Replication Data for: Towards a Better Understanding of Graph Perception in Immersive Environments

Kurzanzeige
creativework.versionV1
dc.contributor.authorWang, Yao
dc.contributor.authorZhang, Lin
dc.contributor.authorZhang, Ying
dc.contributor.authorKerle-Malcharek, Wilhelm
dc.contributor.authorKlein, Karsten
dc.contributor.authorSchreiber, Falk
dc.contributor.authorBulling, Andreas
dc.date.accessioned2025-11-07T08:37:15Z
dc.date.available2025-11-07T08:37:15Z
dc.date.created2025-08-12T13:23:46Z
dc.date.issued2025
dc.description.abstractAs Immersive Analytics (IA) increasingly uses Virtual Reality (VR) for stereoscopic 3D (S3D) graph visualisation, it is crucial to understand how users perceive network structures in these immersive environments. However, little is known about how humans read S3D graphs during task solving, and how gaze behaviour indicates task performance. To address this gap, we report a user study with 18 participants asked to perform three analytical tasks on S3D graph visualisations in a VR environment. Our findings reveal systematic relationships between network structural properties and gaze behaviour. Based on these insights, we contribute a comprehensive eye tracking methodology for analysing human perception in immersive environments and establish eye tracking as a valuable tool for objectively evaluating cognitive load in S3D graph visualisation. The files of this dataset are documented in <a href="https://darus.uni-stuttgart.de/file.xhtml?fileId=415768">README.md</a>.
dc.description.versionpublisheddeu
dc.identifier.doi10.18419/darus-5259
dc.identifier.urihttps://kops.uni-konstanz.de/handle/123456789/75140
dc.language.isoeng
dc.subjectComputer and Information Science
dc.subjectInformation Visualization
dc.subjectData Visualization
dc.subjectVisual analytics
dc.subjectVirtual reality
dc.subjectImage and Language Processing, Computer Graphics and Visualisation, Human Computer Interaction, Ubiquitous and Wearable Computing
dc.subject.ddc004
dc.titleReplication Data for: Towards a Better Understanding of Graph Perception in Immersive Environmentseng
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kops.citation.iso690WANG,  Yao,  Lin ZHANG,  Ying ZHANG,  Wilhelm KERLE-MALCHAREK,  Karsten KLEIN,  Falk SCHREIBER,  Andreas BULLING, 2025. Replication Data for: Towards a Better Understanding of Graph Perception in Immersive Environmentsdeu
kops.citation.iso690WANG,  Yao,  Lin ZHANG,  Ying ZHANG,  Wilhelm KERLE-MALCHAREK,  Karsten KLEIN,  Falk SCHREIBER,  Andreas BULLING, 2025. Replication Data for: Towards a Better Understanding of Graph Perception in Immersive Environmentseng
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However, little is known about how humans read S3D graphs during task solving, and how gaze behaviour indicates task performance.
To address this gap, we report a user study with 18 participants asked to perform three analytical tasks on S3D graph visualisations in a VR environment.
Our findings reveal systematic relationships between network structural properties and gaze behaviour. Based on these insights, we contribute a comprehensive eye tracking methodology for analysing human perception in immersive environments and establish eye tracking as a valuable tool for objectively evaluating cognitive load in S3D graph visualisation. 
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kops.datacite.repositoryUniversitätsbibliothek Stuttgart
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