When exploring data, analysts construct narratives about what the data means by asking questions, generating visualizations, reflecting on patterns, and revising their interpretations as new insights emerge. Yet existing analysis tools treat narrative as an afterthought, breaking the link between reasoning, reflection, and the evolving story from exploration. Consequently, analysts lose the ability to see how their reasoning evolves, making it harder to reflect systematically or build coherent explanations. To address this gap, we propose Narrative Scaffolding, a framework for narrative-driven exploration that positions narrative construction as the primary interface for exploration and reasoning. We implement this framework in a system that externalizes iterative reasoning through narrative-first entry, semantically aligned view generation, and reflection support via insight provenance and inquiry tracking. In a within-subject study N=20, we demonstrate that narrative scaffolding facilitates broader exploration, deeper reflection, and more defensible narratives. An evaluation with visualization literacy experts (N = 6) confirmed that the system produced outputs aligned with narrative intent and facilitated intentional exploration.

翻译：在探索数据时，分析师通过提出问题、生成可视化、反思模式以及随着新见解的出现而修正其解释，来构建关于数据意义的叙事。然而，现有的分析工具将叙事视为事后补充，割裂了探索过程中的推理、反思与不断演化的故事之间的联系。因此，分析师失去了观察其推理如何演变的能力，使得系统化反思或构建连贯解释变得更加困难。为弥补这一差距，我们提出了叙事支架，这是一个用于叙事驱动探索的框架，它将叙事构建定位为探索和推理的主要界面。我们在一个系统中实现了该框架，该系统通过叙事优先输入、语义对齐的视图生成以及通过见解溯源与探究追踪提供的反思支持，将迭代推理外部化。在一项被试内研究（N=20）中，我们证明叙事支架促进了更广泛的探索、更深入的反思以及更具辩护力的叙事。一项与可视化素养专家（N=6）的评估证实，该系统产生的输出与叙事意图保持一致，并促进了有意识的探索。