Abstract:
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.