More Than Beautiful: Exploring Design Features, Practical Perspectives, and Implications of Artistic Data Visualization
Xingyu Lan, Yifan Wang, Lingyu Peng, Xiaofan Ma
TL;DR
This paper investigates artistic data visualization by analyzing a corpus of 220 artworks and conducting in-depth interviews with 12 data artists. It builds a design taxonomy consisting of design paradigms, design intents, and design techniques, revealing how artistic practice infuses data visualization with sensation, narrative, interaction, and physicality. The study highlights the field's roots in contemporary art discourse and identifies seven actionable paths for future work that span theory, evaluation, representation, and applications. By articulating practitioners' perspectives and a structured design framework, the work aims to expand the visualization community's design space and foster cross-disciplinary collaboration.
Abstract
Standing at the intersection of science and art, artistic data visualization has gained popularity in recent years and emerged as a significant domain. Despite more than a decade since the field's conceptualization, a noticeable gap remains in research concerning the design features of artistic data visualizations, the aesthetic goals they pursue, and their potential to inspire our community. To address these gaps, we analyzed 220 data artworks to understand their design paradigms and intents, and construct a design taxonomy to characterize their design techniques (e.g., sensation, interaction, narrative, physicality). We also conducted in-depth interviews with twelve data artists to explore their practical perspectives, such as their understanding of artistic data visualization and the challenges they encounter. In brief, we found that artistic data visualization is deeply rooted in art discourse, with its own distinctive characteristics in both inner pursuits and outer presentations. Based on our research, we outline seven prospective paths for future work.