[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.