Immersive analytics with HMDs and CAVEs: A user study on 3D graph interaction

Abstract

Integrating Virtual Reality (VR) and Human–Computer Interaction (HCI) has transformed user engagement with virtual environments, enhancing immersion and usability. Technologies like Cave Automatic Virtual Environment (CAVE) and Head-Mounted Displays (HMDs) have shown significant promise in visualizing data, especially for examining and comprehending intricate 3D datasets, such as graph visualizations. To explore the effectiveness of these technologies in data visualization, we conducted a user study comparing user experience and performance across these two systems when interacting with a large 3D graph. The virtual environment and interaction modalities were adapted to each platform: the HMD setup utilized dual 6-DOF controllers, while the CAVE configuration employed a Flystick2 controller and a trackball. Preliminary data on participants’ demographics, motion sickness sensitivity, and prior experience with graph theory were collected to provide context for the findings. Results show that users in the HMD condition reported significantly higher levels of perceived presence and involvement, as well as improved task performance in navigation and interaction tasks. While both systems were rated similarly for perceived usefulness and ease of use, the HMD environment offered a more immersive and emotionally positive experience overall. These findings contribute to immersive analytics research by demonstrating the comparative strengths of HMD-based systems for individual 3D graph exploration, while highlighting the potential advantages of CAVE for low-discomfort settings. The study underscores the importance of aligning system design with user profiles and task demands to optimize data exploration in virtual environments.