Enhancing User Experience for Data Visualization in Three-Dimensional Immersive Space

Abstract

Abstract In the era of big data, effectively interpreting complex datasets is critical for decision-making across various fields. Many use data visualization formats, such as 2D techniques, to aid in this process. However, traditional 2D data visualization limits the ability to immerse oneself in the data and analyze large-scale, complex multidimensional data. To address this, virtual reality(VR) for data visualisation is identified as an alternative solution. While 3D visualization in VR offers a promising solution by enabling spatial and interactive data exploration, its potential is hindered by poor user experience (UX) design. This research introduces a UX-driven immersive 3D data visualization prototype to transform VR from a novel technology into a practical approach for data analysis. We used the Design Science Research (DSR) approach over two development cycles. The first produced a basic VR prototype (VRVizX v1) to identify usability issues. The second (VRVizX v2) added enhancements like intuitive navigation, improved UI, feedback cues, and reset features. The final prototype was evaluated in a within-subjects comparative study with 30 users, comparing the VR system to a traditional 2D prototype. Users were evaluated using a Pre-Post test to assess the effectiveness of the system, in terms of accuracy and cognitive workload in understanding the data, using Meta Quest 2. Our results indicated higher accuracy rates and significantly lower cognitive workload in VRVizX, as measured by the NASA Task Load Index (NASA TLX), including reduced mental demand (p¡0.001), effort, and frustration, along with higher perceived performance despite greater physical demand. Additionally, VRVizX received a higher System Usability Scale (SUS) score compared to the 2D system. Our qualitative evaluation suggests that effective UX design, including a clear and minimalistic user interface, multimodal feedback such as visual, auditory, and haptic cues, and support for trial and error through reset functionalities, can make VR visualization more effective than 2D approaches for analytical tasks. While limited to one VR platform(Meta Quest 2) and scatterplot visualizations, this research provides strong evidence that UX-optimized VR data visualizations can overcome traditional 2D data visualization limitations. Future work should expand to diverse visualization types, dataset types(other than CSV), and to analyse multiple datasets at once to assess long-term usability across various user groups. Keywords: Data visualization, Virtual Reality, User Experience, Immersive analytics, 3D interaction, Human-computer interaction.