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、生成可视化图表、反思模式并在新见解出现时修正解释，逐步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，割裂了推理、反思与探索过程中动态演变的叙事之间的关联。这导致分析师难以追踪自身推理的演变过程，从而无法进行系统性反思或构建连贯的解释。为弥补这一不足，我们提出“叙事支架”这一叙事驱动探索框架，将叙事构建定位为探索与推理的核心界面。我们通过一个系统实现该框架，该系统采用叙事优先的输入方式外化迭代推理过程，通过语义对齐的视图生成机制，并借助见解溯源与探究追踪功能提供反思支持。在一项被试内研究（N=20）中，我们证明叙事支架能够促进更广泛的探索、更深入的反思以及更具说服力的叙事构建。可视化素养专家评估（N=6）进一步证实，该系统生成的输出与叙事意图高度契合，并能有效引导有意识的探索过程。