食品安全监管大数据质量评估体系构建研究

Research on Construction of Big Data Quality Assessment System for Food Safety Supervision

食品安全监管的核心是充分利用各种数据资源,但由于食品数据涉及部门和来源方式多样化,是典型的多源异构数据,需要对数据质量进行评估,以便于采取相应的数据治理手段提升数据质量,从而为食品监管大数据应用奠定建设基础。本文对食品监管大数据进行梳理,对食品生产经营主体的经营主体登记注册数据、行政监管数据、经营行为数据、消费投诉数据、互联网舆情数据进行剖析。随后充分考虑数据特点,提出数据全面性、数据完整性、数据冗余性、数据规范性、数据一致性和数据异常值六个方面的数据质量评估体系。最后,对食品大数据质量评估机制建设提出了相关对策建议。

The core of food safety supervision is to make full use of all kinds of data resources.However,food data involves various departments and sources,which are typical multi-source heterogeneous data,making it necessary to evaluate data quality,in order to take corresponding measures of data governance to improve data quality,and lay a foundation for the big data application of food supervision.This paper comprehensively sorts out the food supervision data,and analyzes the registration data of operation entities,administrative supervision data,business behavior data,consumer complaint data,and internet public opinion data of food production and operation entities.Taking full account of the characteristics of data,the paper proposes a data quality evaluation system,including data comprehensiveness,data integrity,data redundancy,data normalization,data consistency and data outlier.The paper also puts forward relevant measures and suggestions for the construction of a big data quality evaluation mechanism for food.