PiCCL: Data-Driven Mark Composition of Bespoke Pictorial Chart
Haoyan Shi -
Yunhai Wang -
Junhao Chen -
Chenglong Wang -
Bongshin Lee -
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Room: Hall M2
Keywords
pictorial charts, data-driven composition, chart composition, parametric representation
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.