Data storytelling has seen rapid growth through a proliferation of examples, as well as theoretical and technical advancements contributed across multiple disciplines. In this paper, we present a comprehensive survey of data storytelling research from 2010 to 2025. By analyzing the conceptualizations of data storytelling collected from related publications, we reveal the field's perspectives on the What, How, Why, and Who of data storytelling. We further investigated the operationalization of data stories. We identified 12 data story forms that provide concrete examples of how data stories have been presented. We derived a set of spectrum-based dimensions that capture important properties of data stories. Along each spectrum, applicable forms and design alternatives were discussed to analyze how they shape data storytelling experiences, along with data storytelling design trade-offs. Additionally, we examine how traditional narrative elements, like plot and character, have been adapted in data stories to support the operationalization of a data storytelling narratological perspective. Finally, we concluded the survey with a synthesis of our major findings and implications for future research.

翻译：数据叙事通过大量实例的涌现以及跨多个学科贡献的理论与技术进展，实现了快速增长。本文对2010年至2025年间的数据叙事研究进行了全面综述。通过分析从相关文献中收集的数据叙事概念化表述，我们揭示了该领域对数据叙事的“内容”（What）、“方法”（How）、“目的”（Why）以及“主体”（Who）的视角。我们进一步研究了数据故事的操作化实现。我们识别了12种数据故事形式，这些形式为数据故事如何被呈现提供了具体实例。我们推导出一组基于谱系的关键维度，用以捕捉数据故事的重要属性。针对每个谱系，我们讨论了适用的形式与设计替代方案，以分析它们如何塑造数据叙事的体验，并探讨了数据叙事设计中的权衡取舍。此外，我们还考察了传统叙事元素（如情节与角色）如何在数据故事中被调整运用，以支持数据叙事叙事学视角的操作化。最后，我们在综述结论中综合了主要发现，并提出了对未来研究的启示。