智慧治理中的数据质量管理:核心要素、机制构建、支撑保障

Data Quality Management in Smart Governance: Core Elements, Mechanism Construction, and Support Guarantee

  • 摘要: 为探究智慧治理中数据质量管理路径,推进数据质量提升,促进智慧治理成效凸显,本文从核心要素、机制构建与支撑保障三个维度,选择传染病监测预警管理进行案例研究,搭建智慧治理中数据质量管理的分析框架。数据质量是影响智慧治理效能的重要因素之一,智慧治理中数据来源及相关方、数据流转环节是数据质量管理的核心要素,质量提升、流程改善经典方法可有效适用于智慧治理,政策保障、技术工具和机制迭代是数据质量管理长效执行的重要保障。智慧治理阶段性及治理成效需求决定数据质量管理要求,数据质量管理能实现智慧治理效能提升、数据要素市场高质量发展,进一步推动数据质量管理理念和方法在数据全周期各环节的实践落地。

     

    Abstract: This paper is to explore the path of data quality management in smart governance, promote the improvement of data quality, and highlight the effectiveness of smart governance. It builds an analytical framework for data quality management in smart governance from three dimensions: core elements, mechanism construction, and support guarantee,with infectious disease monitoring and early warning management as a case study. Data quality is one of the important factors affecting the effectiveness of smart governance. The source and stakeholders of data, as well as the data flow process, are the core elements of data quality management in smart governance. Classic methods for quality improvement and process improvement can be effectively applied to smart governance. Policy guarantees, technological tools, and mechanism iterations are important guarantees for the long-term implementation of data quality management. The phased nature of smart governance and the demand for governance effectiveness determine the requirements for data quality management. Data quality management can achieve the improvement of smart governance efficiency, high-quality development of the data element market, and further promote the practical implementation of data quality management concepts and methods in all aspects of the data cycle.

     

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