People's Daily Jinan, February 17 (Song Cui) "It is recommended to comprehensively strengthen the comprehensive management and utilization of food safety big data from the provincial level, break down data barriers, build a food safety big data platform, and comprehensively promote 'smart supervision'." Hu Mei, member of the Shandong Provincial Committee of the Chinese People's Political Consultative Conference and vice president of the Provincial Food and Drug Inspection and Research Institute, proposed at the "two sessions" in Shandong.
In February 2017, the State Council issued the "13th Five-Year Plan" National Food Safety Plan, which pointed out that food safety supervision should use the "Internet" and big data to implement online smart supervision. At present, with the establishment of the provincial big data bureau and the gradual reform of food-related institutions, it is time to promote the management, analysis and comprehensive utilization of food safety big data.
Hu Mei analysis believes that compared with the development level of big data, Internet, cloud computing, Internet of Things and other technical means, the management and application of food safety big data is still in its infancy. Compared with the rich data resources contained in the food production supply chain from farmland to table, the current collection of food safety big data only covers the tip of the iceberg, and the data acquisition of many links is in a blank state, especially in the aspects of food electronic transactions, online transactions, online catering, etc. There is a prominent information asymmetry in the government regulatory departments, which affects the scientificity and accuracy of regulatory decisions.
At the same time, food safety information data lacks unified management. Under the general trend of gradual unification of food safety supervision, food safety data information management is subject to the "island" effect - provinces, cities and counties, market supervision, agriculture and animal husbandry, industry associations and other levels and departments have established a large number of data systems or information platforms, and the lack of connectivity between them, poor liquidity between data resources, inefficient use and waste of construction resources coexist.
Third, the development of food safety information data analysis technology is lagging behind. The key to the development of the value of data resources is analysis methods and analysis techniques, exploring the derivation of food safety risks through food safety data analysis, and strengthening regulatory orientation to become a research hotspot worldwide. At present, the food safety data analysis methods of Shandong government departments cannot meet the requirements of risk early warning management and effective control of the whole process, and the relevant basic research does not match the complex and changeable food safety situation, and cannot support the effective use of data information.
In this regard, Hu Mei suggested that the comprehensive management and utilization of food safety big data should be comprehensively strengthened from the provincial level.
The first is to improve the top-level planning of food safety big data and promote the construction of data platform infrastructure. Fully clarify the public resource attributes and strategic significance of food safety big data, design and build a data information system and overall architecture covering the whole chain of breeding, production, processing, transportation, operation, storage, quality and safety supervision, pollution monitoring, disease control, laboratory testing, public opinion monitoring, etc., use data as a link to plan food-related government data resources and social data resources, form a unified big data platform, do a good job in infrastructure construction of information collection and information management, and eliminate data blind spots.
The second is to break down data barriers and realize the data connectivity of various departments of food safety. Do a good job in the coordination and linkage and data access of food safety related institutions at all levels and departments, build a bridge between information "islands", and realize cross-level, cross-regional, cross-system, cross-departmental, and cross-business data fusion, resource sharing, collaborative management and comprehensive utilization.
The third is to strengthen the application of big data in food safety decision-making with regulatory needs as the guide. We should establish big data thinking in food safety supervision, organically combine big data with traditional regulatory means such as food safety supervision and sampling, risk monitoring, and on-site inspection, give full play to the advantages of big data tools in perception, summary, refinement, analysis, etc. for complex information and potential risks, promote the innovation of supervision models and regulatory ideas, improve the ability to capture, predict and prevent food safety risk factors, and realize the scientific, precise and efficient decision-making of food safety.
The fourth is to increase investment and guarantee for the research of food safety big data analysis technology. Take scientific research projects as the starting point, encourage research work in food safety information data statistics, trend analysis, model establishment, risk identification, factor mechanism, natural and social impact, etc., create a benign food safety big data research environment, and use scientific research as the engine to promote the overall improvement of big data management and analysis application capabilities.
The fifth is to cultivate professional talents and strengthen the construction of food safety big data talent team. Professional human resources are the necessary guarantee for career development. It is recommended to promote the cross-integration of food science, public health, statistics, information technology and other disciplines, develop and explore food safety big data as an independent discipline, and create conditions for the incubation of talents; at the same time, efforts should be made to cultivate a group of professionals and teams of moderate scale, reasonable structure and exquisite business within the regulatory departments, and enhance the ability of the regulatory authorities to use data to promote various work.