MarioChart: Autonomous Tangibles as Active Proxy Interfaces for Embodied Casual Data Exploration

2026-01-26

AI Summary

This work proposes an “active agent” visualization paradigm to support intuitive, embodied exploration of multivariate data within contextualized environments, implemented in a system named MarioChart. MarioChart employs autonomously mobile robotic agents that dynamically reposition themselves on a tabletop to align with spatial references, thereby integrating tangible interfaces with spatial data mappings. A user study (n=12) using a campus sustainability dataset demonstrates that, compared to conventional tablet-based interaction, MarioChart significantly improves short-term spatial memory and accelerates performance on certain analytical tasks. No significant differences were observed in long-term memory retention, cognitive load, fatigue, or engagement, collectively validating the efficacy of active agents in extending embodied approaches to data analysis.

Technology Category

• Intelligent Robots: Embodied AI
• Multiagent Systems: Modeling other Agents
• Cognitive Modeling & Cognitive Systems: Agent Architectures

Application Category

• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• Web Mining and Content Analysis: Web data visualization
• User Modeling, Personalization and Recommendation: Practical large-scale studies of user experience

Abstract

We introduce the notion of an Active Proxy interface, i.e. tangible models as proxies for physical data referents, supporting interactive exploration of data through active manipulation. We realise an active proxy data visualisation system,"MarioChart", using robot carts relocating themselves on a tabletop, e.g., to align with their data referents in a map or other visual layout. We consider a casual-data exploration scenario involving a multivariate campus sustainability dataset, using scale models as proxies for their physical building data referents. Our empirical study (n=12) compares active proxy use with conventional tablet interaction, finding that our active proxy system enhances short-term spatial memory of data and enables faster completion of certain data analytic tasks. It shows no significant differences compared to traditional touch-screens in long-term memory, physical fatigue, mental workload, or user engagement. Our study offers an initial baseline for active proxy techniques and advances understanding of tangible interfaces in situated data visualisation.

Problem

• Active Proxy
• Tangible Interfaces
• Casual Data Exploration
• Situated Visualization
• Embodied Interaction

Innovation

• Active Proxy
• Tangible Interface
• Autonomous Tangibles
• Embodied Interaction
• Situated Data Visualization