Visualization system for risk grading data of food production and operation subjects

Abstract

The invention provides a food production and operation subject risk grading data visualization system, and belongs to the technical field of risk grading. The food production and operation subject risk grading data visualization system comprises a data receiving module, an area overall condition module, a subject risk information module, a risk identification module and a time trend comparison module. On the basis of mathematical statistics, information presentation is enhanced by means of a visualization technology, and multi-dimensional, high-complexity and large-data-volume risk grading data are vividly, rapidly and interactively displayed in a vivid, rich and efficient mode, so that distribution of single factors and the relation among the multiple factors are deeply explored.

Description

Technical Field

[0001] This invention relates to the field of risk classification technology, specifically to a visualization system for risk classification data of food production and operation entities. Background Technology

[0002] Risk grading of food production and operation entities refers to the dynamic classification of risk levels for food producers and operators by market supervision and management departments based on factors such as food category, business scale, management capabilities, and record-keeping, using quantitative indicators. This approach coordinates regulatory resources and capabilities to implement differentiated and precise supervision and management of food producers and operators, helping to strengthen risk management in food production and operation, optimize the allocation of regulatory resources, implement supervision scientifically and effectively, fulfill food safety regulatory responsibilities, and ensure food safety. As a classification method that integrates information from all stages of breeding, production, processing, storage, transportation, sales, and consumption, risk grading has demonstrated increasingly significant application value in the field of market supervision and management.

[0003] While information technology is currently used for risk assessment of food production and business entities, the complexity of food safety risk factors, the large number of entities, and their varying circumstances result in a large volume of rapidly updating and wide-ranging food safety data, making analysis challenging. Furthermore, local regulatory departments lack supporting information technology tools and have limited professional personnel, leading to problems such as the current manual data collection and analysis methods being simplistic and inefficient, and the absence of post-evaluation of food safety data. Therefore, the lack of tools to support risk classification and categorization management necessitates the urgent need for technical means for tiered data analysis and visualization. Summary of the Invention

[0004] The purpose of this invention is to address the shortcomings of the prior art by proposing a visualization system for risk classification data of food production and operation entities.

[0005] This invention proposes a visualization system for risk classification data of food production and operation entities, including a data receiving module, a regional overall status module, an entity risk information module, a risk identification module, and a time trend comparison module. The data receiving module is used to receive operating data from multiple producers and operators in various business formats within a region. The regional overall status module is used to obtain information reflecting the proportion of producers and operators with different risk levels in various business formats within the region and the changes in producers and operators with different risk levels over the years, based on the operating data. The entity risk information module is used to retrieve the first risk information for the target producer and operator by calling the proportion information. The risk identification module is used to retrieve the main risks of the target producer and operator based on the first risk information. The time trend comparison module is used to retrieve the change information to obtain comparative information of the target producer and operator for two different years.

[0006] Furthermore, the overall regional status module, the main risk information module, the risk identification module, and the time trend comparison module all include static graphics and dynamic interactive graphics. The static graphics include specific information units for providing specific information; the dynamic interactive graphics include additional information units for displaying additional information when the cursor moves to a specific position. The dynamic interactive graphics can be scaled for the entire image area or a selected image area.

[0007] Furthermore, the overall regional status module also includes a spatial distribution unit to reflect the spatial distribution of producers and operators within the region, a risk display unit to display the static and dynamic risks of each producer and operator within the region, and a change display unit to display the producers and operators with the greatest changes in risk scores over time and the changes in their previous inspections.

[0008] Furthermore, the risk information includes primary risk factors and major secondary risk factors. The main risk information module also includes a score change unit for recording the score changes of the selected producer / operator in each inspection.

[0009] Furthermore, the risk identification module also includes a risk classification unit that divides serious items, key items, and non-key items according to the first risk information, and a risk acquisition unit that obtains the main risks based on serious items, key items, and non-key items.

[0010] Furthermore, the risk classification unit is used to organize the mean score and quartile of each risk item among producers and operators in the region, and classify them into serious items, key items and non-key items based on the mean score and quartile.

[0011] Furthermore, the risk classification unit uses an interactive box plot to organize the mean and quartile scores of each risk item among producers and operators in the region.

[0012] Furthermore, the risk identification module also includes a scoring display unit for displaying the scores of each producer and operator on each risk item.

[0013] Furthermore, the time trend comparison module also includes a screening unit for filtering risk items where the score difference of a specified business type exceeds a preset value between two specified years, and a comparison unit for comparing the score data distribution of a specified risk item between two years and the score changes of each producer and operator.

[0014] Furthermore, the comparison unit includes an interactive density plot and a Cleveland dot plot, which respectively compare the distribution of score data for a specified risk item between two years and the score changes of each producer and operator.

[0015] The visualization system for risk grading data of food production and operation entities of the present invention has the following beneficial effects: The data receiving module receives operational data from multiple producers and operators across various business sectors within the region. The overall regional status module obtains information reflecting the proportion of producers and operators with different risk levels across different business sectors within the region, as well as information on the annual changes in producers and operators with different risk levels, based on the operational data. The main risk information module retrieves the proportion information to obtain the primary risk information for the target producer and operator. The risk identification module retrieves the primary risk information for the target producer and operator. The time trend comparison module retrieves the change information to obtain comparative information for the target producer and operator across two different years. Based on mathematical statistics, visualization technology is used to enhance information presentation, providing a vivid, rich, and efficient display of multi-dimensional, highly complex, and large-volume risk classification data in an intuitive, fast, and interactive manner, in order to deeply explore the distribution of single factors and the relationships between multiple factors. Attached Figure Description

[0016] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and, together with the description, serve to explain the principles of the invention. In these drawings, similar reference numerals are used to denote similar elements. The drawings described below are some embodiments of the invention, but not all embodiments. Other drawings will be readily available to those skilled in the art based on these drawings without any inventive effort.

[0017] Figure 1 This is a schematic diagram of the structure of a visualization system for risk classification data of food production and operation entities according to an embodiment of the present invention; Figure 2 This is a schematic diagram of the regional overall status module in a visualization system for risk classification data of food production and operation entities according to an embodiment of the present invention; Figure 3 This is a schematic diagram of the entity risk information module in a visualization system for risk classification data of food production and operation entities according to an embodiment of the present invention; Figure 4 This is a schematic diagram of the risk identification module in a visualization system for risk classification data of food production and operation entities, according to an embodiment of the present invention. Figure 5 This is a schematic diagram illustrating time trend comparison in a visualization system for risk classification data of food production and operation entities, according to an embodiment of the present invention. Figure 6 This invention provides a visualization system for risk classification data of food production and operation entities, including risk level tree diagrams for various business types and business type tree diagrams for each risk level. Figure 7This invention provides a spatial distribution map of various business entities and a time trend area map showing the proportion of each risk level entity in a visualization system for risk classification data of food production and operation entities, as well as an example of the present invention. Figure 8 This invention provides a visualization system for risk classification data of food production and operation entities, including a distribution chart of the total risk score of each business entity and a line graph of the total risk score of the top ten entities with the largest range of total risk scores in each historical period. Figure 9 This invention provides a visualization system for risk classification data of food production and operation entities, which includes a spatial distribution map of the total risk score of a specific business entity and a clustering bubble diagram of the dynamic and static risks of each business entity. Figure 10 This is a line graph showing the scores of the top ten statistical items across the score range for a specific business in a visualization system for risk classification data of food production and operation entities, as described in an embodiment of the present invention. Figure 11 This is a radar chart showing the primary risk factor score of a designated business in a visualization system for risk classification data of food production and operation entities, as described in an embodiment of the present invention. Figure 12 This is a bar chart showing the ranking of the top ten secondary risk factors for a specific business in a visualization system for risk classification data of food production and operation entities, as described in an embodiment of the present invention. Figure 13 The present invention relates to a visualization system for risk classification data of food production and operation entities, which includes heatmaps and horizontal box plots of scores for various business types for a specified business type. Figure 14 This invention provides a visualization system for risk classification data of food production and operation entities, which includes principal component analysis plots of scores for various business types and correlation coefficient matrices of scores for various business types. Figure 15 This is a scatter plot of the correlation of a specified item and a score distribution comparison plot of a specified data range in a visualization system for risk classification data of food production and operation entities, as described in an embodiment of the present invention. Figure 16 This is a Cleveland dot plot comparing two scores within a specified data range in a visualization system for risk classification data of food production and operation entities, as described in an embodiment of the present invention. Figure 17 This is a bar chart showing the difference between two scores within a specified data range in a visualization system for risk classification data of food production and operation entities, as described in an embodiment of the present invention. Figure 18 This is a spatial distribution map of the difference between two scores within a specified data range in a visualization system for risk classification data of food production and operation entities, as described in an embodiment of the present invention.

[0018] In the diagram: 101 - Data receiving module, 102 - Overall regional status module, 103 - Main risk information module, 104 - Risk identification module, 105 - Time trend comparison module. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention. It should be noted that, unless otherwise specified, the embodiments and features in the embodiments of this application can be arbitrarily combined with each other.

[0020] Please see Figure 1-18 This invention discloses a visualization system for risk grading data of food production and operation entities, comprising a data receiving module 101, a regional overall status module 102, an entity risk information module 103, a risk identification module 104, and a time trend comparison module 105. The data receiving module 101 receives operating data from multiple producers and operators in various business sectors within the region. The regional overall status module 102 obtains information reflecting the proportion of producers and operators with different risk levels in various business sectors within the region and the changes in the proportion of producers and operators with different risk levels over the years based on the operating data. The entity risk information module 103 retrieves the proportion information to obtain the first risk information for the target producer and operator. The risk identification module 104 retrieves the main risks of the target producer and operator based on the first risk information. The time trend comparison module 105 retrieves the change information to obtain comparative information of the target producer and operator for two different years.

[0021] This application describes a data visualization system for risk grading of food production and operation entities, built using the R language and extension packages such as ggplot2, plotly, and shiny. It utilizes a series of static and dynamic interactive graphics to assist in the analysis of risk grading data, achieving a comprehensive display and human-computer interaction of the risk grading data. Based on the needs of grassroots supervision and experience in grading evaluation, this application designs four modules: a regional overall situation module (102), an entity risk information module (103), a risk identification module (104), and a time trend comparison module (105).

[0022] Specifically, in the field of public health, R is a popular open-source programming language. R provides an interactive environment for data science work and is the most widely used mathematical statistics tool across various fields. Thanks to well-known data visualization packages such as ggplot2, a key feature of the R language is its powerful data visualization capabilities, enabling data display based on graphical syntax. This application, based on the technical solution and the R 4.3.0 and RStudio 2023.03.0 integrated development environment, combined with extension packages such as ggplot2, plotly, shiny, and rmarkdown, implements risk grading data analysis and visualization for food production and operation entities, supporting automatic risk level calculation.

[0023] The overall regional status module 102, the main risk information module 103, the risk identification module 104, and the time trend comparison module 105 can all include static graphics and dynamic interactive graphics. Static graphics include specific information units used to provide specific information; dynamic interactive graphics include additional information units used to display additional information when the cursor moves to a specific position. Dynamic interactive graphics can zoom in and out of the entire image area or a selected image area.

[0024] Specifically, each module includes both rich static graphics and HTML-based dynamic interactive graphics to quickly, dynamically, and intuitively reflect various risk information in the region. Static graphics provide specific information; for example, the size of points in scatter plots and geospatial distribution maps reflects the scale of producers and operators. Dynamic interactive graphics display additional information such as names and ratings when the cursor moves to a specific location, and support zooming of the entire image or selected image areas. Clicking different legends can hide or show the corresponding categories in the interactive graphics to aid in filtering and more intuitively convey information. Furthermore, this application also includes several option buttons in each module based on data recognition and for automatic data filtering to achieve visualization of custom data ranges.

[0025] The overall regional status module 102 may also include a spatial distribution unit to reflect the spatial distribution of producers and operators within the region, a risk display unit to display the static and dynamic risks of each producer and operator within the region, and a change display unit to display the producers and operators with the greatest changes in risk scores over time and the changes in their previous inspections.

[0026] For details, see Figure 2Through embedded statistical functions and data visualization, the overall regional status module 102 can reflect the proportion of producers and operators with different risk levels in various business types within the region and their changes over the years, and different calendar years can be selected to switch data. The dynamic interactive graphics in the overall regional status module 102 also reflect the spatial distribution of producers and operators with different business types or risk scores within the region, compare the static and dynamic risks of each producer and operator within the region, and automatically find the producers and operators with the largest changes in risk scores over time and display their changes in each inspection. That is, the spatial distribution unit, risk display unit, and change display unit respectively constitute the overall regional status module 102 and perform corresponding actions through dynamic interactive graphics.

[0027] Risk information may include primary risk factors and major secondary risk factors. The main risk information module 103 also includes a score change unit for recording the score changes of the selected producer and operator in each inspection.

[0028] For details, see Figure 3 In addition to the overall situation, the built-in statistical functions and data visualizations allow users to view the risk information of a single producer or operator during a single inspection within the main risk information module 103. The score change unit records the score changes of the selected producer or operator in each inspection through a dynamic interactive graph.

[0029] The risk identification module 104 may also include a risk classification unit that divides serious items, key items and non-key items according to the first risk information, and a risk acquisition unit that obtains the main risks according to serious items, key items and non-key items.

[0030] The risk classification unit is used to compile the mean and quartile scores of each risk item among producers and operators in the region, and to classify the risk items into serious, key, and non-key items based on the mean and quartile scores.

[0031] The risk classification unit can use interactive box plots to organize the mean and quartile scores of each risk item among producers and operators in the region.

[0032] For details, see Figure 4 The risk identification module 104 uses embedded statistical functions and data visualization to organize the average score and quartiles of each risk item among producers and operators in the region using interactive box plots. Based on this, it classifies the risk items into serious items, key items and non-key items, thereby identifying the main risks.

[0033] The risk identification module 104 may also include a scoring display unit for displaying the scores of each producer and operator on each risk item.

[0034] Specifically, the scoring display unit uses an interactive heatmap to show the scores of each producer and operator on each risk item, making it easy for users to intuitively identify major risk items and high-risk entities. This allows observation of the spatial distribution and potential concentration of high-risk items within the region. Furthermore, the risk identification module 104 provides exploratory correlation analysis, including customizable scatter plots to observe the relationship between high-risk items and major statistical items, automatic principal component analysis of risk factors, and correlation matrices.

[0035] The time trend comparison module 105 may also include a filtering unit for filtering risk items where the score difference of a specified business type exceeds a preset value between two specified years, and a comparison unit for comparing the score data distribution of a specified risk item between two years and the score changes of each producer and operator.

[0036] The comparison unit may include interactive density plots and Cleveland dot plots, which compare the distribution of score data for a specified risk item between two years and the score changes for each producer and operator, respectively.

[0037] For details, see Figure 5 The time trend comparison module 105, through embedded statistical functions and data visualization, enables the comparison of data between two different years. First, the filtering unit automatically identifies risk items with significant differences in scores between two specified years for a given business type and presents them in a list format. Then, interactive density plots and Cleveland dot plots can compare the distribution of score data for the specified risk items, such as those with significant differences, between the two years, as well as the score changes for each producer and operator. The difference in the scores for this risk item for each producer and operator between the two years is statistically analyzed through an interactive sorted bar chart and also reflected in an interactive spatial distribution map.

[0038] Specifically, visualization technology is used to display risk classification data of food production and operation entities through features such as coordinate axes, colors, transparency, shapes, and sizes. This allows for a direct and comprehensive description of the characteristics, distribution, changes, and correlations of risks, enabling the identification, ranking, and risk comparison of key regions, industries, enterprises, and risk items within a specific context, thus simplifying risk assessment. Dynamic data visualization facilitates more effective interactive data analysis. Dynamically reading data and freely selecting the desired legend categories and visualization formats better meet the needs of exploratory data analysis in risk assessment. Furthermore, the embedded mathematical model supports local regulatory departments in conducting further data mining on production and operation inspection data generated within their jurisdiction, such as principal component analysis, correlation analysis, and comparison of significant differences. This helps to dynamically, quickly, and intuitively conduct multi-dimensional data analysis and risk assessment of food production and operation entities, strengthen risk characterization, and assist regulatory decision-making. It provides tools to promote and strengthen local food production and operation risk classification and management, optimize regulatory resource allocation, effectively free up local regulatory manpower, implement scientific and effective supervision, and improve regulatory efficiency and food safety assurance capabilities.

[0039] The above-described contents can be implemented individually or in various combinations, and these variations are all within the protection scope of this invention.

[0040] It should be noted that in the description of this application, the terms "upper end," "lower end," and "bottom end," indicating orientation or positional relationship, are based on the orientation or positional relationship shown in the accompanying drawings, or the orientation or positional relationship commonly used when the product of this application is in use. They are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation on this application. Moreover, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements, but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise limited, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0041] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A visualization system for risk classification data of food production and operation entities, characterized in that: The system includes a data receiving module (101), a regional overall status module (102), a main risk information module (103), a risk identification module (104), and a time trend comparison module (105). The data receiving module (101) is used to receive operating data from multiple producers and operators in various business formats within the region. The regional overall status module (102) is used to obtain information reflecting the proportion of producers and operators with different risk levels in various business formats within the region and the changes in producers and operators with different risk levels over the years based on the operating data. The main risk information module (103) is used to call the proportion information to obtain the first risk information for the target producer and operator. The risk identification module (104) is used to obtain the main risks of the target producer and operator based on the first risk information. The time trend comparison module (105) is used to call the change information to obtain the comparison information of the target producer and operator for two different years.

2. The visualization system for risk classification data of food production and operation entities as described in claim 1, characterized in that: The overall regional status module (102), the main risk information module (103), the risk identification module (104), and the time trend comparison module (105) all include static graphics and dynamic interactive graphics. The static graphics include specific information units used to provide specific information; the dynamic interactive graphics include additional information units used to display additional information when the cursor moves to a specific position. The dynamic interactive graphics can be scaled for the entire image area or a selected image area.

3. The visualization system for risk classification data of food production and operation entities as described in claim 2, characterized in that: The overall regional status module (102) also includes a spatial distribution unit to reflect the spatial distribution of producers and operators within the region, a risk display unit to display the static and dynamic risks of each producer and operator within the region, and a change display unit to display the producers and operators with the greatest changes in risk scores and their changes in each inspection over time.

4. A visualization system for risk classification data of food production and operation entities as described in claim 2 or 3, characterized in that: The risk information includes primary risk factors and major secondary risk factors. The main risk information module (103) also includes a score change unit for recording the score changes of the selected producer and operator in each inspection.

5. A visualization system for risk grading data of food production and operation entities as described in claim 2 or 3, characterized in that: The risk identification module (104) further includes a risk classification unit that divides serious items, key items and non-key items according to the first risk information, and a risk acquisition unit that obtains the main risks according to serious items, key items and non-key items.

6. The visualization system for risk classification data of food production and operation entities as described in claim 5, characterized in that: The risk classification unit is used to compile the mean score and quartile of each risk item among producers and operators in the region, and classify them into serious items, key items and non-key items based on the mean score and quartile.

7. The visualization system for risk classification data of food production and operation entities as described in claim 6, characterized in that: The risk classification unit uses interactive box plots to organize the mean and quartile scores of each risk item among producers and operators in the region.

8. The visualization system for risk classification data of food production and operation entities as described in claim 6, characterized in that: The risk identification module (104) also includes a scoring display unit for displaying the scoring status of each producer and operator on each risk item.

9. A visualization system for risk grading data of food production and operation entities as described in claim 2 or 3, characterized in that: The time trend comparison module (105) also includes a screening unit for filtering risk items where the score difference of a specified business type exceeds a preset value between two specified years, and a comparison unit for comparing the score data distribution of a specified risk item between two years and the score changes of each producer and operator.

10. The visualization system for risk classification data of food production and operation entities as described in claim 9, characterized in that: The comparison unit includes an interactive density plot and a Cleveland dot plot, which compare the distribution of score data for a specified risk item over two years and the score changes for each producer and operator, respectively.

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