数据质量评估及改进策略——基于某市公共基础数据库（人口库和法人库）的检测分析

doi:10.13998/j.cnki.issn1002-1248.25-0664

Abstract

Abstract:

[Purpose/Significance] As data become a strategic resource in the digital economy, its quality directly affects the efficiency of value creation and the effectiveness of public governance. However, with the continuous expansion of data scale and the deepening of application scenarios, pervasive quality issues - such as inconsistencies, errors, and redundancies - have emerged as a significant bottleneck restricting the release of data element potential. High-quality public data are particularly critical for empowering government decision-making and optimizing public services. Addressing the urgent practical need for high-quality data supply, this paper relies on the public basic databases (specifically the Population Database and Legal Entity Database) of a representative city to construct a scientific, systematic, and operable data quality assessment system. The study aims to diagnose existing quality defects in these foundational assets and provide theoretical support and actionable references for relevant departments to transition from passive data management to active quality governance. [Method/Process] To ensure the assessment is both scientifically rigorous and practically applicable, this study establishes a comprehensive evaluation framework based on domestic and international research, combined with the national standard GB/T 36344-2018 and local data characteristics. The framework comprises a hierarchical structure with 6 primary indicators (Normativity, Integrity, Consistency, Accuracy, Timeliness, and Accessibility), 17 secondary indicators, and 61 specific detection items. The study employs a dual-track assessment methodology integrating automated detection tools with manual verification. Automated SQL scripts and rule engines are utilized for the large-scale quantitative detection of intrinsic dimensions, while manual checks and interviews address contextual dimensions. This methodology was applied to conduct a multi-dimensional evaluation of 1 367 data items across 102 datasets in the city, ensuring a thorough analysis of the data status. [Results/Conclusions] The evaluation results indicate that while the overall construction of the city's public basic databases is positive, multidimensional quality issues persist. Specifically, the assessment revealed problems such as data coding errors, non-standardized classification, missing data items, missing or duplicate primary keys, inconsistent formats, the presence of illegal characters or outliers, and data delays or discontinuations. To address these challenges, the paper proposes four systematic improvement strategies: 1) To unify data standards and coding systems to ensure consistency across departments; 2) To construct a full-process quality control mechanism covering data collection, storage, and usage; 3) To strengthen technical platform support by implementing real-time monitoring and intelligent warning capabilities; and 4) To improve organizational synergy and institutional guarantees to solidify the management foundation. These measures are intended to optimize data supply quality and support the support the high-quality and sustainable development of the data element market.

Key words: data quality, public basic databases, assessment system, quality management

CLC Number:

G203

PAN Yong, SUN Jing, WANG Jiandong. Data Quality Assessment and Improvement Strategies: A Diagnostic Analysis Based on the Public Basic Databases (Population and Legal Entity Databases) of a City[J].Journal of library and information science in agriculture, 2026, (): 1-11.

Figures/Tables 4

Fig.1

Fig.2

Fig.3

Table 1

Evaluation results of data quality for public infrastructure databases"

序号	数据质量维度			检测指标	得分	测量粒度	检测方式
序号	一级指标	得分	二级指标	检测指标	得分	测量粒度	检测方式
1	数据规范性	94.22	数据标准	手机号码	98.69	字段	程序
2				证件号码	99.76	字段	程序
3				统一社会信用代码	97.11	字段	程序
4				工商注册号	92.52	字段	程序
5				办公电话/传真	98.27	字段	程序
6				邮政编码	84.83	字段	程序
7			权威参考数据源	证件类型	77.54	字段	程序
8				地区代码	82.22	字段	程序
9				行业代码	97.58	字段	程序
10				企业类型代码	99.92	字段	程序
11				组织机构代码	98.6	字段	程序
12				经营范围	97.3	字段	程序
13				残疾类别	100	字段	程序
14				残疾等级	100	字段	程序
15				学校代码	100	字段	程序
16				行政许可事项分类代码	99.91	字段	程序
17			业务规则	残疾人证号	99.99	字段	程序
18				医保系统单位编码	100	字段	程序
19				银行卡号编码	100	字段	程序
20				药品经营许可证编号	100	字段	程序
21				食品小作坊登记证编号	91.86	字段	程序
22				临时建设用地规划许可证编码	91.2	字段	程序
23				食品生产许可证编号	100	字段	程序
24				食品经营许可证编号	94.92	字段	程序
25				医疗器械注册证编号	97.74	字段	程序
26				个体工商户字号	98.28	字段	程序
27				个体工商户组织形式	90.25	字段	程序
28				特种设备目录	99.01	字段	程序
29			安全规范	隐私字段加密检测	96.28	字段	程序
30	数据完整性	78.06	数据记录完整性	数据备份与恢复	100	数据集	访谈
31				数据记录完整性检测	89.35	数据集	程序
32				数据更新完整性	100	数据集	访谈
33				覆盖量	100	数据集	访谈
34			数据元素完整性	地址完整性检测	80.34	字段	程序
35			数据元素完整性	数据完整性校验	0.00	字段	程序
36	数据一致性	93.43	关联数据一致性	关联性检测	83.15	数据集	程序
37			相同数据一致性	日期一致性检测	98.59	字段	程序
38				数值一致性检测	97.85	字段	程序
39				值域一致性检测	94.02	字段	程序
40				数据编码一致性检测	99.97	数据集	程序
41				主键一致性检测	72.72	字段	程序
42				地址一致性检测	79.31	字段	程序
43				计量单位一致性检测	100	字段	程序
44	数据准确性	97.63	数据格式合规性	数值范围检测	96.42	字段	程序
45			数据内容正确性	数据来源	100	数据集	访谈
46				数据收集方式	100	数据集	访谈
47				数据更新策略	100	数据集	访谈
48			数据唯一性	唯一标识检测	97.70	数据集	程序
49			数据重复率	重复记录检测	98.26	字段	程序
50			脏数据出现率	错误值检测	89.72	字段	程序
51	数据时效性	87.70	基于时间段的正确性	时效正确性检测	84.94	数据集	程序
52			基于时间点的及时性	数据更新频率	100	数据集	访谈
53				数据采集时间戳检测	69.45	数据集	程序
54				数据延迟检测	93.85	数据集	程序
55				数据断更检测	90.20	数据集	程序
56	数据可访问性	100	可访问	数据授权机制	100	数据集	访谈
57			可访问	数据共享能力	100	数据集	访谈
58			可用性	接口可用性	100	数据集	访谈
59				数据文档完整性	100	数据集	访谈
60				数据访问性能	100	数据集	访谈
61				数据可理解性	100	数据集	访谈

Table 1

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Data Quality Assessment and Improvement Strategies: A Diagnostic Analysis Based on the Public Basic Databases (Population and Legal Entity Databases) of a City

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