[目的/意义]文章旨在构建一个标准化视角下覆盖多维度和多方面要素的大模型数据治理的理论框架，以填补当前大模型数据治理专门性研究和标准化研究的空白，丰富大模型数据治理的理论研究内容，并为实际应用提供参考。[方法/过程]综合采用内容分析法和专家咨询法，对国内外相关标准、中英文代表性期刊文献进行系统梳理和分析，迭代优化并构建大模型数据治理的理论框架。[结果/结论]大模型数据治理的理论框架涵盖多个维度，包括大模型数据质量管理、大模型数据管理、大模型数据资源管理、大模型数据资产管理、大模型数据风险管理。五个维度沿着“基础前提-执行方式-实施路径-核心目标-内在保障”的逻辑构成理论框架。

[Purpose/significance] This study aims to build a theoretical framework for large model data governance from a standardization perspective, covering multidimensional and multifaceted elements. This framework seeks to fill in current gaps in specialized research and standardization research on large model data governance, which will enrich theoretical research on large model data governance and provide implications to practices. [Method/process] By holis⁃tic approach to content analysis and expert consultation, this study systematically reviews and analyzes relevant stan⁃dards and representative Chinese and English journal literature, iteratively refining and constructing a theoretical framework for large model data governance. [Result/conclusion] The theoretical framework for large model data gover⁃nance covers multiple dimensions, including large model data quality management, large model data management, large model data resource management, large model data asset management, and large model data risk management. These five dimensions are structured along with the logical progression of "fundamental premises - execution methods - im⁃plementation pathways - core objectives - intrinsic guarantees"，forming a comprehensive theoretical framework.