Designing Metaphorical Multivariate Symbols to Optimize Dockless Bike Sharing

ABSTRACT

While dockless bike sharing is gaining popularity, oversupplied and poorly maintained bikes introduce chaos and waste (e.g., so-called zombie bikes that unused). Spatiotemporal pattern visualizations can help policy-making and infrastructure improvement (e.g., allocating parking areas). However, multivariate symbolizing (e.g., supply, flow, usage) to optimize dockless bike sharing is challenging. In this paper, we introduce metaphor theory to design multivariate symbols. First, we systemically explore the coupling of three metaphor types (orientational, ontological and structural) with symbols at three levels of iconicity. Then, we construct metaphorical symbols for optimizing dockless bike sharing following a user-centred design process. We also offer an evaluation using eye-tracking and questionnaire techniques. The results indicate that, compared with bin-packing and multiview symbols, metaphorical symbols significantly improved effectiveness and efficiency, and reduced participants' cognitive load. Our evaluation presents preliminary evidence that metaphors can offer new organizational mechanisms for map symbols to represent multivariate naturally and effectively.

KEYWORDS:

• Map symbol
• metaphor
• spatiotemporal multivariate
• bike sharing
• user-centred design

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

Data available upon request from the authors.

Notes on the contributor

Mingguang Wu is currently a professor at Department of Geographic Information Science, Nanjing Normal University, China. He has a PhD in Geography and Geographic Information Science from the Information Engineering University, China. His professional skills and interests in cartography are symbol design and spatio-temporal mapping.

Correction Statement

This article has been corrected with minor changes. These changes do not impact the academic content of the article.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China (grant numbers 41971417, 41571433).