提出HDMI画布，系统梳理人、数据、模型的互动关系。
The Human-Data-Model Interaction Canvas for Visual Analytics
- 构建HDMI画布，明确三者在可视化分析中的角色与互动
- 融合人机反馈与可解释AI，增强模型贡献可见性
- 适合推动跨学科协作与以用户为中心的分析设计
可视化分析（VA）将人、数据和模型作为洞察生成与数据驱动决策的关键参与者。本文回顾并反思了16个VA过程模型与框架，提出九项高层次观察，推动对VA的新视角。核心贡献是HDMI画布，一种补充现有模型的视角，系统刻画人、数据、模型的多样化角色及其在VA过程中的相互促进关系。该画布具有描述力，能清晰区分一系列VA构建模块，而非仅陈述通用原则。它整合现代以人为中心的方法，如人类知识外化和反馈循环，并强调可解释与可追溯AI在模型贡献上的价值。HDMI画布具备生成能力，可指导新VA流程的设计，且优化面向外部利益相关者的应用，提升推广性、跨学科协作与用户中心设计。其效用通过两个初步案例研究得到验证。
原文摘要 · Abstract (English)
Visual Analytics (VA) integrates humans, data, and models as key actors in insight generation and data-driven decision-making. This position paper values and reflects on 16 VA process models and frameworks and makes nine high-level observations that motivate a fresh perspective on VA. The contribution is the HDMI Canvas, a perspective to VA that complements the strengths of existing VA process models and frameworks. It systematically characterizes diverse roles of humans, data, and models, and how these actors benefit from and contribute to VA processes. The descriptive power of the HDMI Canvas eases the differentiation between a series of VA building blocks, rather than describing general VA principles only. The canvas includes modern human-centered methodologies, including human knowledge externalization and forms of feedback loops, while interpretable and explainable AI highlight model contributions beyond their conventional outputs. The HDMI Canvas has generative power, guiding the design of new VA processes and is optimized for external stakeholders, improving VA outreach, interdisciplinary collaboration, and user-centered design. The utility of the HDMI Canvas is demonstrated through two preliminary case studies.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。