HeedVision: Attention Awareness in Collaborative Immersive Analytics Environments
Authors
Arvind Srinivasan (Aarhus University), Niklas Elmqvist (Aarhus University)
Presentation
- Session
- This feels amazingly real!
- Time
- Friday, Nov 13, 08:48 – 09:00 (US/Eastern) · session 08:00 – 09:30
- Location
- Hall America north
Links
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Keywords
Attention tracking, eyetracking, immersive analytics, ubiquitous analytics, post-WIMP interaction
Abstract
Group awareness, the ability to perceive the activities of collaborators in a shared space, is a vital mechanism to support effective coordination and joint data analysis in collaborative visualization. We introduce collaborative attention-aware visualizations (CAAVs) that track, record, and revisualize the collective attention of multiple users over time. We implement this concept in HEEDVISION, a standards-compliant WebXR system built with React Three Fiber that runs on modern AR/VR headsets, and complement it with proof-of-concept implementations covering the remaining three quadrants of our design space, varying presentation (embedded vs. separated) and situatedness (world space vs. camera space). Through a mixed-methods exploratory study where pairs of co-located analysts performed visual search tasks in a shared immersive AR environment, we investigate how attention revisualization affects collaborative coordination in immersive analytics. Our results show that CAAVs can improve spatial coordination, search efficiency, and task load distribution in collaborative visual search tasks among collaborators, though benefits vary by context, favoring abstract environments lacking natural landmarks. This work extends attention awareness to multi-user settings and provides empirical evidence for its context-dependent benefits in collaborative visual search tasks within immersive analytics environments.
For Practitioners
This paper targets people who build or deploy multi-user AR/VR analytics tools: XR application developers, collaborative visualization and groupware designers, and UX practitioners working on shared 3D workspaces. It could also be of interest to domain practitioners who already explore data together in immersive settings, such as structural biologists inspecting molecular models, geospatial analysts, and data scientists working with high-dimensional embeddings. There are two ways to apply the work. The design space gives a concrete checklist for adding attention awareness to a tool that already exists: how to capture attention (head pose works on any consumer headset and sidesteps the cost and calibration burden of eye tracking), how to accumulate it over time (voxel grids with temporal decay and per-user identity), and how to display it (embedded in the visualization or separated into a panel, anchored in world space or camera space). Our study then says when the feature is worth building at all. Attention cues helped most in abstract environments with no natural landmarks, and added little where the visualization already had spatial structure that collaborators could use to divide up the work on their own. A team can use that to decide whether attention sharing suits their data before committing engineering effort to it. HeedVision is standards-compliant WebXR built with React Three Fiber, and we release the source for it and for the three additional quadrant prototypes, so practitioners can adapt a running system rather than start from scratch.