通过概览和详细导航的大型动态网络沉浸式分析

J. Sorger, Manuela Waldner, Wolfgang Knecht, Alessio Arleo
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引用次数: 18

摘要

大型动态网络的分析是一个蓬勃发展的研究领域,通常依赖于二维图表示。可负担得起的头戴式显示器的出现,激发了人们对沉浸式网络分析的3D可视化潜力的新兴趣。然而,大多数解决方案不能很好地扩展节点和边的数量,并且依赖于传统的飞行或遍历导航。在本文中,我们提出了一种在虚拟现实中探索大型动态图形的新方法,该方法将两种导航隐喻交织在一起:概述探索和沉浸式细节分析。因此,我们利用了最先进的VR头显的潜力,加上基于web的3D渲染引擎,支持异构输入模式,以实现临时沉浸式网络分析。我们通过绩效评估和专家分析医疗数据的案例研究来验证我们的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Immersive Analytics of Large Dynamic Networks via Overview and Detail Navigation
Analysis of large dynamic networks is a thriving research field, typically relying on 2D graph representations. The advent of affordable head mounted displays 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 medical data.
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