[目的/意义]数据驱动治理背景下，破解政府数据治理政策“碎片化”难题、实现政策整体效能提升，已成为释放数据要素价值、构建现代化治理体系的关键突破口。[方法/过程]基于“动态演变解析→协同联动挖掘→增效路径提炼”的三阶研究范式，在构建政府数据治理政策增效理论框架的基础上，依托GraphRAG框架，融合大语言模型的深度语义推理能力与知识图谱的多维关系映射技术，解析我国政府数据治理政策的演变过程与演变规律，进而分析政策主体协作与政策内容要素联动，挖掘我国政府数据治理政策的协同困境，最后提出增效路径建议，为政府数据治理政策优化提供“演变解读-协同优化-效能提升”的实践方向。[结果/结论]我国政府数据治理政策演变呈现主体从“条块分割”到“多维协同生态”、内容从“单点突破”到“系统赋能”、认知从“被动响应”到“价值自觉”的演变特征；存在“蜂窝化隔离”与“广度-强度失衡”等协同困境；必须构建跨领域协同治理生态、完善政策内容动态适配机制和提升多维度政策整体合力，以期提升政策整体效能。

[Purpose/significance] In the context of data-driven governance, solving the problem of fragmented govern⁃ment data governance policies and achieving overall policy effectiveness improvement have become key breakthroughs in unleashing the value of data elements and building a modern governance system. [Method/process] This article is based on the third-order research paradigm of "dynamic evolution analysis→ collaborative linkage mining → efficien⁃cy improvement path extraction". On the basis of constructing the theoretical framework of government data governance policy efficiency improvement，relying on the GraphRAG framework and integrating the deep semantic reasoning abili⁃ty of the big language model with the multidimensional relationship mapping technology of the knowledge graph, this ar⁃ticle analyzes the evolution process and evolution law of China's government data governance policy. Furthermore, it an⁃alyzes the collaboration of policy subjects and the linkage of policy content elements, explores the collaborative difficul⁃ties of China's government data governance policy, and finally proposes efficiency improvement path suggestions, pro⁃viding a practical direction of "evolution interpretation collaborative optimization efficiency improvement" for optimiz⁃ing government data governance policy. [Result/conclusion] China's government data governance policies have evolved from "block segmentation" to "multi-dimensional collaborative ecology", from "single point breakthrough" to "system empowerment", and from "passive response" to "value consciousness" in cognition; there are collaborative challenges such as "cellular isolation" and "breadth intensity imbalance"; it is necessary to build a cross domain collab⁃orative governance ecosystem, improve the dynamic adaptation mechanism of policy content, and enhance the overall synergy of multidimensional policies in order to improve the overall effectiveness of policies.