发表机构
University of Iowa; University of Victoria（爱荷华大学; 维多利亚大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究通过分析项目记录、访谈和设计任务，揭示了数据艺术家在创意可视化中通过数据探索、参考改编、草图与原型共同发展故事与形式，并强调工具需支持替代方案的测试与修订，同时保留设计师的创造性判断。
AI 中文摘要
创意和艺术化的数据可视化能够传达故事并吸引参与，然而设计师如何发展其表达形式仍鲜为人知。我们通过三项互补研究调查了数据艺术家的设计过程：对40个公开项目记录的分析、与七位经验丰富的数据艺术家的基于人工制品的访谈，以及一项涉及八位数据艺术家的基于设计任务的研究。我们发现，故事和视觉形式通过数据探索、参考改编、草图绘制和原型制作共同发展。灵感来源于数据、现有作品、日常图像和个人经验。草图有助于发展映射关系，而使用真实数据的原型可以重塑表征和预期故事。设计师会考虑多种可能性，但通常一次只发展一个方向，部分原因是制作替代方案成本高昂。他们的选择在意义、视觉吸引力、可读性和可行性之间取得平衡。这些发现为连接故事、参考和真实数据的工具提供了信息，包括支持测试和修订替代方案同时保留设计师创造性判断的人工智能辅助。
英文摘要
Creative and artistic data visualizations communicate stories and invite engagement, yet how designers develop their expressive forms remains poorly understood. We investigate the design process of data artists through three complementary studies: an analysis of 40 public project accounts, artifact-anchored interviews with seven experienced data artists, and a design task-based study with eight data artists. We find that stories and visual forms develop together through data exploration, reference adaptation, sketching, and prototyping. Inspiration comes from data, existing work, everyday imagery, and personal experience. Sketches help develop mappings, while prototypes with real data can reshape representations and intended stories. Designers consider multiple possibilities but typically develop one direction at a time, partly because producing alternatives is costly. Their choices balance meaning, visual appeal, readability, and feasibility. These findings inform tools connecting stories, references, and real data, including AI assistance that supports testing and revising alternatives while preserving designers' creative judgment.
Comments28 pages, 7 figures
