Immersive Analytics of Large Dynamic Networks via Overview and Detail Navigation

PubDate: Oct 2019

Teams: Complexity Science Hub；TU Wien；

Writers: Johannes Sorger, Manuela Waldner, Wolfgang Knecht, Alessio Arleo

PDF: Immersive Analytics of Large Dynamic Networks via Overview and Detail Navigation

Abstract

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.