Wesley Willett - (Author)
  • Arnaud Prouzeau - (Author)
  • Christoph Anthes - (Author)
  • Wolfgang Büschel - , Chair of Multimedia Technology (Author)
  • Cody Dunne - (Author)
  • Tim Dwyer - (Author)
  • Jens Grubert - (Author)
  • Jason H. Haga - (Author)
  • Nurit Kirshenbaum - (Author)
  • Dylan Kobayashi - (Author)
  • Tica Lin - (Author)
  • Monsurat Olaosebikan - (Author)
  • Fabian Pointecker - (Author)
  • David Saffo - (Author)
  • Nazmus Saquib - (Author)
  • Dieter Schmalstieg - (Author)
  • Danielle Albers Szafir - (Author)
  • Matt Whitlock - (Author)
  • Yalong Yang - (Author)

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.

Details

Original languageEnglish
Title of host publicationCHI '21: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems
Place of PublicationNew York, NY, USA
PublisherAssociation for Computing Machinery (ACM), New York
ISBN (print)9781450380966
Publication statusPublished - Jun 2021
Peer-reviewedYes

External IDs

ORCID /0000-0002-3548-723X/work/142245497
Scopus 85137078246
Mendeley 01c4dce8-59b2-3e61-9c07-65220aab8c3c

Keywords

Keywords

  • Immersive analytics, augmented reality, data visualisation, grand research challenges, virtual reality, Data visualisation, Grand research challenges, Virtual reality, Augmented reality