Utilization of variation in stereoscopic depth for encoding aspects of non-spatial data

AlTarawneh, Ragaad; Humayoun, Shah Rukh; Ebert, Achim

doi:10.1109/3dui.2015.7131741

Cited by 2 publications

(2 citation statements)

References 3 publications

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“…This data representation was used by Elmqvist et al who investigated the benefit of motion constraints for navigating complex 3D environments [ETT08]. Moreover, we also found a compound graph which combines a matrix representation and node‐link diagrams [AHE16]…”

Section: Resultsmentioning

confidence: 93%

A Systematic Literature Review of User Evaluation in Immersive Analytics

Friedl‐Knirsch,

Pointecker,

Pfistermüller

et al. 2024

Computer Graphics Forum

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User evaluation is a common and useful tool for systematically generating knowledge and validating novel approaches in the domain of Immersive Analytics. Since this research domain centres around users, user evaluation is of extraordinary relevance. Additionally, Immersive Analytics is an interdisciplinary field of research where different communities bring in their own methodologies. It is vital to investigate and synchronise these different approaches with the long‐term goal to reach a shared evaluation framework. While there have been several studies focusing on Immersive Analytics as a whole or on certain aspects of the domain, this is the first systematic review of the state of evaluation methodology in Immersive Analytics. The main objective of this systematic literature review is to illustrate methodologies and research areas that are still underrepresented in user studies by identifying current practice in user evaluation in the domain of Immersive Analytics in coherence with the PRISMA protocol. (see https://www.acm.org/publications/class-2012)

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Section: Resultsmentioning

confidence: 93%

A Systematic Literature Review of User Evaluation in Immersive Analytics

Friedl‐Knirsch,

Pointecker,

Pfistermüller

et al. 2024

Computer Graphics Forum

View full text Add to dashboard Cite

show abstract

“…The method of compound graphs is also employed in [24] for the bio-molecular interaction networks along with force-directed layout, where the networks are placed into cellular components to quickly identify the location of the network elements, especially for the densely populated locations. In [25,26], the stereoscopic depth is utilized to encode the different levels-of-details in compound graphs and the interaction operations provided by the ExpanD technique for expanding or contracting the nodes in order to align graph nodes in the 3D space with minimum occlusion.…”

Section: Related Workmentioning

confidence: 99%

VizTract: Visualization of Complex Social Networks for Easy User Perception

Akula

Garibay

2019

BDCC

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Social networking platforms connect people from all around the world. Because of their user-friendliness and easy accessibility, their traffic is increasing drastically. Such active participation has caught the attention of many research groups that are focusing on understanding human behavior to study the dynamics of these social networks. Oftentimes, perceiving these networks is hard, mainly due to either the large size of the data involved or the ineffective use of visualization strategies. This work introduces VizTract to ease the visual perception of complex social networks. VizTract is a two-level graph abstraction visualization tool that is designed to visualize both hierarchical and adjacency information in a tree structure. We use the Facebook dataset from the Social Network Analysis Project from Stanford University. On this data, social groups are referred as circles, social network users as nodes, and interactions as edges between the nodes. Our approach is to present a visual overview that represents the interactions between circles, then let the user navigate this overview and select the nodes in the circles to obtain more information on demand. VizTract aim to reduce visual clutter without any loss of information during visualization. VizTract enhances the visual perception of complex social networks to help better understand the dynamics of the network structure. VizTract within a single frame not only reduces the complexity but also avoids redundancy of the nodes and the rendering time. The visualization techniques used in VizTract are the force-directed layout, circle packing, cluster dendrogram, and hierarchical edge bundling. Furthermore, to enhance the visual information perception, VizTract provides interaction techniques such as selection, path highlight, mouse-hover, and bundling strength. This method helps social network researchers to display large networks in a visually effective way that is conducive to ease interpretation and analysis. We conduct a study to evaluate the user experience of the system and then collect information about their perception via a survey. The goal of the study is to know how humans can interpret the network when visualized using different visualization methods. Our results indicate that users heavily prefer those visualization techniques that aggregate the information and the connectivity within a given space, such as hierarchical edge bundling.

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Utilization of variation in stereoscopic depth for encoding aspects of non-spatial data

Cited by 2 publications

References 3 publications

A Systematic Literature Review of User Evaluation in Immersive Analytics

A Systematic Literature Review of User Evaluation in Immersive Analytics

VizTract: Visualization of Complex Social Networks for Easy User Perception

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