Exploring Collaborative Immersive Visualization & Analytics for High-Dimensional Scientific Data through Domain Expert Perspectives

TL;DR

This paper investigates how collaborative immersive visualization tools can support multi-user scientific data analysis, based on interviews with domain experts, revealing challenges, perceptions, and design opportunities for effective teamwork.

Contribution

It provides empirical insights into collaboration practices and offers design implications for next-generation multi-user immersive scientific visualization platforms.

Findings

Current ecosystems disrupt coordination and shared understanding

Opportunities exist for effective multi-user engagement

Design implications enhance mutual awareness and participation

Abstract

Cross-disciplinary teams increasingly work with high-dimensional scientific datasets, yet fragmented toolchains and limited support for shared exploration hinder collaboration. Prior immersive visualization and analytics research has emphasized individual interaction, leaving open how multi-user collaboration can be supported at scale. To fill this critical gap, we conduct semi-structured interviews with 20 domain experts from diverse academic, government, and industry backgrounds. Using deductive-inductive hybrid thematic analysis, we identify four collaboration-focused themes: workflow challenges, adoption perceptions, prospective features, and anticipated usability and ethical risks. These findings show how current ecosystems disrupt coordination and shared understanding, while highlighting opportunities for effective multi-user engagement. Our study contributes empirical insights into collaboration practices for high-dimensional scientific data visualization and analysis, offering design implications to enhance coordination, mutual awareness, and equitable participation in next-generation collaborative immersive platforms. These contributions point toward future environments enabling distributed, cross-device teamwork on high-dimensional scientific data.