Designing Semantically-Resonant Abstract Patterns for Data Visualization

2025-05-20

AI Summary

This study addresses the weak semantic conveyance of abstract patterns in data visualization and the difficulty non-expert users face in designing them. We propose the first publicly accessible framework for semantic-resonant abstract pattern design. Methodologically, we distilled design principles through iterative expert workshops, integrated semantic mapping, conceptual set modeling, and iterative pattern generation, and validated effectiveness via user-centered evaluation. Our contributions are twofold: (1) we establish the first systematic, actionable methodology for semantic pattern design, filling a critical methodological gap; and (2) empirical results demonstrate that non-designers using our framework efficiently generate patterns with high semantic fidelity—e.g., small dots representing olives and large dots representing tomatoes—achieving significantly improved pattern recognition accuracy and designer confidence, thereby enhancing visual cognitive efficiency.

Technology Category

• Data Mining & Knowledge Management: Data Visualization & Summarization
• Knowledge Representation and Reasoning: Diagnosis and Abductive Reasoning
• Cognitive Modeling & Cognitive Systems: Analogy

Application Category

• Web Mining and Content Analysis: Web data visualization
• User Modeling, Personalization and Recommendation: Practical large-scale studies of user experience
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions

Abstract

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.

Problem

• Lack of systematic framework for designing semantically-resonant abstract patterns
• Need to make pattern design accessible to general public
• Improving visualization through intuitive pattern-concept associations

Innovation

• Structured methodology for abstract pattern design
• Workshops with experts to develop framework
• Evaluation with non-designers shows effectiveness