基于本体论的食品安全数据融合框架研究

庞杂的食品安全抽检数据由于分类编码问题不统一而使得数据融合难以实现，并进一步阻碍了与其他监测系统的融合与数据分析。解决各种食品安全数据融合的问题将对国家的食品安全监管具有重要意义，文章归纳总结了食品安全大数据在分类编码方面的主要存在问题，引入本体论的思想，并结合计算机工程，提出了构建基于本体论的计算机工程与大数据分析相结合的总体框架，以实现数据融合，服务政府和企业的有效监管。

Research on food safety data fusion framework based on ontology

The complicated food safety sampling data makes data fusion difficult to achieve due to the inconsistency of classification and coding problems. Addressing the integration of various food safety data will be of great importance to national food safety regulation. The paper summarized the main problems in the classification and coding of food safety big data, introduced the ontological idea and combining with computer engineering, proposed an overall framework for constructing an ontology-based computer engineering and big data analysis, so as to achieve data fusion and serve the effective supervision of the government and enterprises.