让可视化与文字互动生成，一键构建数据叙事
DATAWEAVER: Authoring Data-Driven Narratives through the Integrated Composition of Visualization and Text
- 支持可视化生成文字，也支持文字反推可视化
- 用户点击图表元素自动生成相关叙述内容
- 适合新闻编辑、数据分析师快速制作交互式报告
数据驱动的叙事在新闻报道等领域日益重要。但创作过程仍具挑战性，需将有效可视化与引人入胜的叙述有机结合，形成连贯且可交互的呈现。为此，我们提出集成式创作框架与系统 DataWeaver，支持“可视化到文本”和“文本到可视化”的双向生成。DataWeaver 通过“呼出”交互（即用户主动高亮可视化元素）触发相关叙述内容，实现数据事实锚定的叙事生成。同时支持从已有叙述生成相应交互式可视化。对13名参与者的评估表明，DataWeaver 具有实用性和易用性，其集成创作框架效果显著。评估也揭示了改进空间：需优化过滤机制、可视化推荐，并通过高级定制选项更好支持创作自由度。
原文摘要 · Abstract (English)
Data-driven storytelling has gained prominence in journalism and other data reporting fields. However, the process of creating these stories remains challenging, often requiring the integration of effective visualizations with compelling narratives to form a cohesive, interactive presentation. To help streamline this process, we present an integrated authoring framework and system, DataWeaver, that supports both visualization-to-text and text-to-visualization composition. DataWeaver enables users to create data narratives anchored to data facts derived from "call-out" interactions, i.e., user-initiated highlights of visualization elements that prompt relevant narrative content. In addition to this "vis-to-text" composition, DataWeaver also supports a "text-initiated" approach, generating relevant interactive visualizations from existing narratives. Key findings from an evaluation with 13 participants highlighted the utility and usability of DataWeaver and the effectiveness of its integrated authoring framework. The evaluation also revealed opportunities to enhance the framework by refining filtering mechanisms and visualization recommendations and better support authoring creativity by introducing advanced customization options.
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。