PiCCL: Data-Driven Composition of Bespoke Pictorial Charts

We present PiCCL (Pictorial Chart Composition Language), a new language that enables users to easily create pictorial charts using a set of simple operators. To support systematic construction while addressing the main challenge of expressive pictorial chart authoring-manual composition and fine-tuning of visual properties-PiCCL introduces a parametric representation that integrates data-driven chart generation with graphical composition. It also employs a lazy data-binding mechanism that automatically synthesizes charts. PiCCL is grounded in a comprehensive analysis of real-world pictorial chart examples. We describe PiCCL's design and its implementation as piccl.js, a JavaScript-based library. To evaluate PiCCL, we showcase a gallery that demonstrates its expressiveness and report findings from a user study assessing the usability of piccl.js. We conclude with a discussion of PiCCL's limitations and potential, as well as future research directions.

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Publication Details

Journal
IEEE Transactions on Visualization and Computer Graphics
Published
2025-11-21
DOI
https://doi.org/10.1109/tvcg.2025.3634264
Primary Topic
Data Visualization and Analytics
Type
article
Field-Weighted Citation Impact
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article

PiCCL: Data-Driven Composition of Bespoke Pictorial Charts

Yunhai Wang, Chenglong Wang, Junhao Chen, Bongshin Lee et al.
IEEE Transactions on Visualization and Computer Graphics
Data Visualization and Analytics
article

PiCCL: Data-Driven Composition of Bespoke Pictorial Charts

Yunhai Wang, Chenglong Wang, Junhao Chen, Bongshin Lee, Haoyan Shi
article en

Abstract

We present PiCCL (Pictorial Chart Composition Language), a new language that enables users to easily create pictorial charts using a set of simple operators. To support systematic construction while addressing the main challenge of expressive pictorial chart authoring-manual composition and fine-tuning of visual properties-PiCCL introduces a parametric representation that integrates data-driven chart generation with graphical composition. It also employs a lazy data-binding mechanism that automatically synthesizes charts. PiCCL is grounded in a comprehensive analysis of real-world pictorial chart examples. We describe PiCCL's design and its implementation as piccl.js, a JavaScript-based library. To evaluate PiCCL, we showcase a gallery that demonstrates its expressiveness and report findings from a user study assessing the usability of piccl.js. We conclude with a discussion of PiCCL's limitations and potential, as well as future research directions.

IEEE Transactions on Visualization and Computer GraphicsVol. 32(1)
Microsoft (United States) (US), Shandong University (CN), Yonsei University (KR), Renmin University of China (CN)
Openalex Percentile: Top 63%
Data Visualization and Analytics
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