A study of mental maps in immersive network visualization

Joseph Kotlarek, Oh-Hyun Kwon, Kwan-Liu Ma, Peter Eades, Andreas Kerren, Karsten Klein, Falk Schreiber

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

1 Citation (Scopus)

Abstract

The visualization of a network influences the quality of the mental map that the viewer develops to understand the network. In this study, we investigate the effects of a 3D immersive visualization environment compared to a traditional 2D desktop environment on the comprehension of a network's structure. We compare the two visualization environments using three tasks - interpreting network structure, memorizing a set of nodes, and identifying the structural changes - commonly used for evaluating the quality of a mental map in network visualization. The results show that participants were able to interpret network structure more accurately when viewing the network in an immersive environment, particularly for larger networks. However, we found that 2D visualizations performed better than immersive visualization for tasks that required spatial memory.

Original languageEnglish
Title of host publication2020 IEEE Pacific Visualization Symposium (PacificVis)
Subtitle of host publicationTianjin, China, 14–17 April, 2020, Proceedings
EditorsFabian Beck, Jinwook Seo, Chaoli Wang
Place of PublicationPiscataway NJ USA
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages1-10
Number of pages10
ISBN (Electronic)9781728156972
ISBN (Print)9781728156989
DOIs
Publication statusPublished - 2020
Externally publishedYes
EventIEEE Pacific Visualization Symposium 2020 - Tianjin, China
Duration: 3 Jun 20205 Jun 2020
Conference number: 13th
https://ieeexplore.ieee.org/xpl/conhome/9082508/proceeding (Proceedings)
http://vis.tju.edu.cn/pvis2020/ (Website)

Publication series

NameIEEE Pacific Visualization Symposium
PublisherIEEE, Institute of Electrical and Electronics Engineers
Volume2020-June
ISSN (Print)2165-8765
ISSN (Electronic)2165-8773

Conference

ConferenceIEEE Pacific Visualization Symposium 2020
Abbreviated titlePacificVis 2020
CountryChina
CityTianjin
Period3/06/205/06/20
Internet address

Keywords

  • Empirical studies in visualization
  • Graph drawings
  • Human-centered computing
  • Visualization
  • Visualization techniques

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