Immersive Analysis with Natural Interaction for Collaborative Task Analysis

Apaza Apaza N.J.; Valdivia A.M.C. · Proceedings - International Conference of the Chilean Computer Science Society, SCCC (2025) · DOI: 10.1109/sccc67219.2025.11420376

Resumen

The accelerated growth in data volume and complexity has exposed limitations in traditional 2D analysis environments, particularly when dealing with high-dimensional and unstructured information from diverse sources. To address these challenges, immersive analytics has emerged, combining data analysis with 3D virtual environments to enable a more intuitive and natural exploration of complex datasets. However, individual exploration is often insufficient in scenarios that require comparing multiple perspectives or sources. In response, collaborative immersive analytics (CIA) allows multiple users to share an immersive environment for joint reasoning and decision-making. Despite advances, few systems focus on supporting collaborative analytical tasks such as data organization, navigation, annotation, and interpretation through natural interaction. In this paper, we present a tool designed to facilitate the collaborative exploration and analysis of data within immersive virtual environments, emphasizing natural interaction among users. Our system enables the discovery of patterns and joint decision-making on complex data in real-time. We describe the design, implementation, and results of a preliminary feasibility study, which explores the capabilities and limitations of these environments for collaborative analytical tasks, identifying key challenges for future research.

Instituciones: Universidad Nacional de San Agustín de Arequipa