Immersive Collaborative Analysis of Network Connectivity: CAVE-style or Head-Mounted Display?

• Published in: IEEE transactions on visualization and computer graphics Vol. 23; no. 1; pp. 441 - 450
• Main Authors: Cordeil, Maxime, Dwyer, Tim, Klein, Karsten, Laha, Bireswar, Marriott, Kim, Thomas, Bruce H.
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.01.2017; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: 3D Network; CAVE; Collaboration; Completion time; Cost analysis; Data analysis; Data visualization; Displays; Helmet mounted displays; Immersive Analytics; Navigation; Network analysis; Oculus Rift; Scientific visualization; Three-dimensional displays; Two dimensional displays; Virtual reality; Visualization
• ISSN: 1077-2626; 1941-0506; 1941-0506
• DOI: 10.1109/TVCG.2016.2599107

High-quality immersive display technologies are becoming mainstream with the release of head-mounted displays (HMDs) such as the Oculus Rift. These devices potentially represent an affordable alternative to the more traditional, centralised CAVE-style immersive environments. One driver for the development of CAVE-style immersive environments has been collaborative sense-making. Despite this, there has been little research on the effectiveness of collaborative visualisation in CAVE-style facilities, especially with respect to abstract data visualisation tasks. Indeed, very few studies have focused on the use of these displays to explore and analyse abstract data such as networks and there have been no formal user studies investigating collaborative visualisation of abstract data in immersive environments. In this paper we present the results of the first such study. It explores the relative merits of HMD and CAVE-style immersive environments for collaborative analysis of network connectivity, a common and important task involving abstract data. We find significant differences between the two conditions in task completion time and the physical movements of the participants within the space: participants using the HMD were faster while the CAVE2 condition introduced an asymmetry in movement between collaborators. Otherwise, affordances for collaborative data analysis offered by the low-cost HMD condition were not found to be different for accuracy and communication with the CAVE2. These results are notable, given that the latest HMDs will soon be accessible (in terms of cost and potentially ubiquity) to a massive audience.