A Study of Layout, Rendering, and Interaction Methods for Immersive Graph Visualization

Kwon, Oh-Hyun; Muelder, Chris; Lee, Kyungwon; Ma, Kwan‐Liu

doi:10.1109/tvcg.2016.2520921

Cited by 160 publications

(126 citation statements)

References 42 publications

Supporting

Mentioning

121

Contrasting

Unclassified

Order By: Relevance

“…We share the belief that egocentric data views are a unique strength of virtual environments to provide a new perspective on the data that cannot be easily obtained on a desktop screen. In contrast to Kwon et al [8], [27], however, we also believe that a conventional exocentric view on a network provides a visual anchor for orientation and overview. In contrast to these prior works, we therefore present and explore a new immersive network analytics approach, where users can flexibly switch between an exocentric overview and an egocentric detail view.…”

Section: Related Workcontrasting

confidence: 88%

Immersive Analytics of Large Dynamic Networks via Overview and Detail Navigation

Sorger

Waldner

Knecht

et al. 2019

2019 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR)

View full text Add to dashboard Cite

Analysis of large dynamic networks is a thriving research field, typically relying on 2D graph representations. The advent of affordable head mounted displays however, sparked new interest in the potential of 3D visualization for immersive network analytics. Nevertheless, most solutions do not scale well with the number of nodes and edges and rely on conventional fly-or walk-through navigation. In this paper, we present a novel approach for the exploration of large dynamic graphs in virtual reality that interweaves two navigation metaphors: overview exploration and immersive detail analysis. We thereby use the potential of state-of-the-art VR headsets, coupled with a web-based 3D rendering engine that supports heterogeneous input modalities to enable ad-hoc immersive network analytics. We validate our approach through a performance evaluation and a case study with experts analyzing a co-morbidity network.

show abstract

Section: Related Workcontrasting

confidence: 88%

Immersive Analytics of Large Dynamic Networks via Overview and Detail Navigation

Sorger

Waldner

Knecht

et al. 2019

2019 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR)

View full text Add to dashboard Cite

show abstract

“…Researchers have noted that display sizes strongly affect the usability of scatterplots [4]. They have studied the effect of display sizes on design decisions of scatterplots, such as interactions on mobile phones [23,29], cognitive processes on large high-resolution displays [3], and graph layouts in immersive environments [38]. Moreover, the advances in display technology invoke new scenarios for exploratory analysis.…”

Section: Visual Encodings Of Scatterplotmentioning

confidence: 99%

Evaluating Perceptual Bias During Geometric Scaling of Scatterplots

Wei

Mei

Zhao

et al. 2020

IEEE Trans. Visual. Comput. Graphics

View full text Add to dashboard Cite

Scatterplots are frequently scaled to fit display areas in multi-view and multi-device data analysis environments. A common method used for scaling is to enlarge or shrink the entire scatterplot together with the inside points synchronously and proportionally. This process is called geometric scaling. However, geometric scaling of scatterplots may cause a perceptual bias, that is, the perceived and physical values of visual features may be dissociated with respect to geometric scaling. For example, if a scatterplot is projected from a laptop to a large projector screen, then observers may feel that the scatterplot shown on the projector has fewer points than that viewed on the laptop. This paper presents an evaluation study on the perceptual bias of visual features in scatterplots caused by geometric scaling. The study focuses on three fundamental visual features (i.e., numerosity, correlation, and cluster separation) and three hypotheses that are formulated on the basis of our experience. We carefully design three controlled experiments by using well-prepared synthetic data and recruit participants to complete the experiments on the basis of their subjective experience. With a detailed analysis of the experimental results, we obtain a set of instructive findings. First, geometric scaling causes a bias that has a linear relationship with the scale ratio. Second, no significant difference exists between the biases measured from normally and uniformly distributed scatterplots. Third, changing the point radius can correct the bias to a certain extent. These findings can be used to inspire the design decisions of scatterplots in various scenarios.

show abstract

“…Particular use cases include 3D graph layout e.g. [12,33,41,59] and multivariate data visualisation, e.g. [7,11].…”

Section: Immersive Analyticsmentioning

confidence: 99%

Origin-Destination Flow Maps in Immersive Environments

Yang

Dwyer

Jenny

et al. 2019

IEEE Trans. Visual. Comput. Graphics

View full text Add to dashboard Cite

Immersive virtual- and augmented-reality headsets can overlay a flat image against any surface or hang virtual objects in the space around the user. The technology is rapidly improving and may, in the long term, replace traditional flat panel displays in many situations. When displays are no longer intrinsically flat, how should we use the space around the user for abstract data visualisation? In this paper, we ask this question with respect to origin-destination flow data in a global geographic context. We report on the findings of three studies exploring different spatial encodings for flow maps. The first experiment focuses on different 2D and 3D encodings for flows on flat maps. We find that participants are significantly more accurate with raised flow paths whose height is proportional to flow distance but fastest with traditional straight line 2D flows. In our second and third experiment we compared flat maps, 3D globes and a novel interactive design we call MapsLink, involving a pair of linked flat maps. We find that participants took significantly more time with MapsLink than other flow maps while the 3D globe with raised flows was the fastest, most accurate, and most preferred method. Our work suggests that careful use of the third spatial dimension can resolve visual clutter in complex flow maps.

show abstract

A Study of Layout, Rendering, and Interaction Methods for Immersive Graph Visualization

Cited by 160 publications

References 42 publications

Immersive Analytics of Large Dynamic Networks via Overview and Detail Navigation

Immersive Analytics of Large Dynamic Networks via Overview and Detail Navigation

Evaluating Perceptual Bias During Geometric Scaling of Scatterplots

Origin-Destination Flow Maps in Immersive Environments

Contact Info

Product

Resources

About