DataHop: Spatial Data Exploration in Virtual Reality

Hayatpur, Devamardeep; Xia, Haijun; Wigdor, Daniel

doi:10.1145/3379337.3415878

Cited by 42 publications

(23 citation statements)

References 32 publications

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“…However, supporting the ability to design and create visualisations using immersive technologies is a necessary step to create complete systems. Some works have started to explore this direction, such as ImAxes [9], which focused on the use of embodied interactions to create visualisations, DataHop [15], which explored how to use the space to organise the analyse, and Corsican Twin [22], which used digital twins for authoring situated and embedded visualisations, but a vast space still needs to be explored. Research opportunities in this area are on the authoring of more complex visualisations, the study of the impact of embodied and spatial methods on the creation process and on the authoring of interactive visualisations.…”

Section: Perspectives Of Interestmentioning

confidence: 99%

Immersive Analytics 2.0: Spatial and Embodied Sensemaking

Ens

Cordeil

North

et al. 2022

CHI Conference on Human Factors in Computing Systems Extended Abstracts

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Immersive Analytics is now a fully emerged research topic that spans several research communities, including Human-Computer Interaction, Data Visualisation, Virtual Reality and Augmented Reality. Immersive Analytics research has identifed and validated benefts of using embodied, 3D spatial immersive environments for visualisation and have shown benefts in the efective use of space and 3D interaction to explore complex data. As of today, most studies in Immersive Analytics have focused on exploring novel visualisation techniques in 3D embodied immersive environments. Thus far, there is a lack of fundamental study in this feld that clearly compares immersive versus non immersive platforms for analytics purposes, and frmly delineates the benefts of immersive environments for analytic tasks. We feel that it is time to establish an agenda to assess the benefts and potential of immersive technologies, spatial interfaces, and embodied interaction to support sensemaking, data understanding, and collaborative analytics. This workshop will aim at putting this agenda together, by gathering international experts from Immersive Analytics and related felds to defne which studies need to be conducted to assess the efect of embodied interaction on cognition in data analytics.

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Section: Perspectives Of Interestmentioning

confidence: 99%

Immersive Analytics 2.0: Spatial and Embodied Sensemaking

Ens

Cordeil

North

et al. 2022

CHI Conference on Human Factors in Computing Systems Extended Abstracts

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“…Besides such typical approaches that are concerned with the visualization of network or hierarchical data, other visualizations exist that fall into the same category of 'node-link graphs'. For instance, Hayatpur et al [HXW20] present a visualization approach for analytics provenance graphs, which are generated throughout analysis procedures. Even though this is not a typical graph visualization problem, it still is, in principle, a node-link graph visualization of abstract data.…”

Section: Analytic Provenance and Processes As Graphs -mentioning

confidence: 99%

“…Making use of the huge space provided in virtual environments, Hayatpur et al . [HXW20] try to exploit the ‘endless’ workspace available in VR and present a technique for analytic provenance in which analysis steps are spatially lay‐outed and can be explored by the user.…”

Section: Literature Reviewmentioning

confidence: 99%

“…[HXW20] try to exploit the 'endless' workspace available in VR and present a technique for analytic provenance in which analysis steps are spatially lay-outed and can be explored by the user.Other works adopt and extend or modify existing visualizations. For instance, Mota et al [MRS*18] present 3De Interactive Lenses, a technique for focus&context flow visualizations of multigeometry data and Kraus et al [KAB*20] present a technique for the comparative analysis of 3D distributions in VR environments.…”

mentioning

confidence: 99%

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Immersive Analytics with Abstract 3D Visualizations: A Survey

Kraus

Fuchs

Sommer

et al. 2021

Computer Graphics Forum

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After a long period of scepticism, more and more publications describe basic research but also practical approaches to how abstract data can be presented in immersive environments for effective and efficient data understanding. Central aspects of this important research question in immersive analytics research are concerned with the use of 3D for visualization, the embedding in the immersive space, the combination with spatial data, suitable interaction paradigms and the evaluation of use cases. We provide a characterization that facilitates the comparison and categorization of published works and present a survey of publications that gives an overview of the state of the art, current trends, and gaps and challenges in current research.

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“…VR and AR [21] headsets provide immersion, 3D input, and enhanced depth cues, in particular head-coupled motion and stereo disparity [20], [22], [23]. Recent uses of these platforms for information visualization include ImAxes [24] and DataHop [25]. Input to such systems is often via handheld controllers or whole hands.…”

Section: Introductionmentioning

confidence: 99%

Path Tracing in 2D, 3D, and Physicalized Networks

McGuffin¹,

Servera²,

Forest³

2022

Preprint

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It is common to advise against using 3D to visualize abstract data such as networks, however Ware and Mitchell's 2008 study showed that path tracing in a network is less error prone in 3D than in 2D. It is unclear, however, if 3D retains its advantage when the 2D presentation of a network is improved using edge-routing, and when simple interaction techniques for exploring the network are available. We address this with two studies of path tracing under new conditions. The first study was preregistered, involved 34 users, and compared 2D and 3D layouts that the user could rotate and move in virtual reality with a handheld controller. Error rates were lower in 3D than in 2D, despite the use of edge-routing in 2D and the use of mouse-driven interactive highlighting of edges. The second study involved 12 users and investigated data physicalization, comparing 3D layouts in virtual reality versus physical 3D printouts of networks augmented with a Microsoft HoloLens headset. No difference was found in error rate, but users performed a variety of actions with their fingers in the physical condition which can inform new interaction techniques.

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DataHop: Spatial Data Exploration in Virtual Reality

Cited by 42 publications

References 32 publications

Immersive Analytics 2.0: Spatial and Embodied Sensemaking

Immersive Analytics 2.0: Spatial and Embodied Sensemaking

Immersive Analytics with Abstract 3D Visualizations: A Survey

Path Tracing in 2D, 3D, and Physicalized Networks

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