Research on intelligent coal mine data governance system and key issues
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摘要: 智能化煤矿数据治理是实现煤矿智能化建设高阶段发展目标的关键瓶颈，对于确保数据运营合规、保障数据质量、防控数据风险、提升数据价值具有重要意义，但目前缺乏完善的方法论体系指导智能化煤矿数据治理的理论研究和技术实践。针对该问题，从数据治理要素、治理机制、治理层次和治理过程4个维度构建智能化煤矿数据治理要素−机制−层次−过程参考模型，提供多维度融合的方法论视角和理论分析逻辑，达成对关键问题的认识。分析得出复杂系统理论、数据战略管理理论、协同创新理论、数字连续性理论、公共治理理论、信息生命周期理论、PDCA循环理论是智能化煤矿数据治理重要的理论基础。在智能化煤矿数据治理参考模型的指导下，基于相关理论基础，构建包括数据治理环境、驱动与保障因素、顶层设计、数据治理域、数据治理过程与能力5大组成部分的智能化煤矿数据治理体系框架。对标智能化煤矿数据治理体系框架，得出智能化煤矿数据治理尚需进一步突破数据价值运动规律揭示、元数据与数据字典构建、数据质量和数据安全体系管理规则设计、复杂巨系统数据耦合模型开发和数字智慧发生规律建模等5个方面的关键问题。Abstract: Intelligent coal mine data governance is the key bottleneck to achieving the high-level development goal of coal mine intelligent construction. It is of great significance to ensure data operation compliance, ensure data quality, prevent and control data risks, and improve data value. However, there is a lack of perfect methodology to guide the theoretical research and technical practice of intelligent coal mine data governance. In order to solve this problem, an intelligent coal mine data governance element-mechanism-hierarchy-process reference model is constructed from four dimensions of data governance elements, governance mechanism, governance hierarchy and governance process. It provides a multi-dimensional fusion methodology perspective and theoretical analysis logic to achieve an understanding of key issues. It is concluded that complex system theory, data strategic management theory, collaborative innovation theory, digital continuity theory, public governance theory, information life cycle theory, and PDCA cycle theory are the important theoretical basis of intelligent coal mine data governance. Under the guidance of the reference model of intelligent coal mine data governance, and based on the relevant theoretical basis, an intelligent coal mine data governance system framework is constructed. It includes five major components: data governance environment, driving and supporting factors, top-level design, data governance domain, and data governance process and capability. Benchmarking the framework of intelligent coal mine data governance system, it is concluded that intelligent coal mine data governance still needs to further break through the five key issues. The issues are data value movement law disclosure, metadata and data dictionary construction, data quality and data security system management rule design, complex giant system data coupling model development and digital intelligence generation law modeling.
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Keywords:
- intelligent coal mine /
- data governance /
- data management /
- data value /
- data quality /
- data security /
- data standard
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编者按：《关于加快煤矿智能化发展的指导意见》指出，要以数据为核心资源，推动煤矿智能化技术开发和应用模式创新。随着大数据、人工智能等技术的不断发展和应用，煤矿大数据呈现爆炸式增长，对这些数据进行有效的管理、分析和挖掘，对于提高矿山生产效率和资源利用率、优化矿山生产结构具有重要意义，然而现有的数据治理模式还存在一些亟需解决的问题。为推动煤矿智能化建设高质量发展，提升矿山数据治理水平，实现数据融合共享和智能化应用，《工矿自动化》编辑部特邀中国矿业大学（北京）谭章禄教授担任客座主编，汪莹教授、刘婵副教授、王美君博士担任客座副主编，于2023年第5期组织出版“智能化矿山数据治理”专题。在专题刊出之际，衷心感谢各位专家学者的大力支持！
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图 1 智能化煤矿数据治理要素−机制−层次−过程参考模型
Figure 1. The element-mechanism-hierarchy-process reference model of intelligent coal mine data governance
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