Visualizing Proximity-Based Spatiotemporal Behavior of Museum Visitors using Tangram Diagrams

• Published in: Computer graphics forum Vol. 33; no. 3; pp. 261 - 270
• Main Authors: Lanir, J., Bak, P., Kuflik, T.
• Format: Journal Article
• Language: English
• Published: Oxford Blackwell Publishing Ltd 01-06-2014
• Subjects: Accessibility; Analysis; Categories and Subject Descriptors (according to ACM CCS); Consumer behavior; Conveying; Curators; Data visualization; Decisions; Design Tools and Techniques [D.2.2]: UI; Indoor; Information processing; Museums; Studies; Visual; Visualization
• ISSN: 0167-7055; 1467-8659
• DOI: 10.1111/cgf.12382

For museum curators it is imperative to learn, analyze, and understand the behavior patterns of the visitors in their museum. Recent developments in the field of indoor positioning systems make the acquisition and availability of visitor behavior data more attainable. However, the analysis of such data remains a challenge due to its noisiness, complexity and sheer size. The current paper applies information visualization techniques to analyze this data and make it more accessible to museum curators and personnel. We first provide a detailed description of the application domain including an analysis of the curators' information needs and a description of how a dataset on visitors' spatiotemporal behavior could be acquired. In order to address the curators' needs, we designed a visualization to encode and convey the information based on a newly adjusted visual glyph that we call Tangram Diagrams. We thereby focus on the adaptability of the technique to a particular domain, rather than on the novelty aspects of the technique itself. We have evaluated our design decisions empirically, and conducted an expert study to describe the insights gained and the value of the information obtained from the visualization. The contribution of this work is twofold. First, we apply information visualization to the museum domain and discuss how it extends to general indoor spatiotemporal behavior analysis. Second, we show how a visual glyph metaphor can be applied in different ways and contexts to efficiently encode multi‐faceted information.