Data interaction method and system based on digital government management platform

Abstract

The invention relates to a data interaction method and system based on a digital government management platform, and belongs to the technical field of data processing. Comprising the following steps: designing a data storage model for all data acquired by a digital government management platform; extracting interaction behaviors of a user in the digital government management platform to obtain interaction information, and establishing an interaction entity library; compiling an automatic script or program for data interaction by mining a trigger condition and an intention action of each piece of interaction information in the interaction entity library; and creating a folder component according to a business demand selection component, and displaying a data automatic interaction result through a large visual screen. According to the method, data models are designed for data from different sources for storage, the convenience of data interaction is improved, meanwhile, an automatic data interaction mode is established, the efficiency, accuracy and real-time performance of data interaction are improved, finally, the flexibility of data visualization is improved through configuration of a visualization component, and the data interaction efficiency is improved. And different requirements of users are met.

Description

Technical Field

[0001] The present invention belongs to the field of data processing technology, and specifically relates to a data interaction method and system based on a digital government management platform. Background Art

[0002] Digital government management platforms aggregate data from diverse government departments, providing data sharing and service integration to support various public services, social management, and decision-making analysis. However, with the rapid increase in data volume, the diversification of data sources, and the demand for real-time and accurate data, effectively designing and implementing data interaction mechanisms has become a key technical challenge in the construction of digital government management platforms.

[0003] Currently, most digital government management platforms have functions such as data storage, data query, and business process management. However, there are still some problems in data interaction: data from different government departments are usually stored in isolation, and cross-departmental and cross-system data access and data sharing are difficult; many government services require real-time or near real-time data support, which requires the data interaction process to be efficient and fast, with high real-time requirements; most data interaction processes still require manual intervention, and lack intelligent management of data interaction. Summary of the Invention

[0004] In order to solve the above-mentioned problems existing in the prior art, the present invention provides a data interaction method and system based on a digital government management platform. By designing a data model for storing data from different sources, the convenience of data interaction is improved. At the same time, by establishing an automated data interaction mode, the efficiency, accuracy and real-time performance of data interaction are improved. Finally, through the configuration of visualization components, the flexibility of data visualization is improved to meet the different needs of users.

[0005] The purpose of the present invention can be achieved through the following technical solutions:

[0006] A first aspect of the present disclosure provides a data interaction method based on a digital government management platform, comprising the following steps:

[0007] S1. Data model design: Design a data storage model for all data obtained by the digital government management platform, and manage the data by adding indexes;

[0008] S2. Interaction Information Extraction: Extracting interaction information from users’ interaction behaviors in the digital government management platform and establishing an interaction entity database.

[0009] S3. Data interaction automation: By mining the trigger conditions and intended actions of each interactive message in the interactive entity library, automated scripts or programs are written for data interaction.

[0010] S4. Visualization of interaction results: Select components and create folder components according to business needs, and display the results of data automation interaction through a large visualization screen.

[0011] Furthermore, the data model design includes the following steps:

[0012] S11. Organize all data into several data records, each of which includes a label, a data source, and basic content. The label is used to identify the data type, the data source is used to record the source information of the data, and the basic content includes a timestamp, data content, and metadata.

[0013] S12. Save each data record as a document and create an index for each document, including a timestamp index, a tag index, and a data source index;

[0014] S13. Set up data record access control, authorize access rights, encrypt sensitive data, and perform compliance checks on data storage.

[0015] Furthermore, the interactive information extraction includes the following steps:

[0016] S21. Define interactive information: Based on the interactive characteristics of the digital government management platform, define interactive elements, interactive actions, and response elements;

[0017] S22. Traversing Visual Elements: Use automated tools to traverse the platform interface, record all interactive elements, and capture the user's interaction elements, interactive actions, and response elements with the platform in real time;

[0018] S23. Record interaction information: store the captured interaction information in a database using a structured data storage format;

[0019] S24. Build an interactive entity library: After matching each extracted interactive information with the basic information, aggregate and integrate them to form a structured interactive entity library.

[0020] Furthermore, the basic information includes the timestamp of the interactive information generation, the department to which the response element belongs, the project type, and the intended action.

[0021] Furthermore, the data interaction automation includes the following steps:

[0022] S31. Calculate the correlation between the attributes of the updated data and the intended action based on the data update log of the digital government management platform, and set a threshold to select attribute data that meets the correlation calculation requirements.

[0023] S32. Add the filtered attribute data to the interactive entity library according to the timestamp of each interactive information, and mine the triggering condition of each interactive information in the interactive entity library;

[0024] S33. Group and merge all interaction information based on the intended action. Use an association rule mining algorithm to mine frequent item sets for each type of intended action in each group. Generate association rules from the frequent item sets and calculate the support and confidence of the rules.

[0025] S34. Filter association rules based on support and confidence thresholds, use the premise of the association rules as trigger conditions, and the conclusion as the intended action, and write an automation script or program based on the interaction information corresponding to the intended action;

[0026] S35. Monitor the data status of the digital government management platform. When the trigger condition is met, call the automated script or program to perform automated data interaction according to the triggered intention action, and record the automated data interaction ID.

[0027] Furthermore, the interaction result visualization includes the following steps:

[0028] S41. Enter the large-screen editing page, select components in visualization mode according to business needs, and adjust the position and size of the components as needed;

[0029] S42. Click the selected component to enter the property setting interface, configure component parameters, and create a folder component corresponding to the visualization mode, where the component parameters include the automated data interaction ID;

[0030] S43. The visualization screen matches the folder component according to the displayed visualization mode, and the platform performs data interaction and displays data according to the automated data interaction ID in the folder component;

[0031] S44. Users create different visualization modes by combining folder components, and visualization screens achieve cross-screen interaction by sending their respective folder components to each other;

[0032] S45. The visualization screen obtains a new folder component by splicing the received folder component IDs, traverses the automated data interaction IDs in the folder component, and reintegrates the folder component.

[0033] Furthermore, the components include column charts, bar charts, line charts, pie charts, scatter plots, text, flippers, time selectors, audio and video, tabs, search boxes, and maps.

[0034] A second aspect of the present disclosure provides a data interaction system based on a digital government management platform, which applies the data interaction method based on a digital government management platform as described above, including a data model design module, an interaction information extraction module, a data interaction automation module, an interaction result visualization module, a data management and security module, and a system monitoring and logging module;

[0035] The data model design module is used to design and manage the storage model of all data obtained by the digital government management platform and provide data query and access;

[0036] The data model design module includes the following steps when implementing its functions:

[0037] Standardize the design of each piece of data, including labels, data sources, timestamps, data content, and metadata, and create indexes for data records; set access controls for data records and encrypt sensitive data; and conduct compliance reviews of data storage.

[0038] The interactive information extraction module is used to extract the user's interactive behavior in the digital government management platform and build a structured interactive entity library;

[0039] The interactive information extraction module includes the following steps when implementing its function:

[0040] Define interactive elements, interactive actions, and response elements; use automated tools to traverse the platform interface to capture all user-interactive elements and corresponding interactive actions; store the captured interactive information in a structured manner and match it with other basic information; summarize and integrate the extracted interactive information and basic information to form a structured interactive entity library.

[0041] As a preferred technical solution of the present invention, the data interaction automation module is used to mine data interaction trigger conditions based on the information in the interactive entity library and execute data interaction through an automated script or program;

[0042] The data interaction automation module includes the following steps when implementing its functions:

[0043] Based on data update logs, the correlation between data attributes and interaction intent actions is analyzed to select useful data as trigger conditions. Association rule mining algorithms are used to analyze frequent item sets in interaction information and generate association rules between trigger conditions and intended actions. Based on the mined association rules, automated scripts or programs are written to automate data interaction. Platform data is monitored in real time, and when the data meets the trigger conditions, the script is automatically called to execute the data interaction and the ID of each automated interaction is recorded.

[0044] The interaction result visualization module is used to select visualization components to display the results of data interaction according to business needs;

[0045] The interactive result visualization module includes the following steps when implementing its functions:

[0046] Select appropriate components based on business needs, configure component parameters, and associate automated data interaction IDs; organize and adjust visualization components to form a large visualization screen to provide user interactive display; support interaction and data sharing between different large visualization screens through the combination and splicing of components; match interaction information from the interaction entity library based on the automated interaction ID to execute automated scripts or programs and update the large screen display content.

[0047] As a preferred technical solution of the present invention, the data management and security module is used to manage, store and protect all data in the digital government management platform;

[0048] The data management and security module includes the following steps when implementing its functions:

[0049] Protect sensitive data through encryption technology and set access rights for users with different roles; regularly check the compliance of data storage and management;

[0050] The system monitoring and logging module is used to monitor the platform's operating status and data interaction in real time and record relevant log information;

[0051] The system monitoring and logging module includes the following steps when implementing its functions:

[0052] Monitor the platform operation in real time and record the log information of each data interaction; detect abnormal situations in system operation and issue alarm notifications in a timely manner.

[0053] The beneficial effects of the present invention are:

[0054] The present invention first establishes a data storage model for all data obtained by the digital government management platform, classifies and tags the data for storage, and then captures the user's data interaction behavior in the platform by defining interaction information, thereby establishing an interaction entity library for each interaction information; then, by mining the interaction patterns of all interaction information in the interaction entity library, the trigger conditions and intended actions of the data interaction behavior are obtained through the association rule mining algorithm, and at the same time, the automation program of data interaction is written according to the interaction information, thereby establishing a complete "trigger condition-interaction information-automation program-intent action" mode of automated data interaction ID; finally, the automated data interaction ID is visualized by the component parameters in the visualization mode. In this process, the user's data interaction behavior is learned and then converted into automated operation, replacing manual operation and reducing human errors, improving efficiency, accuracy and reliability in the data interaction process, enhancing overall productivity, and at the same time, by establishing an automation mode with flexibility and scalability to adapt to different data interaction needs and support real-time data synchronization.

[0055] During the data interaction visualization process, the present invention establishes a folder component of the visualization large screen, and customizes different visualization modes by combining the folder components, providing a large number of choices for the user's visualization needs, and at the same time provides a convenient way for cross-screen data interaction. Cross-screen data interaction can be achieved by simply adding or deleting automated data interaction IDs, which reduces the difficulty of setting up the visualization large screen and improves the efficiency of platform management and decision-making. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] To facilitate understanding by those skilled in the art, the present invention is further described below with reference to the accompanying drawings.

[0057] Figure 1 A flowchart of a data interaction method based on a digital government management platform provided by an embodiment of the present invention;

[0058] Figure 2 A schematic diagram of the process flow of automated data interaction provided by an embodiment of the present invention;

[0059] Figure 3 A structural diagram of a data interaction system based on a digital government management platform provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0060] In order to further illustrate the technical means and effects adopted by the present invention to achieve the predetermined purpose of the invention, the specific implementation methods, structures, features and effects of the present invention are described in detail below in conjunction with the accompanying drawings and preferred embodiments.

[0061] This embodiment provides a data interaction method based on a digital government management platform, such as Figure 1 As shown, the following steps are included:

[0062] S1. Data model design: Design a data storage model for all data obtained by the digital government management platform and manage the data by adding indexes, including the following steps:

[0063] S11. Organize all data into several data records. Each data record includes a label, a data source, and basic content. The label is used to identify the data type, the data source is used to record the data source information, and the basic content includes a timestamp, data content, and metadata.

[0064] It is understandable that tags can help with quick classification, such as financial data, public security data, people's livelihood service data, etc.; data sources can record the source of data, such as departments, services, and projects; metadata is additional detailed information, including department ID, data version, user information, etc.

[0065] S12. Save each data record as a document and create an index for each document, including a timestamp index, a tag index, and a data source index.

[0066] S13. Set up data record access control, authorize access rights, encrypt sensitive data, and perform compliance checks on data storage.

[0067] It should be noted that the design of the data storage model lays the foundation for subsequent data interaction. The designed data storage model can efficiently perform data queries. At the same time, by designing an automated calling strategy, the accuracy and reliability of data interaction can be achieved.

[0068] S2. Interaction Information Extraction: Extracting interaction information from users’ interaction behaviors in the digital government management platform and establishing an interaction entity database, including the following steps:

[0069] S21. Define interactive information: Based on the interactive characteristics of the digital government management platform, define interactive elements (such as buttons, input boxes, chart elements, etc.), interactive actions (such as clicking, dragging, sliding, etc.), and response elements (such as page updates, data changes, etc.);

[0070] S22. Traversing visual elements: Use automated tools (such as Selenium and Puppeteer) to traverse the platform interface, record all interactive elements, and capture the user's interaction elements, interaction actions, and response elements with the platform in real time;

[0071] S23. Record interaction information: store the captured interaction information (such as interaction elements, interaction actions, and response elements) in a database using a structured data storage format;

[0072] S24. Build an interactive entity library: After matching each extracted interactive information with the basic information, aggregate and integrate them to form a structured interactive entity library.

[0073] Basic information includes the timestamp of the interaction, the department to which the response element belongs, the project type, and the intended action. It should be noted that the intended action refers to the final form of data interaction, such as visualization, data migration, and query.

[0074] It is understandable that extracting interaction information can deeply explore the data interaction forms of users or platforms, discover interaction patterns, dynamically update according to user operations, and provide trigger conditions and intention action mining for automated data interaction.

[0075] S3. Data interaction automation: By mining the trigger conditions and intention actions of each interactive information in the interactive entity library, write automated scripts or programs to perform data interaction, such as Figure 2 As shown, the following steps are included:

[0076] S31. Calculate the correlation between the attributes of the updated data and the intended action based on the data update log of the digital government management platform, and set a threshold to select attribute data that meets the correlation calculation requirements.

[0077] It is understandable that by using the correlation coefficient method to measure the correlation between the intended action and the attribute field update, a part of the data can be screened out for use as the mining content of the intention action trigger condition, enriching the types of trigger conditions and making the trigger conditions more accurate.

[0078] S32. Add the filtered attribute data to the interactive entity library according to the timestamp of each interactive information, and mine the triggering condition of each interactive information in the interactive entity library;

[0079] It should be noted that the filtered attribute data reflects the situation where a certain type of data in the platform is updated, resulting in data interaction. Therefore, the update time of the attribute data should be before the timestamp of the interaction information, and this is used as the basis for matching with the interaction information.

[0080] S33. All interaction information is grouped and merged based on the intended action. In each group, an association rule mining algorithm (Apriori, FP-Growth, etc.) is used to mine frequent itemsets for each type of intended action. Association rules are generated from the frequent itemsets, and the support and confidence of the rules are calculated.

[0081] S34. Filter association rules based on support and confidence thresholds, use the premise of the association rules as trigger conditions, and the conclusion as the intended action, and write an automation script or program based on the interaction information corresponding to the intended action;

[0082] S35. Monitor the data status of the digital government management platform. When the trigger condition is met, call the automated script or program to perform automated data interaction according to the triggered intention action, and record the automated data interaction ID.

[0083] It should be noted that by implementing automated data interaction, an automated data interaction ID based on the "trigger condition - interaction information - automated program - intended action" model was ultimately established. Automated scripts were used to simulate user operations within web applications, automating the data interaction process and reducing manual intervention. This enabled automated data retrieval, conversion, transmission, and call processing, reducing errors and risks in data interaction, improving data consistency and accuracy, and saving human resources and time. Furthermore, by mining association rules or proactively editing user-defined intended action scripts, automated data interaction can be expanded to accommodate data interaction needs of varying scale and complexity.

[0084] By learning the automated data interaction process using the above method, the automated script can be edited according to actual needs, reducing the waste of human resources and improving the efficiency of system data interaction and the practicality of automation.

[0085] S4. Visualization of interaction results: Select components based on business needs and create folder components. Display the results of data automation interaction on a large visualization screen. This includes the following steps:

[0086] Among them, components include column charts, bar charts, line charts, pie charts, scatter plots, text, flippers, time selectors, audio and video, tabs, search boxes, maps, etc.

[0087] S41. Enter the large-screen editing page, select components in visualization mode according to business needs, and adjust the position and size of the components as needed;

[0088] S42. Click the selected component to enter the property setting interface, configure component parameters, and create a folder component corresponding to the visualization mode, where the component parameters include the automated data interaction ID;

[0089] S43. The visualization screen matches the folder component according to the displayed visualization mode, and the platform performs data interaction and displays data according to the automated data interaction ID in the folder component.

[0090] S44. Users create different visualization modes by combining folder components, and visualization screens achieve cross-screen interaction by sending their respective folder components to each other;

[0091] S45. The visualization screen obtains a new folder component by splicing the received folder component IDs, traverses the automated data interaction IDs in the folder component, and reintegrates the folder component.

[0092] It should be noted that by creating folder components that meet different display needs, users can flexibly adjust the content displayed on the visual large screen, and by sharing the respective folder components between visual large screens, cross-screen data interaction can be achieved, thereby improving the efficiency of platform management and decision-making.

[0093] This embodiment also provides a data interaction system based on the digital government management platform, such as Figure 3 As shown, it includes data model design module, interaction information extraction module, data interaction automation module, interaction result visualization module, data management and security module, and system monitoring and log module.

[0094] The data model design module is used to design and manage the storage model of all data obtained by the digital government management platform, ensuring that the data storage structure meets the requirements of the platform and can efficiently query and access data.

[0095] The data model design module includes the following steps when implementing its functions:

[0096] Data record design: Standardize the design of each piece of data, including labels, data sources, timestamps, data content, and metadata, to ensure a unified data format;

[0097] Index management: Create indexes for data records (such as timestamps, tags, data sources, etc.) to improve query efficiency;

[0098] Permission and security management: Set access control for data records to ensure that only authorized users can access the corresponding data. At the same time, encrypt sensitive data to ensure data security.

[0099] Compliance Check: Conduct compliance review of data storage to ensure compliance with relevant regulatory requirements.

[0100] It is understandable that the data model design module is the foundation of the system, providing a framework for data storage, query, management and security control, and providing support for subsequent automated interactions.

[0101] The interactive information extraction module is used to extract the user's interactive behavior in the digital government management platform and build a structured interactive entity library to facilitate subsequent data interaction automation.

[0102] The interactive information extraction module includes the following steps when implementing its function:

[0103] Interaction information definition: clearly define interactive elements (buttons, input boxes, etc.), interactive actions (click, drag, etc.), and response elements (page updates, data changes, etc.);

[0104] Visual element traversal: Use automated tools (such as Selenium, Puppeteer, etc.) to traverse the platform interface and capture all user-interactive elements and corresponding interactive actions;

[0105] Interaction information storage: The captured interaction information is stored in a structured manner and ensured to match with other basic information (such as timestamp, department to which the response element belongs, project type, etc.);

[0106] Interaction entity library construction: The extracted interaction information and basic information are aggregated and integrated to form a structured interaction entity library.

[0107] It is understandable that the interaction information extraction module mainly monitors the interaction between users and the platform, automatically extracts and stores interaction information, and provides input data for subsequent data interaction automation.

[0108] The data interaction automation module is used to mine data interaction trigger conditions based on the information in the interaction entity library, and execute data interaction through automated scripts or programs to ensure the automation and accuracy of data flow.

[0109] The data interaction automation module includes the following steps when implementing its functions:

[0110] Calculate the correlation between attributes and intended actions: Based on the data update log, analyze the correlation between data attributes and interaction intended actions, and filter out useful data as trigger conditions;

[0111] Trigger condition mining: Use association rule mining algorithms (such as Apriori and FP-Growth) to analyze frequent item sets in interactive information and generate association rules between trigger conditions and intended actions;

[0112] Automated script writing: Based on the mined association rules, write automated scripts or programs to achieve automated execution of data interaction;

[0113] Monitoring and triggering: Real-time monitoring of platform data. When the data reaches the trigger condition, the script is automatically called to perform data interaction and the ID of each automated interaction is recorded.

[0114] It is understandable that the data interaction automation module triggers data operations according to interaction rules through automated means, simulates human operations for data interaction, and improves interaction efficiency and accuracy.

[0115] The interaction result visualization module is used to select appropriate visualization components to display the results of data interaction according to business needs, ensuring that the data display on the platform is intuitive and easy to understand.

[0116] The interactive result visualization module includes the following steps when implementing its functions:

[0117] Visualization component selection and configuration: Select appropriate components (such as bar charts, pie charts, maps, etc.) based on business needs, configure component parameters, and associate automated data interaction IDs;

[0118] Component layout and adjustment: organize and adjust visual components to form a large visual screen to provide user interactive display;

[0119] Cross-screen interaction support: Through the combination and splicing of components, it supports interaction and data sharing between different visualization screens;

[0120] Data display: Based on the automated interaction ID, the interaction information is matched from the interaction entity library and the automated script or program is executed to update the large-screen display content to ensure the real-time and accuracy of the displayed information.

[0121] It is understandable that the interaction result visualization module presents the automated interaction results in a componentized form, providing intuitive business insights and decision support, and enhancing the platform user experience.

[0122] The data management and security module is used to manage, store and protect all data in the digital government management platform to ensure the integrity, confidentiality and accessibility of the data.

[0123] The data management and security module includes the following steps when implementing its functions:

[0124] Data encryption and privacy protection: Protect sensitive data through encryption technology to ensure the security of data during transmission and storage;

[0125] Access rights management: Set access rights for users with different roles to ensure that data is only accessible to authorized users;

[0126] Compliance review: Regularly check the compliance of data storage and management to ensure compliance with laws and regulations.

[0127] It is understandable that the data management and security module ensures the security, compliance and operability of all data within the platform, providing guarantees for the normal operation of the platform.

[0128] The system monitoring and logging module is used to monitor the platform's operating status and data interaction in real time, and record relevant log information to ensure the stability and traceability of the system.

[0129] The system monitoring and logging module includes the following steps when implementing its functions:

[0130] Platform status monitoring: Real-time monitoring of platform operation to ensure smooth operation and data interaction;

[0131] Log recording and analysis: Record the log information of each data interaction (such as interaction ID, trigger conditions, execution results, etc.) to facilitate later analysis and troubleshooting;

[0132] Abnormal detection and alarm: Detect abnormal conditions in system operation and issue alarm notifications in a timely manner to facilitate problem resolution.

[0133] It is understandable that the system monitoring and logging module ensures the high availability of the platform operation and enhances the stability and reliability of the system through logging and anomaly detection.

[0134] The present invention first establishes a data storage model for all data obtained by the digital government management platform, classifies and tags the data for storage, and then captures the user's data interaction behavior in the platform by defining interaction information, thereby establishing an interaction entity library for each interaction information; then, by mining the interaction patterns of all interaction information in the interaction entity library, the trigger conditions and intended actions of the data interaction behavior are obtained through the association rule mining algorithm, and at the same time, the automation program of data interaction is written according to the interaction information, thereby establishing a complete "trigger condition-interaction information-automation program-intent action" mode of automated data interaction ID; finally, the automated data interaction ID is visualized by the component parameters in the visualization mode. In this process, the user's data interaction behavior is learned and then converted into automated operation, replacing manual operation and reducing human errors, improving efficiency, accuracy and reliability in the data interaction process, enhancing overall productivity, and at the same time, by establishing an automation mode with flexibility and scalability to adapt to different data interaction needs and support real-time data synchronization.

[0135] During the data interaction visualization process, the present invention establishes a folder component of the visualization large screen, and customizes different visualization modes by combining the folder components, providing a large number of choices for the user's visualization needs, and at the same time provides a convenient way for cross-screen data interaction. Cross-screen data interaction can be achieved by simply adding or deleting automated data interaction IDs, which reduces the difficulty of setting up the visualization large screen and improves the efficiency of platform management and decision-making.

[0136] The above description is merely a preferred embodiment of the present invention and does not constitute any form of limitation to the present invention. Although the present invention has been disclosed as above in terms of a preferred embodiment, it is not intended to limit the present invention. Any person skilled in the art can, without departing from the scope of the technical solution of the present invention, make some changes or modifications to equivalent embodiments using the technical contents disclosed above. However, any brief modifications, equivalent changes and modifications made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solution of the present invention are still within the scope of the technical solution of the present invention.

Claims

1. A data interaction method based on a digital government management platform, characterized by: The following steps are involved: Data model design: Design a data storage model for all data obtained by the digital government management platform, and manage the data by adding indexes; Interaction information extraction: Extracting interaction information from users’ interaction behaviors in the digital government management platform and establishing an interaction entity database; Data interaction automation: By mining the trigger conditions and intended actions of each interactive information in the interactive entity library, automated scripts or programs are written for data interaction; Visualization of interaction results: Select components and create folder components based on business needs, and display the results of data automation interaction on a large visualization screen.

2. A data interaction method based on a digital government management platform according to claim 1, characterized in that: The data model design includes the following steps: All data are organized into several data records. Each data record includes a label, a data source, and basic content. The label is used to identify the data type, the data source is used to record the source information of the data, and the basic content includes a timestamp, data content, and metadata. Save each data record as a document and create an index for each document, including a timestamp index, a tag index, and a data source index; Set up data record access control, authorize access rights, encrypt sensitive data, and perform compliance checks on data storage.

3. A data interaction method based on a digital government management platform according to claim 1, characterized in that: The interactive information extraction comprises the following steps: Define interactive information: Based on the interactive characteristics of the digital government management platform, define interactive elements, interactive actions, and response elements; Traversing visual elements: Use automated tools to traverse the platform interface, record all interactive elements, and capture the user's interactive elements, interactive actions, and response elements between the platform and the platform in real time; Record interaction information: Store the captured interaction information in the database using a structured data storage format; Build an interactive entity library: After matching each extracted interactive information with the basic information, summarize and integrate it to form a structured interactive entity library.

4. A data interaction method based on a digital government management platform according to claim 3, characterized in that: The basic information includes the timestamp of the interaction information, the department to which the response element belongs, the project type, and the intended action.

5. The data interaction method based on the digital government management platform according to claim 1 is characterized by: The data interaction automation includes the following steps: Based on the data update log of the digital government management platform, the correlation between the attributes of the updated data and the intended action is calculated, and a threshold is set to select attribute data that meets the correlation calculation requirements; The filtered attribute data is added to the interactive entity library according to the timestamp of each interactive information, and the triggering conditions of each interactive information are mined in the interactive entity library; All interaction information is grouped and merged based on intent actions. In each group, an association rule mining algorithm is used to mine frequent item sets for each type of intent action. Association rules are generated from the frequent item sets, and the support and confidence of the rules are calculated. Filter association rules based on support and confidence thresholds, use the association rule premises as trigger conditions, and the conclusions as intended actions. Write automated scripts or programs based on the interaction information corresponding to the intended actions. Monitor the data status of the digital government management platform. When the trigger conditions are met, call the automated script or program to perform automated data interaction according to the triggered intention action, and record the automated data interaction ID.

6. A data interaction method based on a digital government management platform according to claim 1, characterized in that: The interactive result visualization includes the following steps: Enter the large-screen editing page, select components in visualization mode according to business needs, and adjust the position and size of components as needed; Click the selected component to enter the property setting interface, configure the component parameters, and create a folder component corresponding to the visualization mode. The component parameters include the automated data interaction ID. The visualization screen matches folder components based on the displayed visualization mode, and the platform performs data interaction and displays data based on the automated data interaction ID in the folder component; Users create different visualization modes by combining folder components, and cross-screen interaction is achieved between visualization screens by sending their respective folder components to each other; The visualization screen obtains a new folder component by splicing the received folder component IDs, traverses the automated data interaction IDs in the folder component, and reintegrates the folder component.

7. A data interaction method based on a digital government management platform according to claim 6, characterized in that: The components include column charts, bar charts, line charts, pie charts, scatter plots, text, flippers, time selectors, audio and video, tabs, search boxes, and maps.

8. A data interaction system based on a digital government management platform, applying the data interaction method based on a digital government management platform according to any one of claims 1 to 7, characterized in that: It includes data model design module, interactive information extraction module, data interaction automation module, interactive result visualization module, data management and security module, and system monitoring and log module; The data model design module is used to design and manage the storage model of all data obtained by the digital government management platform and provide data query and access; The data model design module includes the following steps when implementing its functions: Standardize the design of each piece of data, including labels, data sources, timestamps, data content, and metadata, and create indexes for data records; set access controls for data records and encrypt sensitive data; and conduct compliance reviews of data storage. The interactive information extraction module is used to extract the user's interactive behavior in the digital government management platform and build a structured interactive entity library; The interactive information extraction module includes the following steps when implementing its function: Define interactive elements, interactive actions, and response elements; use automated tools to traverse the platform interface and capture all user-interactive elements and corresponding interactive actions; The captured interaction information is stored in a structured manner and matched with other basic information; the extracted interaction information and basic information are aggregated and integrated to form a structured interaction entity library.

9. A data interaction system based on a digital government management platform according to claim 8, characterized in that: The data interaction automation module is used to mine data interaction trigger conditions based on the information in the interaction entity library and execute data interaction through automated scripts or programs; The data interaction automation module includes the following steps when implementing its functions: Based on the data update log, the correlation between data attributes and interaction intention actions is analyzed to select useful data as trigger conditions. Association rule mining algorithms are used to analyze frequent item sets in interaction information to generate association rules between trigger conditions and intended actions. Based on the mined association rules, automated scripts or programs are written to achieve automated execution of data interaction. Monitor platform data in real time. When the data reaches the trigger condition, automatically call the script to execute data interaction and record the ID of each automated interaction. The interaction result visualization module is used to select visualization components to display the results of data interaction according to business needs; The interactive result visualization module includes the following steps when implementing its functions: Select appropriate components based on business needs, configure component parameters, and associate automated data interaction IDs; organize and adjust visualization components to form a large visualization screen to provide user interactive display; support interaction and data sharing between different large visualization screens through the combination and splicing of components; match interaction information from the interaction entity library based on the automated interaction ID to execute automated scripts or programs and update the large screen display content.

10. A data interaction system based on a digital government management platform according to claim 8, characterized in that: The data management and security module is used to manage, store and protect all data in the digital government management platform; The data management and security module includes the following steps when implementing its functions: Protect sensitive data through encryption technology and set access rights for users with different roles; regularly check the compliance of data storage and management; The system monitoring and logging module is used to monitor the platform's operating status and data interaction in real time and record relevant log information; The system monitoring and logging module includes the following steps when implementing its functions: Monitor the platform operation in real time and record the log information of each data interaction; detect abnormal situations in system operation and issue alarm notifications in a timely manner.

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