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.
Authors
- Yunhai Wang (ORCID: https://orcid.org/0000-0003-3622-8261)
- Chenglong Wang (ORCID: https://orcid.org/0000-0003-2391-0923)
- Junhao Chen (ORCID: https://orcid.org/0000-0001-9577-1710)
- Bongshin Lee
- Haoyan Shi (ORCID: https://orcid.org/0009-0008-2316-088X)
Institutions
- Microsoft (United States) (US)
- Shandong University (CN)
- Yonsei University (KR)
- Renmin University of China (CN)
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
- 0.00