Visual Analytics on Large Displays: Exploring User Spatialization and How Size and Resolution Affect Task Performance

Cetin, Gokhan; Stuerzlinger, Wolfgang; Dill, John

doi:10.1109/bdva.2018.8534027

Cited by 6 publications

(1 citation statement)

References 92 publications

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“…All plots are coordinated through brushing and linking. DynSpace was designed to aid analysis of complex datasets [34]. Initially it displays a number of charts, each generated automatically by picking random pairs of data dimensions.…”

Section: Common Software Platformmentioning

confidence: 99%

Immersive Analytics Sensemaking on Different Platforms

Blum¹,

Cetin²,

Stuerzlinger³

2019

Computer Science Research Notes

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In this work we investigated sensemaking activities on different immersive platforms. We observed user s during a classification task on a very large wall-display system (experiment I) and in a modern Virtual Reality headset (experiment II). In experiment II, we also evaluated a condition with a VR headset with an extended field of view, through a sparse peripheral display. We evaluated the results across the two studies by analyzing quantitative and qualitative data, such as task completion time, number of classifications, followed strategies, and shape of clusters. The results showed differences in user behaviors between the different immersive platforms, i.e., the very large display wall and the VR headset. Even though quantitative data showed no significant differences, qualitatively, users used additional strategies on the wall-display, which hints at a deeper level of sensemaking compared to a VR Headset. The qualitative and quantitative results of the comparison between VR Headsets do not indicate that users perform differently with a VR Headset with an extended field of view.

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Section: Common Software Platformmentioning

confidence: 99%