Pré-Publication, Document De Travail Année : 2025

Designing Semantically-Resonant Abstract Patterns for Data Visualization

Zihan Lu
Jiayi Hong
Lijie Yao
Tobias Isenberg

Résumé

We present a structured design methodology for creating semantically-resonant abstract patterns, making the pattern design process accessible to the general public. Semantically-resonant patterns are those that intuitively evoke the concept they represent within a specific set (e.g., in a vegetable concept set, small dots for olives and large dots for tomatoes), analogous to the concept of semantically-resonant colors (e.g., using olive green for olives and red for tomatoes). Previous research has shown that semantically-resonant colors can improve chart reading speed, and designers have made attempts to integrate semantic cues into abstract pattern designs. However, a systematic framework for developing such patterns was lacking. To bridge this gap, we conducted a series of workshops with design experts, resulting in a design methodology that summarizes the methodology for designing semantically-resonant abstract patterns. We evaluated our design methodology through another series of workshops with non-design participants. The results indicate that our proposed design methodology effectively supports the general public in designing semantically-resonant abstract patterns for both abstract and concrete concepts.

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Dates et versions

hal-05235899 , version 1 (02-09-2025)

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Zihan Lu, Tingying He, Jiayi Hong, Lijie Yao, Tobias Isenberg. Designing Semantically-Resonant Abstract Patterns for Data Visualization. 2025. ⟨hal-05235899⟩
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