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2020 | OriginalPaper | Chapter

Breaking the Curse of Visual Analytics: Accommodating Virtual Reality in the Visualization Pipeline

Authors : Matthias Kraus, Matthias Miller, Juri Buchmüller, Manuel Stein, Niklas Weiler, Daniel A. Keim, Mennatallah El-Assady

Published in: Computer Vision, Imaging and Computer Graphics Theory and Applications

Publisher: Springer International Publishing

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Abstract

Previous research has exposed the discrepancy between the subject of analysis (real world) and the actual data on which the analysis is performed (data world) as a critical weak spot in visual analysis pipelines. In this paper, we demonstrate how Virtual Reality (VR) can help to verify the correspondence of both worlds in the context of Information Visualization (InfoVis) and Visual Analytics (VA). Immersion allows the analyst to dive into the data world and collate it to familiar real-world scenarios. If the data world lacks crucial dimensions, then these are also missing in created virtual environments, which may draw the analyst’s attention to inconsistencies between the database and the subject of analysis. When situating VR in a generic visualization pipeline, we can confirm its basic equality compared to other mediums as well as possible benefits. To overcome the guarded stance of VR in InfoVis and VA, we present a structured analysis of arguments, exhibiting the circumstances that make VR a viable medium for visualizations. As a further contribution, we discuss how VR can aid in minimizing the gap between the data world and the real world and present a use case that demonstrates two solution approaches. Finally, we report on initial expert feedback attesting the applicability of our approach in a real-world scenario for crime scene investigation.

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Title: Breaking the Curse of Visual Analytics: Accommodating Virtual Reality in the Visualization Pipeline
Authors: Matthias Kraus
Matthias Miller
Juri Buchmüller
Manuel Stein
Niklas Weiler
Daniel A. Keim
Mennatallah El-Assady
Publisher: Springer International Publishing
Book: Computer Vision, Imaging and Computer Graphics Theory and Applications
Print ISBN: 978-3-030-41589-1

Electronic ISBN: 978-3-030-41590-7

Copyright Year: 2020
DOI: https://doi.org/10.1007/978-3-030-41590-7_11

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