数据治理是支撑煤矿智能化建设的底层技术，是煤矿智能化系统实现协同集控的关键保障。针对智能化煤矿数据治理缺乏顶层设计和方法论支撑的问题，从“理论基础、概念模型、基本原则、过程和程序、方法和工具、评估准则”6个方面构建智能化煤矿数据治理方法论体系，系统阐明有效实现智能化煤矿数据治理目标的依据和原则，为智能化煤矿数据治理的顶层设计提供理论基础和方法论支撑；参考相关技术标准，开发智能化煤矿数据治理实施框架，为智能化煤矿数据治理的管理实施提供具体路径和管理方法；基于分层架构思想，设计智能化煤矿数据治理技术架构，为智能化煤矿数据治理的技术实现提供技术方法和工具。研究结论如下：① 复杂系统理论、数据战略管理理论、数字连续性理论、公共治理理论、协同创新理论、信息生命周期理论和PDCA循环理论共同构成智能化煤矿数据治理的理论基础。② 智能化煤矿数据治理的概念模型由理念、目标、主体、客体、流程和工具5个核心概念维度构成，遵循业务导向、协同治理、文化驱动、技术赋能、流程嵌入、持续改进的基本原则。③ 智能化煤矿数据治理实施框架自顶向下阐释智能化煤矿数据治理的管理过程和关键程序，包括“统筹与规划、构建与运行、监控与评价、改进与优化”4个循环迭代的关键环节。④ 智能化煤矿湖仓一体技术架构阐述智能化煤矿数据治理平台的系统结构和技术选型，为智能化煤矿数据治理的技术实现提供方法和工具，关键在于数据中台5大核心层级的开发。⑤ 智能化煤矿数据治理能力成熟度模型为智能化煤矿数据治理提供评估准则框架和能力提升路径，由“能力成熟度等级、数据治理能力、数据治理实践”3个维度耦合而成，遵循“项目化管理—流程化管理—标准化管理—定量化管理—标杆化管理”的渐进式发展规律。

Data governance underpins the intelligent development of coal mines and ensures collaborative centralized control of mine systems. To tackle the issues of inadequate top-level design and methodological support in intelligent coal mine data governance, a methodological system has been developed. The methodological system comprises six key components: theoretical foundation, conceptual model, basic principles, processes and procedures, methods and tools, and evaluation criteria. It systematically clarifies the basis and principles for effectively realizing the goals of intelligent coal mine data governance, and provides the theoretical foundation and methodological support for the top-level design of intelligent coal mine data governance. Meanwhile, the implementation framework for intelligent coal mine data governance is developed with reference to relevant technical standards, which provides specific paths and management methods for the management and implementation of intelligent coal mine data governance. Furthermore, the technical architecture for intelligent coal mine data governance is designed based on the idea of layered architecture to provide technical methods and tools for the technical realization of intelligent coal mine data governance. The following study results have been obtained. ① The theoretical foundation of intelligent coal mine data governance is grounded in complex system theory, data strategy management theory, digital continuity theory, public governance theory, collaborative innovation theory, information lifecycle theory and PDCA cycle theory. ② The conceptual model of intelligent coal mine data governance consists of five core conceptual dimensions: governance philosophy, governance goals, governance subjects, governance objects, and governance processes and tools. It adheres to the principles of business orientation, collaborative governance, culture-driven, technology-enabled, process-embedded, and continuous improvement. ③ The implementation framework of intelligent coal mine data governance delineates the management processes and key procedures from the top down, encompassing four key links of the iterative cycle: coordination and planning, construction and operation, monitoring and evaluation, and improvement and optimization. ④ The technical architecture of the Data Lakehouse for intelligent coal mine describes the system structure and technology selection for the data governance platform. It offers technical methods and tools to facilitate the implementation of intelligent coal mine data governance, with the core focus on developing the five key layers of the data middle platform. ⑤ The data governance capability maturity model for intelligent coal mines provides an assessment criteria framework and capability improvement pathway. It encompasses three dimensions namely, the level of capability maturity, data governance capabilities, and data governance practices. The enhancement of data governance capabilities in intelligent coal mines progresses from project management to benchmarking, encompassing process, standardization, and quantitative management stages.