Reframing Pattern: A Comprehensive Approach to a Composite Visual Variable
Tingying He, Jason Dykes, Petra Isenberg, Tobias Isenberg

TL;DR
This paper introduces a comprehensive, consistent theory of pattern as a composite visual variable in visualization, clarifying ambiguities and expanding the design space for pattern-based data encoding.
Contribution
It proposes a new formal system for pattern as a composite visual variable, integrating spatial, relational, and retinal variables, and connects this to existing visualization and cartography theories.
Findings
Provides a unified framework for pattern in visualization.
Demonstrates the explanatory power of complex spatial arrangements.
Connects pattern theory to broader cartography concepts.
Abstract
We present a new comprehensive theory for explaining, exploring, and using pattern as a visual variable in visualization. Although patterns have long been used for data encoding and continue to be valuable today, their conceptual foundations are precarious: the concepts and terminology used across the research literature and in practice are inconsistent, making it challenging to use patterns effectively and to conduct research to inform their use. To address this problem, we conduct a comprehensive cross-disciplinary literature review that clarifies ambiguities around the use of "pattern" and "texture". As a result, we offer a new consistent treatment of pattern as a composite visual variable composed of structured groups of graphic primitives that can serve as marks for encoding data individually and collectively. This new and widely applicable formulation opens a sizable design space…
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