【摘要】 [目的/意义]数据作为一种新型的生产要素，充分开发利用数据资源，拓展规范化数据的应用场景是释放数据要素价值、激活数据要素潜能的必要手段。[方法/过程]按照“场景识别—模型设计—模型阐释”的思路，运用质性分析法对文本资料进行编码场景识别，形成数据应用场景的分类体系，并结合创新应用案例以及数据生命周期理论、CRISP-DM模型和数据价值链构建数据应用场景模型，自上而下地从需求导向、数据支撑和技术驱动三个维度对数据应用场景模型进行梳理阐释。[结果/结论]形成涵盖4个一级场景、14个二级场景和41个三级场景的分类体系，构建以需求为导向、数据为支撑、技术为驱动三位一体的场景模型框架，并对模型的逻辑和内涵进行深入剖析和阐释，为拓展规范化数据的应用场景提供参考与指引。更多还原

【Abstract】 [Purpose/significance] As a new type of production factor, fully developing and utilizing data resources and expanding the application scenarios of standardized data are the necessary means to release the value and activate the potential of data elements.[Method/process] According to the idea of “scene identification-model design-model interpretation”,and the qualitative analysis method is used to identify the coding scenes of textual data, to form the classification system of data application scenes.The data application scenario model is constructed by combining innovative application cases, data life cycle theory, CRISP-DM model and data value chain, and the data application scenario model is explained from top to bottom in the three dimensions of demand-oriented, data-supporting and technology-driven.[Result/conclusion] We form a classification system covering 4 first-level scenarios, 14 second-level scenarios and 41 third-level scenarios, construct a scenario model framework that is demand-oriented, data-supported and technology-driven, and analyze and explain the logic and connotation of the model in depth to provide reference and guidance for broadening the application scenarios of normalized data.更多还原