Physical Containers as Framing Conditions for Visualization in Augmented Reality
This addresses the challenge for users who struggle with configuring visualization tools when lacking specific goals, though it appears incremental by building on existing AR and visualization concepts.
The paper tackles the problem of cold-start friction in exploratory data analysis by proposing a framework that uses physical containers in Augmented Reality as implicit framing mechanisms to guide data interpretation, demonstrating how container attributes like shape and size can encourage specific analytic patterns such as cyclic or comparative analysis.
Exploratory data analysis (EDA) is often hindered by cold-start friction; when users lack specific analytic goals, they struggle to configure complex visualization parameters. While existing visualization tools mostly rely on explicit user input to frame data, we propose leveraging the physical environment as an implicit framing mechanism. We introduce a conceptual framework that uses the geometric and spatial properties of physical containers in Augmented Reality (AR) to guide data interpretation. We characterize how container attributes, such as number of faces, size, proportion, and shape, give rise to distinct perceptual tendencies. For example, a circular container may encourage cyclic interpretation, while juxtaposed planar faces may facilitate comparative analysis. By treating physical forms as environmental framing conditions, we show how AR can orient a user's attention and structure their exploration without requiring manual encoding or prescribing fixed conclusions. We demonstrate this framework through a series of AR design examples illustrating how container morphology foregrounds cyclic, comparative, and sequential analytic patterns.