Title: Safire: Similarity Framework for Visualization Retrieval Show Chinese title

Title: Safire：可视化检索的相似性框架

Abstract: Effective visualization retrieval necessitates a clear definition of similarity. Despite the growing body of work in specialized visualization retrieval systems, a systematic approach to understanding visualization similarity remains absent. We introduce the Similarity Framework for Visualization Retrieval (Safire), a conceptual model that frames visualization similarity along two dimensions: comparison criteria and representation modalities. Comparison criteria identify the aspects that make visualizations similar, which we divide into primary facets (data, visual encoding, interaction, style, metadata) and derived properties (data-centric and human-centric measures). Safire connects what to compare with how comparisons are executed through representation modalities. We categorize existing representation approaches into four groups based on their levels of information content and visualization determinism: raster image, vector image, specification, and natural language description, together guiding what is computable and comparable. We analyze several visualization retrieval systems using Safire to demonstrate its practical value in clarifying similarity considerations. Our findings reveal how particular criteria and modalities align across different use cases. Notably, the choice of representation modality is not only an implementation detail but also an important decision that shapes retrieval capabilities and limitations. Based on our analysis, we provide recommendations and discuss broader implications for multimodal learning, AI applications, and visualization reproducibility. Show Chinese abstract

Abstract: 有效的可视化检索需要对相似性进行明确的定义。 尽管在专门的可视化检索系统方面已有大量研究，但系统地理解可视化相似性的方法仍然缺失。 我们提出了可视化检索的相似性框架（Safire），这是一个概念模型，从两个维度来描述可视化相似性：比较标准和表示模态。 比较标准确定使可视化相似的方面，我们将它们分为主要方面（数据、视觉编码、交互、风格、元数据）和派生属性（以数据为中心和以人类为中心的度量）。 Safire通过表示模态将比较什么与如何执行比较联系起来。 我们将现有的表示方法根据其信息内容水平和可视化确定性分为四类：位图图像、矢量图像、规范和自然语言描述，这些共同指导哪些内容是可计算和可比较的。 我们使用Safire分析几个可视化检索系统，以展示其在澄清相似性考虑方面的实际价值。 我们的研究结果揭示了不同使用案例中特定标准和模态如何对齐。 值得注意的是，表示模态的选择不仅是一个实现细节，而且是一个重要的决策，它塑造了检索能力和限制。 基于我们的分析，我们提供了建议，并讨论了多模态学习、人工智能应用和可视化可重复性的更广泛影响。