Building Multiple Coordinated Spaces for Effective Immersive Analytics through Distributed Cognition

Mahmood, Tahir; Butler, Erik; Davis, Nicholas; Huang, Jian; Lu, Aidong

doi:10.1109/bdva.2018.8533893

Cited by 29 publications

(15 citation statements)

References 42 publications

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“…Study relevance. Although research in AR/VR with multiview settings exist (e. g., [32]), the interaction requirements of 3D data visualization usually differ from those in other use cases, specifically the demand of high-precision work. For 3D selection, e. g., common methods like ray-casting are unsuitable for scientific datasets because they usually do not natively define objects or regions [9].…”

Section: Design Choicesmentioning

confidence: 99%

Towards an Understanding of Augmented Reality Extensions for Existing 3D Data Analysis Tools

Wang

Besançon

Rousseau

et al. 2020

Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

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We present an observational study with domain experts to understand how augmented reality (AR) extensions to traditional PC-based data analysis tools can help particle physicists to explore and understand 3D data. Our goal is to allow researchers to integrate stereoscopic AR-based visual representations and interaction techniques into their tools, and thus ultimately to increase the adoption of modern immersive analytics techniques in existing data analysis workflows. We use Microsoft's HoloLens as a lightweight and easily maintainable AR headset and replicate existing visualization and interaction capabilities on both the PC and the AR view. We treat the AR headset as a second yet stereoscopic screen, allowing researchers to study their data in a connected multi-view manner. Our results indicate that our collaborating physicists appreciate a hybrid data exploration setup with an interactive AR extension to improve their understanding of particle collision events.

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Section: Design Choicesmentioning

confidence: 99%

Towards an Understanding of Augmented Reality Extensions for Existing 3D Data Analysis Tools

Wang

Besançon

Rousseau

et al. 2020

Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

View full text Add to dashboard Cite

show abstract

“…With these separate views of individual layers taking up more visual space than a single one combining them, immersive systems offer a solution through their virtually limitless visual space, and the call for them to be thus utilized in immersive analytics (Knudsen, Carpendale, 2017) is beginning to get answered. AR systems can project virtual screens of information anywhere in a real room (Mahmood et al, 2018, Cavallo et al, 2019, and VR is able to construct any desired configuration.…”

Section: Multiple and Coordinated Viewsmentioning

confidence: 99%

Visualizing Multilayered Geospatial Data in Virtual Reality to Assess Public Lighting

Spur

Houel

Tourre

2020

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. With the improvement and proliferation of virtual reality devices, their use for research and professional activity is broadening, fostering the advent of the field of immersive analytics, as is their acceptance among consumers. Other than the heightened sense of immersion into visualized data they provide, they also make displays of much larger apparent size and different positioning practical than what would be possible otherwise. Drawing on these benefits, we implemented a development of Multiple and Coordinated Displays (MCVs) for geovisualization that stacks different layers of data above each other, tilted for legibility. In a formal experiment, we evaluated it and two other, comparable MCV methods implemented in VR for their usefulness in analyzing public perception and soliciting public feedback regarding urban street lighting. In that field, the direction has recently been shifting from purely systemic development to a participatory approach, thus our investigation was into how a system like this could facilitate participation that can yield actionable results. Previous analysis of interaction data and usability questionnaires reveals preferences for certain systems depending on user characteristics, with the stack system showing a slight advantage over a grid of layers and especially over temporal multiplexing. We show that regardless of MCV variation, participants were able to analyze and provide feedback on public lighting situations that can directly contribute to urbanist work. The MCV approach further aided in understanding their choices, as eye-tracking allowed us to analyze attention to individual data layers.

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“…In [29], arguments for immersive analytics are reiterated, with a call for more research into its application to coordinated and multiple views (interchangeably abbreviated to CMVs or MVCs) [6]-a powerful form of composite visualization by juxtaposition [12]. Many of the systems mentioned above contain MCVs in the shape of a map view augmented by connected tables or charts, others [30,31] also link related maps in innovative ways. While studies have been conducted to explore and compare the efficacy of different compositions of such coordinated geospatial map views [5], to our knowledge they have so far only evaluated the case of two map layers, and also not within immersive environments.…”

Section: Multiple and Coordinated Viewsmentioning

confidence: 99%

Exploring Multiple and Coordinated Views for Multilayered Geospatial Data in Virtual Reality

et al. 2020

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Virtual reality (VR) headsets offer a large and immersive workspace for displaying visualizations with stereoscopic vision, as compared to traditional environments with monitors or printouts. The controllers for these devices further allow direct three-dimensional interaction with the virtual environment. In this paper, we make use of these advantages to implement a novel multiple and coordinated view (MCV) system in the form of a vertical stack, showing tilted layers of geospatial data. In a formal study based on a use-case from urbanism that requires cross-referencing four layers of geospatial urban data, we compared it against more conventional systems similarly implemented in VR: a simpler grid of layers, and one map that allows for switching between layers. Performance and oculometric analyses showed a slight advantage of the two spatial-multiplexing methods (the grid or the stack) over the temporal multiplexing in blitting. Subgrouping the participants based on their preferences, characteristics, and behavior allowed a more nuanced analysis, allowing us to establish links between e.g., saccadic information, experience with video games, and preferred system. In conclusion, we found that none of the three systems are optimal and a choice of different MCV systems should be provided in order to optimally engage users.

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Building Multiple Coordinated Spaces for Effective Immersive Analytics through Distributed Cognition

Cited by 29 publications

References 42 publications

Towards an Understanding of Augmented Reality Extensions for Existing 3D Data Analysis Tools

Towards an Understanding of Augmented Reality Extensions for Existing 3D Data Analysis Tools

Visualizing Multilayered Geospatial Data in Virtual Reality to Assess Public Lighting

Exploring Multiple and Coordinated Views for Multilayered Geospatial Data in Virtual Reality

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