摘要
随着数据科学技术发展与应用,数据日益成为重要的生产资料和战略资源。高质量的数据是提升其社会价值和生产潜力的重要前提。国内外各界从多维角度评价数据质量,有些领域结合行业特点开发数据质量检测系统来监控数据质量问题。通过分析数据质量评估国内外研究现状,提出一种面向多领域标准的数据质量评估框架,来评估数据质量的一致性。首先对标准解析和知识图谱梳理,得到知识图谱模型;接着以此模型为基础,搭建标准池库;随后设计数据标准符合性检测系统。分析验证提出的框架模型具有正确性、合理性和可扩展性和通用性。
With the development and application of data science and technology,data has increasingly become an important means of production and strategic resources.High-quality data is an important prerequisite to enhance its social value and productivity potential.All walks of life at home and abroad evaluate data quality from a multidimensional perspective,and data quality detection system is developed in some areas to monitor data quality problems in accordance with industry characteristics.By analyzing the research status of data quality assessment at home and abroad,a data quality assessment framework oriented to mul-ti-domain standards is proposed to evaluate the consistency of data quality.In this paper,the standard analysis and knowledge map are sorted out,and the knowledge map model is obtained.Based on this model,the standard pool is built,and the data standard conformity detection system is designed.The analysis verifies the correctness,rationality,scalability and generality of the proposed framework model.
作者
尹榕慧
姚祖发
YIN Rong-hui;YAO Zu-fa(Guangdong Science and Technology Foundation Platform Center;Guangdong Provincial Key Laboratory of High Performance Computing)
出处
《标准科学》
2020年第1期92-95,共4页
Standard Science
关键词
数据质量
数据质量评估
标准
数据标准符合性
data quality
data quality assessment
standard
data standard compliance
