Multi-modal file data co-processing management system

Abstract

The invention discloses a multi-modal file data co-processing management system, which relates to the technical field of file management and comprises a data input layer, a data storage layer, a data processing layer, a business logic layer, an application layer, an integration layer, a security monitoring layer and an infrastructure layer. The method not only supports management and processing of various data types, improves data inclusivity and processing capability, but also has real-time cooperation and version control functions, improves team cooperation efficiency, reduces data conflicts, ensures data integrity and consistency, simplifies data entry, classification, filing and retrieval processes through automatic tools and algorithms, and improves the efficiency of team cooperation. And meanwhile, an intelligent search function is provided, required data can be quickly positioned, a user can remotely access archive data from any place with network connection, the accessibility of the data is improved, the system also supports cross-department data sharing, and the circulation and collaboration of information are promoted.

Description

Technical Field

[0001] The present invention relates to the technical field of archive management, and in particular to a multi-modal archive data collaborative processing and management system. Background Art

[0002] With the rapid development of information technology and the information industry, a wave of informatization characterized by digitization, networking, intelligence, and wisdom has emerged. Informatization has been widely and deeply applied in various fields of society. Archives informatization has become an inevitable development trend of archives management, and archives work has gradually moved from the traditional management model to the information age.

[0003] The existing technology has the following problems: Existing archive management systems often encounter various challenges during operation. These problems not only affect the efficiency, security, and scalability of the system, but may also damage the user experience. For example, insufficient data security can easily lead to sensitive information leakage or illegal access; low search efficiency makes it difficult for users to quickly locate the required files; data redundancy and system compatibility issues may lead to waste of storage space and difficulty in data sharing. In addition, there are problems such as poor user experience, limited scalability of the system, high maintenance costs, version control difficulties, lack of audit and tracking functions, non-compliance with legal and compliance requirements, inconvenience in backup and recovery, insufficient technical support, and excessive hardware dependence. Summary of the invention

[0004] The present invention provides a multi-modal archive data collaborative processing management system to solve the problems raised in the above background technology.

[0005] In order to solve the above technical problems, the technical solution adopted by the present invention is: A multi-modal archive data collaborative processing management system, comprising a data input layer, a data storage layer, a data processing layer, a business logic layer, an application layer, an integration layer, a security monitoring layer, and an infrastructure layer; The data input layer is responsible for receiving multimodal data from various sources, including text, images, audio and video, etc. The data input layer is closely connected with the data storage layer and transmits the collected data to the storage layer for storage; The data storage layer is used to store and process structured and unstructured data to ensure data persistence and reliability. The data storage layer exchanges data with the data input layer and provides a data access interface for the data processing layer. The data processing layer can clean, convert, index and merge the data in the storage layer, and provide the processed data to the business logic layer. The data processing layer obtains data from the data storage layer and passes the processed data to the business logic layer. The business logic layer can implement the core functions of the system, such as the collaborative processing engine, the authority control module, and the version control module. The business logic layer works closely with the data processing layer, uses the processed data to execute the business logic, and passes the results to the application layer; The application layer provides a user interface and application programs for users to perform data operations and access system functions. The application layer receives user input, processes data through the business logic layer, and feeds back the processing results to the user; The integration layer can realize integration with other systems and provide data exchange and extension functions through API. The integration layer cooperates with the business logic layer and the application layer to ensure the openness and interoperability of the system; The security monitoring layer is responsible for the security and stability of the system, including encryption modules, identity authentication and authorization, monitoring tools, backup and recovery, etc. The security monitoring layer runs through the entire system architecture and provides security protection and monitoring functions for all levels; The infrastructure layer can provide the infrastructure required for system operation, including servers, networks, cloud services, load balancers, etc. The infrastructure layer is the foundation of all levels and provides physical resources and computing power for the system.

[0006] A further improvement of the technical solution of the present invention is that: the data input layer includes a data acquisition interface and a data conversion module; The data acquisition interface is responsible for receiving and importing external data, such as from scanners, cameras, web crawlers, etc.; The data conversion module can convert raw data into a format that can be processed within the system, such as converting images, audio and video files into digital signals.

[0007] A further improvement of the technical solution of the present invention is that: the data storage layer includes a database management system, a file storage system and an object storage; The database management system is responsible for storing and processing structured data, including relational databases and NoSQL databases; The file storage system is used to store unstructured data, such as a file server or a distributed file system; The object storage can provide a storage solution for large-scale unstructured data, such as Amazon S3 or Google Cloud Storage.

[0008] A further improvement of the technical solution of the present invention is that: the data processing layer includes a data cleaning and preprocessing module, a data indexing module, and a multimodal data fusion engine; The data cleaning and preprocessing module is responsible for removing errors and inconsistencies in the data and preparing the data for subsequent analysis; The data indexing module is capable of creating indexes for data to speed up the search and retrieval process; The multimodal data fusion engine can fuse different types of data to form a unified view for easy comprehensive analysis.

[0009] A further improvement of the technical solution of the present invention is that: the business logic layer includes a collaborative processing engine, a permission control module and a version control module; The collaborative processing engine can support multiple users to edit and access the same archive data at the same time and handle concurrent operations; The authority control module can control data access and operation according to user roles and authorities; The version control module can track the data change history and ensure the integrity and traceability of the data.

[0010] A further improvement of the technical solution of the present invention is that: the application layer includes a user interface, a data analysis tool and a workflow management; The user interface can provide an interface for users to interact with the system, and can be a Web application or a desktop application; The data analysis tool can provide data visualization, report generation and decision support tools; The workflow management is used to define and execute the workflow of data processing.

[0011] A further improvement of the technical solution of the present invention is that: the integration layer includes an API interface and a data exchange format; The API interface allows the system to exchange data and integrate with external systems; The data exchange format supports standard data exchange formats, such as JSON, XML, etc., to facilitate integration with other systems.

[0012] A further improvement of the technical solution of the present invention is that: the security monitoring layer includes an encryption module, identity authentication and authorization, monitoring tools, and backup and recovery; The encryption module can ensure the security of data during transmission and storage; Said authentication and authorization can ensure that only authorized users can access the system; The monitoring tool can monitor system performance, record user behavior and system event logs; The backup and recovery can back up data regularly and provide a data recovery mechanism.

[0013] A further improvement of the technical solution of the present invention is that: the infrastructure layer includes a server, a network, a cloud service and a load balancer; The server can provide computing resources and can be a physical server or a virtual server; The network can provide network connection to ensure the stability and security of data transmission; The cloud service can utilize cloud computing resources, such as computing instances, storage, and database services; The load balancer is responsible for distributing network traffic and improving system availability and scalability.

[0014] Due to the adoption of the above technical solution, the present invention has the following technical advances compared with the prior art: 1. The present invention provides a multimodal archive data collaborative processing management system to achieve efficient collaboration and data diversity processing. The system not only supports the management and processing of multiple data types, improves data inclusiveness and processing capabilities, but also has real-time collaboration and version control functions, improves team collaboration efficiency, reduces data conflicts, and ensures data integrity and consistency.

[0015] 2. The present invention provides a multimodal archive data collaborative processing and management system, which achieves a dual improvement in data management efficiency and security. It simplifies the data entry, classification, archiving and retrieval processes through automated tools and algorithms, and provides intelligent search functions to quickly locate required data. In addition, sophisticated permission settings and encrypted storage ensure the security and confidentiality of data, preventing unauthorized access and data leakage.

[0016] 3. The present invention provides a multimodal archival data collaborative processing and management system to enhance data accessibility, sharing and system flexibility. Users can remotely access archival data from any location with a network connection, thereby improving data accessibility. The system also supports cross-departmental data sharing, promoting the circulation and collaboration of information. At the same time, the system has good scalability and flexibility, can easily adapt to changes in business needs, and can be integrated with existing IT infrastructure and business systems.

[0017] 4. The present invention provides a multi-modal archive data collaborative processing management system, which improves cost-effectiveness and decision-making support capabilities, reduces the storage and management costs of paper archives through digitized archives, and reduces labor costs through automated and intelligent data processing. In addition, the data analysis and reporting functions provided by the system help management to better understand archive data and make trend forecasts based on data, providing strong support for strategic planning. These advantages jointly promote the improvement of organizational decision-making efficiency and the reduction of costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 It is a system flow chart of the multi-modal archive data collaborative processing management system of the present invention; Figure 2 It is a system architecture diagram of the multimodal archive data collaborative processing and management system used in the present invention. DETAILED DESCRIPTION

[0019] The present invention is further described in detail below in conjunction with embodiments: Example 1 like Figure 1 As shown, the present invention provides a multi-modal archive data collaborative processing management system, including a data input layer, a data storage layer, a data processing layer, a business logic layer, an application layer, an integration layer, a security monitoring layer, and an infrastructure layer; The data input layer is responsible for receiving multimodal data from various sources, including text, images, audio, and video. The data input layer is closely connected to the data storage layer and transmits the collected data to the storage layer for storage; The data storage layer is used to store and process structured and unstructured data to ensure data persistence and reliability. The data storage layer exchanges data with the data input layer and provides a data access interface for the data processing layer. The data processing layer can clean, convert, index and merge the data in the storage layer, and provide the processed data to the business logic layer. The data processing layer obtains data from the data storage layer and passes the processed data to the business logic layer. The business logic layer can implement the core functions of the system, such as the collaborative processing engine, permission control module, and version control module. The business logic layer works closely with the data processing layer, uses the processed data to execute business logic, and passes the results to the application layer; The application layer provides user interfaces and applications for users to perform data operations and access system functions. The application layer receives user input, processes data through the business logic layer, and feeds back the processing results to the user. The integration layer can realize integration with other systems and provide data exchange and extension functions through API. The integration layer cooperates with the business logic layer and application layer to ensure the openness and interoperability of the system. The security monitoring layer is responsible for the security and stability of the system, including encryption modules, identity authentication and authorization, monitoring tools, backup and recovery, etc. The security monitoring layer runs through the entire system architecture, providing security protection and monitoring functions for all levels; The infrastructure layer can provide the infrastructure required for system operation, including servers, networks, cloud services, and load balancers. The infrastructure layer is the foundation of all levels and provides physical resources and computing power for the system.

[0020] In this embodiment, data passes through the storage layer and the processing layer from the input layer to the business logic layer and the application layer. Users send requests through the application layer, the business logic layer processes these requests and controls the operations of the data processing layer. The application layer receives the processing results of the business logic layer and passes user feedback back to the system to optimize and improve data processing and business logic. The security and monitoring layers run through all levels to ensure the security and compliance of data throughout the entire process, thereby achieving efficient, secure, and reliable collaborative processing of multimodal archival data while maintaining the flexibility and scalability of the system.

[0021] Example 2 like Figure 2 As shown, based on Example 1, the present invention provides a technical solution: preferably, the data input layer includes a data acquisition interface and a data conversion module; The data collection interface is responsible for receiving and importing external data, such as from scanners, cameras, web crawlers, etc. These interfaces usually support multiple data sources to ensure the diversity and breadth of data; The data conversion module converts raw data into a format that can be processed within the system, such as converting images, audio and video files into digital signals. This process involves parsing and converting multiple data formats to ensure data compatibility and consistency.

[0022] The data storage layer includes database management system, file storage system and object storage; Database management systems are responsible for storing and processing structured data, including relational databases and NoSQL databases. These database management systems provide efficient data storage and query capabilities and support complex data relationships and transaction processing; File storage systems are used to store unstructured data, such as file servers or distributed file systems. These systems provide flexible data storage solutions and support the storage and access of large-scale data. Object storage can provide storage solutions for large-scale unstructured data, such as Amazon S3 or Google Cloud Storage. These object storage services are usually highly available and scalable, and support fast access and efficient transmission of data.

[0023] The data processing layer includes data cleaning and preprocessing modules, data indexing modules, and multimodal data fusion engines; The data cleaning and preprocessing module is responsible for removing errors and inconsistencies in the data and preparing the data for subsequent analysis. This module usually includes operations such as data deduplication, formatting, and standardization to ensure the quality and accuracy of the data. The data index module can create indexes for data to speed up the search and retrieval process. The establishment of indexes can significantly improve the efficiency of data retrieval and support complex query operations. A multimodal data fusion engine can fuse different types of data to form a unified view for easy comprehensive analysis. This engine usually involves data fusion algorithms and models that can handle the association and mapping between different types of data.

[0024] The business logic layer includes the collaborative processing engine, permission control module and version control module; The collaborative processing engine can support multiple users to edit and access the same archive data at the same time and handle concurrent operations. This engine ensures data consistency and real-time performance, and supports efficient team collaboration. The permission control module can control data access and operations based on user roles and permissions. This module ensures data security and prevents unauthorized access and operations. The version control module can track the history of data changes and ensure the integrity and traceability of the data. This module usually includes version records, difference comparison and rollback functions, and supports data version management and historical recovery.

[0025] The application layer includes user interfaces, data analysis tools, and workflow management; The user interface provides an interface for users to interact with the system. It can be a web application or a desktop application. These interfaces are usually designed to be user-friendly, easy to operate, and support multiple user interaction methods. Data analysis tools can provide data visualization, report generation and decision support tools, which can help users better understand the data and support data-driven decision making; Workflow management is used to define and execute data processing workflows. This module usually includes functions such as workflow design, task allocation, and progress monitoring, and supports the automation and management of complex business processes.

[0026] The integration layer includes API interfaces and data exchange formats; API interfaces allow the system to exchange and integrate data with external systems. These interfaces usually follow open standards and support multiple data formats and protocols to ensure system interoperability. Data exchange formats support standard data exchange formats, such as JSON, XML, etc., to facilitate integration with other systems. These formats generally have good compatibility and scalability, and support data exchange and sharing between different systems.

[0027] The security monitoring layer includes encryption modules, authentication and authorization, monitoring tools, and backup and recovery; The encryption module can ensure the security of data during transmission and storage. This module usually includes functions such as data encryption, decryption and key management to protect data from unauthorized access and attacks; Authentication and authorization can ensure that only authorized users can access the system. This module usually includes functions such as user authentication, permission allocation and access control to ensure the security of the system; Monitoring tools can monitor system performance, record user behavior and system event logs. These tools usually include functions such as performance monitoring, log analysis and alarm mechanisms to support stable system operation and problem diagnosis; Backup and recovery can back up data regularly and provide a data recovery mechanism. This module usually includes functions such as data backup, recovery, and disaster recovery to ensure data persistence and system reliability.

[0028] The infrastructure layer includes servers, networks, cloud services, and load balancers; Servers can provide computing resources and can be physical servers or virtual servers. These servers usually have high performance and high availability to support stable operation and expansion of the system. The network can provide network connections to ensure the stability and security of data transmission. This layer usually includes network equipment, security equipment and network management tools to ensure efficient and secure data transmission; Cloud services can utilize cloud computing resources, such as computing instances, storage, and database services. These cloud services are usually highly elastic and scalable, supporting flexible deployment and on-demand expansion of systems. The load balancer is responsible for distributing network traffic and improving the availability and scalability of the system. This component usually includes functions such as traffic distribution, failover, and performance optimization to ensure high availability and stability of the system.

[0029] In this embodiment, through this multi-level, modular architecture design, the system can effectively process and manage various types of data, support the business development and decision-making of the enterprise, not only improve the efficiency and quality of data processing, but also ensure the security of data and the stability of the system, providing a solid foundation for the digital transformation of the enterprise.

[0030] The above generally describes the present invention in detail, but it is obvious to a person skilled in the art that some modifications or improvements can be made to the present invention. Therefore, modifications or improvements that do not depart from the spirit of the present invention are within the scope of protection of the present invention.

Claims

1. A multi-modal archival data collaborative processing and management system, characterized in that: It includes data input layer, data storage layer, data processing layer, business logic layer, application layer, integration layer, security monitoring layer, and infrastructure layer; The data input layer is responsible for receiving multimodal data from various sources, including text, images, audio and video. The data input layer is closely connected with the data storage layer and transmits the collected data to the storage layer for storage; The data storage layer is used to store and process structured and unstructured data to ensure data persistence and reliability. The data storage layer exchanges data with the data input layer and provides a data access interface for the data processing layer. The data processing layer can clean, convert, index and merge the data in the storage layer, and provide the processed data to the business logic layer. The data processing layer obtains data from the data storage layer and passes the processed data to the business logic layer. The business logic layer can implement the core functions of the system, such as the collaborative processing engine, the authority control module and the version control module. The business logic layer works closely with the data processing layer, uses the processed data to execute the business logic, and passes the results to the application layer; The application layer provides a user interface and application programs for users to perform data operations and access system functions. The application layer receives user input, processes data through the business logic layer, and feeds back the processing results to the user; The integration layer can realize integration with other systems and provide data exchange and extension functions through API. The integration layer cooperates with the business logic layer and the application layer to ensure the openness and interoperability of the system; The security monitoring layer is responsible for the security and stability of the system, including encryption modules, identity authentication and authorization, monitoring tools, and backup and recovery. The security monitoring layer runs through the entire system architecture and provides security protection and monitoring functions for all levels; The infrastructure layer can provide the infrastructure required for system operation, including servers, networks, cloud services and load balancers. The infrastructure layer is the foundation of all levels and provides physical resources and computing power for the system.

2. A multi-modal archival data collaborative processing and management system according to claim 1, characterized in that: The data input layer includes a data acquisition interface and a data conversion module; The data acquisition interface is responsible for receiving and importing external data, such as from scanners, cameras, and web crawlers; The data conversion module can convert raw data into a format that can be processed within the system, such as converting images, audio and video files into digital signals.

3. The multimodal archival data collaborative processing and management system according to claim 1, characterized in that: The data storage layer includes a database management system, a file storage system and an object storage; The database management system is responsible for storing and processing structured data, including relational databases and NoSQL databases; The file storage system is used to store unstructured data, such as a file server or a distributed file system; The object storage can provide a storage solution for large-scale unstructured data, such as Amazon S3 or Google Cloud Storage.

4. The multimodal archival data collaborative processing and management system according to claim 1, characterized in that: The data processing layer includes a data cleaning and preprocessing module, a data indexing module, and a multimodal data fusion engine; The data cleaning and preprocessing module is responsible for removing errors and inconsistencies in the data and preparing the data for subsequent analysis; The data indexing module is capable of creating indexes for data to speed up the search and retrieval process; The multimodal data fusion engine can fuse different types of data to form a unified view for easy comprehensive analysis.

5. The multimodal archival data collaborative processing and management system according to claim 1, characterized in that: The business logic layer includes a collaborative processing engine, a permission control module and a version control module; The collaborative processing engine can support multiple users to edit and access the same archive data at the same time and handle concurrent operations; The authority control module can control data access and operation according to user roles and authorities; The version control module can track the data change history and ensure the integrity and traceability of the data.

6. A multi-modal archival data collaborative processing and management system according to claim 1, characterized in that: The application layer includes user interface, data analysis tools and workflow management; The user interface can provide an interface for users to interact with the system, and can be a Web application or a desktop application; The data analysis tool can provide data visualization, report generation and decision support tools; The workflow management is used to define and execute the workflow of data processing.

7. A multi-modal archival data collaborative processing and management system according to claim 1, characterized in that: The integration layer includes an API interface and a data exchange format; The API interface allows the system to exchange data and integrate with external systems; The data exchange format supports standard data exchange formats, such as JSON and XML, to facilitate integration with other systems.

8. The multimodal archival data collaborative processing and management system according to claim 1, characterized in that: The security monitoring layer includes encryption modules, identity authentication and authorization, monitoring tools, and backup and recovery; The encryption module can ensure the security of data during transmission and storage; Said authentication and authorization can ensure that only authorized users can access the system; The monitoring tool can monitor system performance, record user behavior and system event logs; The backup and recovery can back up data regularly and provide a data recovery mechanism.

9. The multimodal archival data collaborative processing and management system according to claim 1, characterized in that: The infrastructure layer includes servers, networks, cloud services, and load balancers; The server can provide computing resources and can be a physical server or a virtual server; The network can provide network connection to ensure the stability and security of data transmission; The cloud service can utilize cloud computing resources, such as computing instances, storage, and database services; The load balancer is responsible for distributing network traffic and improving system availability and scalability.

Images