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

TL;DR

MarioChart introduces an active proxy tangible interface using robot carts for data exploration, enhancing short-term spatial memory and task speed in casual data analysis scenarios.

Contribution

The paper presents a novel active proxy interface with robot carts for embodied data visualization, demonstrating its benefits over traditional tablet interactions.

Findings

Enhances short-term spatial memory during data exploration

Enables faster completion of certain data tasks

No significant difference in long-term memory or user fatigue compared to tablets

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.