Characterizing Creativity in Data Visualization: Reflections and Future Directions
TL;DR
Two complementary studies to characterize creativity in data visualization are presented, indicating that artifacts or final products are often disproportionately considered as the primary indicator of creativity, whereas the design process remains undervalued in practical.
Abstract
Creativity is valued in data visualization design and research, yet how it manifests remains unclear. Understanding creativity is essential for developing expressive visualization tools and representations. In this paper, we present two complementary studies to characterize creativity in data visualization. First, a systematic review of 104 papers yields a design space spanning four themes: design frameworks incorporating divergent and convergent thinking activities; creative representations developing unorthodox visualizations; visualization-enabled creativity support tools supporting creative tasks (e.g., writing); and understanding creativity, creative processes, and influencing factors. Second, qualitative interviews with 11 visualization practitioners and researchers explore practical challenges and contrast them with current academic framing through our design space. Findings indicate that artifacts or final products are often disproportionately considered as the primary indicator of creativity, whereas the design process remains undervalued in practical. We conclude by presenting a definition of creativity in data visualization and directions for future research.
