Data opening and sharing platform based on multi-modal data interaction

Abstract

The invention provides a data opening and sharing platform based on multi-modal data interaction, belongs to the field of big data processing and artificial intelligence, and realizes intelligent management, query, analysis and sharing of data by integrating natural language processing and multi-modal data processing technologies. A user is supported to carry out data interaction in various modes such as voice, text and graphical interfaces, user requirements are analyzed by utilizing a language large model, and the user experience is improved through an automatic API document generation system, a dynamic data service optimization platform and an intelligent data display and report generation system and through automatic quality auditing and problem analysis. And the accuracy and consistency of the data are improved. And a data query and analysis function driven by a natural language enables non-technical background users to easily perform data analysis. According to the multi-source heterogeneous data integration and processing technology, the problems of data islands and inconsistent data formats are solved, and seamless integration of data resources is achieved.

Description

Technical Field

[0001] The present invention relates to the fields of big data processing and artificial intelligence, and in particular to a data open sharing platform based on multimodal data interaction, which is used to realize intelligent management, analysis and sharing of data, provide functions such as natural language processing, multimodal interaction, automatic data processing and intelligent recommendation, and significantly improve data utilization efficiency and user experience. Background Art

[0002] With the rapid development and widespread application of big data technology, data has become an important asset for enterprises and organizations. The efficient management, analysis and sharing of data are of great significance for improving business decisions, optimizing operational efficiency and promoting innovation. However, the current data management and sharing platform has significant deficiencies in many aspects, including data island problems, difficulty in matching data demand and supply, insufficient personalized services, complex API document generation and maintenance, insufficient data service performance optimization, single data display and analysis methods, and imperfect data security and privacy protection. The data between different departments and systems cannot be effectively connected, resulting in serious data island phenomenon, which limits the comprehensive utilization and value mining of data. There are language inconsistencies and understanding deviations in the process of data demand description and data resource matching, which makes it difficult to accurately express and meet data needs. The existing system lacks an intelligent data demand parsing and matching mechanism, and the process of users obtaining the required data is complicated and time-consuming. The current data sharing platform lacks in-depth analysis of user behavior and needs, and it is difficult to provide personalized data recommendations and services. Users need to spend a lot of time and energy to find the required data in huge data resources, which reduces work efficiency and user experience. During the release and maintenance of data services, the writing and updating of API documents is cumbersome and error-prone. Manually writing API documents is not only time-consuming, but also difficult to maintain the integrity and consistency of the documents, affecting the efficiency of development and operation and maintenance. With the increase in data volume and access frequency, the performance problems of data services have become increasingly prominent, such as long response time and high error rate. The existing system lacks intelligent performance monitoring and optimization mechanisms, making it difficult to timely discover and solve performance bottlenecks. Traditional data display and analysis methods require users to have a high technical background, which is not friendly to business personnel and ordinary users. Data analysis results are difficult to display intuitively and dynamically adjust, affecting the effectiveness and efficiency of data analysis. Data is prone to leakage and abuse during transmission and use. Data security and privacy protection issues need to be addressed urgently. The existing system's mechanisms in data desensitization, encryption, and access control are not perfect enough to fully guarantee data security. Summary of the invention

[0003] In order to solve the above technical problems, the present invention provides a data open sharing platform based on multimodal data interaction. It uses natural language processing, multimodal interaction, automated data processing, intelligent recommendation and other technologies to provide efficient, intelligent and secure data management and sharing solutions.

[0004] The architecture of the present invention includes the following main modules and functional components:

[0005] 1. Data collection and integration layer

[0006] Data source management: Manage and configure different types of data sources, including structured data, semi-structured data, and unstructured data.

[0007] Data collection adapter: supports multiple data collection methods (such as FTP, API, database connection, streaming data collection, etc.) to achieve unified data collection and access.

[0008] Data cleaning and conversion: Clean, convert and standardize the collected data to ensure data quality and consistency.

[0009] 2. Data storage and management layer

[0010] Data warehouse: stores structured data and supports efficient query and analysis operations.

[0011] Data Lake: Stores semi-structured and unstructured data and supports large-scale data storage and processing.

[0012] Metadata management: manage data metadata, including data sources, data tables, field information, data lineage, and data relationships.

[0013] Data asset management: Manage data resources as assets to achieve full life cycle management and value mining of data.

[0014] 3. Data processing and analysis layer

[0015] Batch processing and stream processing engine: supports batch processing and real-time stream processing of large-scale data, improving data processing efficiency and timeliness.

[0016] Data modeling and analysis: Provides data modeling tools, supports a variety of data analysis methods and algorithms, and enables in-depth analysis and insights into data.

[0017] Natural Language Processing (NLP): Uses large language models to parse users’ natural language needs, perform semantic understanding and information extraction, and support natural language query and interaction.

[0018] 4. Data service and sharing layer

[0019] API service management: supports the registration, publishing and management of data services, and provides standardized API interfaces (such as REST API, GraphQL, etc.) for external systems and users to access data.

[0020] Data sharing mechanism: realize secure data sharing, support multiple data access methods (such as API, FTP, message queue, etc.), and ensure efficient flow of data between different systems and users.

[0021] Service monitoring and optimization: Real-time monitoring of data service usage, analysis of call frequency, response time, and error rate, and provision of performance optimization recommendations and automated tuning capabilities.

[0022] 5. User interaction and presentation layer

[0023] Multimodal interactive interface: supports users to query and operate data through natural language, voice, graphical interface and other methods, achieving a seamless multimodal interactive experience.

[0024] Data visualization tools: Provides a variety of data visualization components, such as charts, dashboards, report generators, etc., to support users in intuitively displaying and analyzing data.

[0025] Intelligent recommendation system: Analyze user behavior and needs based on a multimodal large model, generate personalized data recommendation lists and analysis tools, and improve user experience and data utilization efficiency.

[0026] 6. Security and Privacy Protection Layer

[0027] Data desensitization and encryption: Dynamically desensitize and encrypt sensitive data to ensure data security during transmission and use.

[0028] Access control and auditing: Data access control is performed based on user roles and permissions, and all data operation logs are recorded to provide security auditing functions.

[0029] Data security strategy: Develop and implement a comprehensive data security strategy to ensure data security and privacy protection throughout its life cycle.

[0030] 7. System management and operation and maintenance layer

[0031] System monitoring and alarm: Real-time monitoring of the platform's operating status, including hardware resources, software components, and data services, and providing anomaly detection and alarm functions.

[0032] Log management and analysis: Collect and analyze system logs to support troubleshooting and performance optimization.

[0033] Operation and maintenance automation tools: Provide automated operation and maintenance tools to support automated deployment, upgrades, and maintenance of the system, improving operation and maintenance efficiency and reliability.

[0034] The architecture of the present invention forms an efficient, intelligent and secure data open sharing platform by integrating multiple levels such as data collection and integration, data storage and management, data processing and analysis, data service and sharing, user interaction and display, security and privacy protection, system management and operation and maintenance. Through the application of technologies such as natural language processing, multimodal interaction and intelligent recommendation, efficient management, analysis and sharing of data can be achieved, data utilization efficiency and user experience can be improved, and enterprises and organizations can be helped to achieve data-driven business decisions and innovations.

[0035] The present invention integrates advanced natural language processing technology to enable users to query and operate data through natural languages ​​such as voice and text, supports users to drag, filter and visualize data through a graphical interface, and realizes seamless switching of multiple interaction modes; uses a language big model to parse users' natural language needs, extract key entities and attributes, and perform accurate data matching, and dynamically adjusts data demand analysis and matching strategies based on user feedback and behavior to improve matching accuracy and user satisfaction; uses a multimodal big model to analyze users' operation records, access history and interest preferences, builds user portraits, and generates personalized data sets and analysis tool recommendation lists based on user portraits and current needs to improve data usage efficiency; based on predefined templates and A PI metadata automatically generates structured API document content, automatically supplements detailed descriptions and examples based on the specific functions and parameters of the API, and ensures the integrity and ease of use of the document; implements some optimization measures through automated tools to achieve dynamic optimization and self-repair of data services; provides a natural language query interface, users input natural language queries, the system parses and generates SQL or other query languages, returns query results, and displays query results in the form of charts, dashboards, etc., supports user interactive operations such as filtering, sorting, and drilling down; dynamically desensitizes and encrypts sensitive data to ensure the security of data during transmission and use, performs data access control based on user roles and permissions, and records all data operation logs to provide security audit functions. The present invention aims to break data silos, improve the efficiency of data demand matching, provide personalized services, simplify API document generation and maintenance, optimize data service performance, improve data display and analysis methods, and strengthen data security and privacy protection, and comprehensively improve data utilization efficiency and user experience.

[0036] The architecture of the present invention forms an efficient, intelligent and secure data open sharing platform by integrating multiple levels such as data collection and integration, data storage and management, data processing and analysis, data service and sharing, user interaction and display, security and privacy protection, system management and operation and maintenance. Through the application of technologies such as natural language processing, multimodal interaction and intelligent recommendation, efficient management, analysis and sharing of data can be achieved, data utilization efficiency and user experience can be improved, and enterprises and organizations can be helped to achieve data-driven business decisions and innovations.

[0037] The beneficial effects of the present invention are

[0038] The present invention integrates natural language processing, multimodal interaction, automated data processing and intelligent recommendation technologies to achieve the following beneficial effects:

[0039] Breaking down data silos and achieving efficient data integration: The present invention integrates and uniformly manages data resources from different systems and departments to achieve efficient data integration and sharing, breaking down data isolation, enhancing the comprehensive utilization value of data, and promoting data interconnection and interoperability.

[0040] Improve the efficiency of data demand matching: Utilize natural language processing technology and multimodal large models to intelligently analyze users' natural language needs, extract key information, and achieve accurate data resource matching. Users only need to describe their needs in natural language, and the system can quickly match the corresponding data resources, greatly improving data acquisition efficiency and reducing users' learning costs and operational complexity.

[0041] Provide personalized data services to improve user experience: Analyze user behavior and needs, build user profiles, and provide personalized data set recommendations and analysis tools based on user profiles and current needs. Users can quickly obtain the most relevant data and analysis tools, improving data usage efficiency and user experience.

[0042] Simplify API document generation and maintenance, and improve development and operation efficiency: Use the language model to automatically generate and maintain high-quality API documents, ensure the integrity and consistency of the documents, reduce the workload of manual document writing and updating, and improve development and operation efficiency. Developers can focus more on the development and optimization of core business functions.

[0043] Optimize data service performance and ensure efficient operation: Through multi-modal large models, real-time monitoring and analysis of data service usage, provide performance optimization suggestions and achieve automatic tuning. The system can automatically adjust the configuration during peak hours to ensure efficient operation and stability of data services, improving system reliability and user satisfaction.

[0044] Improve data display and analysis methods, and enhance data analysis results: Provide natural language query interface and multimodal interactive interface, support users to query, analyze and visualize data through natural language and graphical interface. Users can obtain data analysis results through simple natural language query or graphical operation, which reduces the technical threshold of data analysis and improves the intuitiveness and flexibility of data analysis.

[0045] Strengthen data security and privacy protection: During data transmission and use, data security is ensured through dynamic desensitization and encryption processing, access control is performed based on user roles and permissions, and all data operation logs are recorded to provide comprehensive data security audit functions. This effectively protects the security and privacy of sensitive data and meets the high standards of enterprises and organizations for data security.

[0046] Realize data asset management and value mining: Establish a unified data resource catalog and asset management mechanism, support the automatic registration and release of data services, and promote the full life cycle management and value mining of data. The system can help enterprises and organizations fully grasp data resources, fully explore data value, and enhance the commercial value and application potential of data. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 It is a schematic diagram of the overall structure of the present invention;

[0048] Figure 2 It is a schematic diagram of the workflow of the present invention. DETAILED DESCRIPTION

[0049] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0050] The present invention discloses a data open sharing platform based on multimodal data interaction, which aims to realize intelligent management, query, analysis and sharing of data by integrating natural language processing and multimodal data processing technology. The platform supports users to interact with data through voice, text, graphical interface and other methods, and uses a large language model to parse user needs, providing high-precision data resource matching and personalized recommendations. Through the automated API document generation system, dynamic data service optimization platform and intelligent data display and report generation system, the platform significantly improves the efficiency and quality of data services. At the same time, the platform realizes dynamic desensitization, encryption and access control of data to ensure the security of the entire life cycle of data. The intelligent data governance and quality management module improves the accuracy and consistency of data through automated quality audits and problem analysis. The natural language-driven data query and analysis function enables users with non-technical backgrounds to easily perform data analysis. Multi-source heterogeneous data integration and processing technology solves the problems of data islands and inconsistent data formats, and realizes the seamless integration of data resources.

[0051] The present invention solves various problems existing in current data management and sharing platforms. Specifically, the invention aims to:

[0052] 1. Eliminate data silos: By integrating and uniformly managing data resources from different systems and departments, efficient data integration and sharing can be achieved, thus breaking the isolated state of data and improving the comprehensive utilization value of data.

[0053] 2. Improve the efficiency of data demand matching: Utilize natural language processing technology and multimodal large models to intelligently analyze users' natural language needs, extract key information, and achieve accurate data resource matching, thereby improving the efficiency of users in obtaining the required data.

[0054] 3. Provide personalized data services: Build user portraits by analyzing user behaviors and needs. Based on user portraits and current needs, provide personalized data set recommendations and analysis tools to improve user experience and data usage efficiency.

[0055] 4. Simplify API document generation and maintenance: Use the language big model to automatically generate and maintain high-quality API documents, ensure the integrity and consistency of the documents, reduce the workload of manual writing and updating documents, and improve development and operation efficiency.

[0056] 5. Optimize data service performance: Use multimodal large models to monitor and analyze data service usage in real time, provide performance optimization suggestions and implement automated tuning to ensure efficient operation and stability of data services.

[0057] 6. Improve data display and analysis methods: Provide natural language query interface and multimodal interactive interface to support users to query, analyze and visualize data through natural language and graphical interface, lower the technical threshold of data analysis, and improve the intuitiveness and flexibility of data analysis.

[0058] 7. Strengthen data security and privacy protection: During data transmission and use, data security is ensured through dynamic desensitization and encryption processing, access control is performed based on user roles and permissions, and all data operation logs are recorded to provide comprehensive data security audit functions.

[0059] 8. Realize data asset management and value mining: Establish a unified data resource catalog and asset management mechanism, support the automated registration and release of data services, promote the full life cycle management and value mining of data, and enhance the commercial value and application potential of data.

[0060] The present invention provides an efficient, intelligent and secure data open sharing platform by comprehensively applying technologies such as natural language processing, multimodal large models, intelligent recommendations and automated data processing, aiming to comprehensively improve data utilization efficiency and user experience, and help enterprises and organizations achieve data-driven business decisions and innovations.

[0061] The implementation process of the data open sharing platform based on multimodal data interaction of the present invention is as follows:

[0062] 1. Data collection and integration

[0063] i. Data source configuration: First, configure the platform's various data sources, including structured data sources (such as relational databases), semi-structured data sources (such as JSON, XML files), and unstructured data sources (such as text, images, audio, etc.).

[0064] ii. Data collection adapter development: Develop corresponding collection adapters for different types of data sources, supporting multiple data collection methods such as FTP, API, database connection, and streaming data collection.

[0065] iii. Data cleaning and conversion: Clean, convert and standardize the collected data to ensure data quality and consistency. Implement data format conversion, missing value processing, data deduplication and other operations.

[0066] 2. Data storage and management

[0067] i. Data warehouse construction: Establish a storage warehouse for structured data and use efficient query and analysis tools (such as Hive and Presto) for data management.

[0068] ii. Data lake construction: Build a data lake to store semi-structured and unstructured data, and use big data processing technologies (such as Hadoop and Spark) for data processing.

[0069] iii. Metadata management: Develop a metadata management system to record data sources, data tables, field information, data lineage, and data relationships to ensure data traceability and ease of management.

[0070] iv. Data asset management: Manage data resources as assets, establish a data asset catalog, and realize full life cycle management and value mining of data.

[0071] 3. Data Processing and Analysis

[0072] i. Batch processing and stream processing engines: Deploy batch processing engines (such as Spark) and stream processing engines (such as Flink) to implement batch processing and real-time stream processing of large-scale data.

[0073] ii. Data modeling and analysis tools: Provide data modeling and analysis tools, support a variety of data analysis methods and algorithms, and users can perform data modeling, statistical analysis, machine learning and other operations.

[0074] iii. Natural Language Processing (NLP): Integrate large language models, develop NLP functional modules, implement parsing, semantic understanding and information extraction of users’ natural language needs, and support natural language query and interaction.

[0075] 4. Data services and sharing

[0076] i.API service development: Based on data resources, develop standardized API services, support multiple interfaces such as REST API and GraphQL, for external systems and users to access data.

[0077] ii. Data service registration and release: Establish a data service registration and release system to realize the automated registration, release and management of data services.

[0078] iii. Service monitoring and optimization: Monitor API call frequency, response time, and error rate in real time, use multimodal large models to analyze the results, provide performance optimization suggestions, and implement automated tuning.

[0079] 5. User interaction and display

[0080] i. Multimodal interactive interface development: Develop a user interface that supports multimodal interaction, allowing users to query and operate data through natural language, voice, graphical interface, and other methods, to achieve a seamless multimodal interactive experience.

[0081] ii. Data visualization tools: Integrate rich data visualization components (such as charts, dashboards, and report generators) to support users in intuitively displaying and analyzing data.

[0082] iii. Intelligent recommendation system: Analyze user behavior and needs based on multimodal large models, develop personalized data recommendation systems, and generate personalized data set recommendation lists and analysis tools.

[0083] 6. Security and Privacy Protection

[0084] i. Data desensitization and encryption: Develop dynamic desensitization and encryption processing modules to dynamically desensitize and encrypt sensitive data to ensure the security of data during transmission and use.

[0085] ii. Access control and auditing: Perform data access control based on user roles and permissions, record all data operation logs, and provide security auditing functions.

[0086] iii. Data security strategy: Develop and implement a comprehensive data security strategy to ensure data security and privacy protection throughout its life cycle.

[0087] 7. System management and operation and maintenance

[0088] i. System monitoring and alarm: Develop a system monitoring and alarm module to monitor the operating status of the platform in real time, including hardware resources, software components and data services, and provide anomaly detection and alarm functions.

[0089] ii. Log management and analysis: Integrated log management system to collect and analyze system logs to support troubleshooting and performance optimization.

[0090] iii. Operation and maintenance automation tools: Provide automated operation and maintenance tools to support automated deployment, upgrades, and maintenance of the system, and improve operation and maintenance efficiency and reliability.

[0091] Through the above implementation process, the present invention provides an efficient, intelligent and secure data open sharing platform, which integrates multiple levels such as data collection and integration, data storage and management, data processing and analysis, data service and sharing, user interaction and display, security and privacy protection, system management and operation and maintenance. By using technologies such as natural language processing, multimodal interaction and intelligent recommendation, efficient management, analysis and sharing of data can be achieved, data utilization efficiency and user experience can be comprehensively improved, and enterprises and organizations can be helped to achieve data-driven business decisions and innovations.

[0092] The above description is only a preferred embodiment of the present invention, which is only used to illustrate the technical solution of the present invention, and is not used to limit the protection scope of the present invention. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention are included in the protection scope of the present invention.

Claims

1. A data open sharing platform based on multimodal data interaction, characterized in that: include: The data collection and integration layer is used to configure and manage multiple data sources, develop data collection adapters, realize unified data collection and access, and clean, convert and standardize data; The data storage and management layer is used to store and manage structured, semi-structured, and unstructured data, including data warehouses and data lakes, manage data metadata and assets, and implement full life cycle management of data; Data processing and analysis layer, including batch and stream processing engines, data modeling and analysis tools, and natural language processing modules, to achieve large-scale data processing, modeling, and analysis; The data service and sharing layer is used to develop and manage data services, support the automated registration, publishing, and monitoring of data services, and provide performance optimization suggestions and automated tuning. The user interaction and display layer provides a multimodal interactive interface, supports users to query and operate data through natural language, voice, and graphical interface, and integrates data visualization tools and intelligent recommendation systems; The security and privacy protection layer is used for data desensitization and encryption, data access control based on user roles and permissions, and records all data operation logs to provide data security audit functions; The system management and operation and maintenance layer includes system monitoring and alarm, log management and analysis, and operation and maintenance automation tools to achieve automated deployment, upgrades, and maintenance of the system.

2. The platform according to claim 1, characterized in that The data collection and integration layer further includes: Data source management module, used to configure and manage different types of data sources; Data collection adapters to support several data collection methods, including FTP, API, database connection, and streaming data collection; The data cleaning and conversion module is used to clean, convert and standardize the collected data to ensure data quality and consistency.

3. The platform according to claim 1, characterized in that: The data storage and management layer further includes: Data warehouse, which is used to store structured data and support query and analysis operations; Data lake, which is used to store semi-structured and unstructured data and supports large-scale data storage and processing; Metadata management module, used to manage data metadata, including data sources, data tables, field information, data lineage, and data relationships; The data asset management module is used to manage data resources as assets and realize the full life cycle management and value mining of data.

4. The platform according to claim 1, characterized in that: The data processing and analysis layer further includes: Batch and stream processing engines, used for batch processing and real-time stream processing of large-scale data; Data modeling and analysis tools to support a variety of data analysis methods and algorithms; The natural language processing module is used to parse users' natural language needs, perform semantic understanding and information extraction, and support natural language query and interaction.

5. The platform according to claim 1, characterized in that: The data service and sharing layer further includes: API service management module, used to develop and manage data services, supporting REST API and GraphQL interfaces; Data service registration and publishing module, used to realize the automatic registration, publishing and management of data services; The service monitoring and optimization module is used to monitor the usage of data services in real time, analyze call frequency, response time and error rate, provide performance optimization suggestions and implement automated tuning.

6. The platform according to claim 1, characterized in that: The user interaction and presentation layer further includes: Multimodal interactive interface, used to support users to query and operate data through natural language, voice, and graphical interface; Data visualization tools are used to provide rich data visualization components to support users in intuitively displaying and analyzing data; Intelligent recommendation system, used to generate personalized data recommendation lists and analysis tools based on user behavior and demand analysis.

7. The platform according to claim 1, characterized in that The security and privacy protection layer further includes: Data desensitization and encryption module, used to dynamically desensitize and encrypt sensitive data to ensure data security during transmission and use; Access control and audit module, which is used to control data access based on user roles and permissions, record all data operation logs, and provide security audit functions; Data security strategy is used to formulate and implement comprehensive data security strategies to ensure the security and privacy protection of data throughout its life cycle.

8. The platform according to claim 1, characterized in that The system management and operation and maintenance layer further includes: System monitoring and alarm module, which is used to monitor the operation status of the platform in real time, including hardware resources, software components and data services, and provide anomaly detection and alarm functions; Log management and analysis module, used to collect and analyze system logs, support troubleshooting and performance optimization; Operation and maintenance automation tools are used to support the automated deployment, upgrade, and maintenance of the system, improving operation and maintenance efficiency and reliability.

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