A Collaborative Untethered Virtual Reality Environment for Interactive Social Network Visualization
This addresses the problem of noncollaborative VR systems for data analysts and visualization practitioners, offering a domain-specific solution for social network visualization.
The paper tackles the challenge of creating collaborative virtual reality environments for data visualization by integrating multiple tracking systems and new interaction paradigms, resulting in a system for interactive social network visualization that combines GearVR headsets, OptiTrack motion capture, and Perception Neuron suits to enable untethered, multi-person experiences.
The increasing prevalence of Virtual Reality technologies as a platform for gaming and video playback warrants research into how to best apply the current state of the art to challenges in data visualization. Many current VR systems are noncollaborative, while data analysis and visualization is often a multi-person process. Our goal in this paper is to address the technical and user experience challenges that arise when creating VR environments for collaborative data visualization. We focus on the integration of multiple tracking systems and the new interaction paradigms that this integration can enable, along with visual design considerations that apply specifically to collaborative network visualization in virtual reality. We demonstrate a system for collaborative interaction with large 3D layouts of Twitter friend/follow networks. The system is built by combining a 'Holojam' architecture (multiple GearVR Headsets within an OptiTrack motion capture stage) and Perception Neuron motion suits, to offer an untethered, full-room multi-person visualization experience.