Heavy asset REITs database management system and method

Abstract

The invention relates to the technical field of data management, in particular to a heavy asset REITs database management system and method.The system comprises a three-dimensional association model and a multi-dimensional task management module, a license full-life-cycle management module, an archive resource positioning module and a full-link operation auditing module, and the three-dimensional association model is a cross-module data dynamic linkage center. The method comprises the steps of constructing a three-dimensional dynamic index and transaction mechanism, performing task classification and screening, managing and controlling the whole process of certificates, correlating and positioning archives and reserving full-link operation traces, and combining an intelligent screening and batch processing technology. According to the invention, the problems of scattered license and archive management, incomplete process tracing and low screening processing efficiency of the existing system are solved, integrated management and compliance auditing are realized, and efficient compliance data support is provided for REITs business.

Description

Technical Field

[0001] This invention belongs to the field of data management technology, specifically relating to a database management system and method for heavy asset REITs. Background Technology

[0002] Existing REITs project management systems are mainly used to implement basic functions such as project license management, file storage, and task workflow processing. However, in practical applications, they suffer from numerous technical bottlenecks, making it difficult to meet the full-process management and financial-grade compliance requirements of asset-heavy REITs businesses. Specific issues are as follows: (1) Rigid data association mode and data silos: Existing systems mostly adopt a "one-to-one" static association method, which can only achieve simple binding of certificates and project basic information, and has not established a dynamic association between certificates, tasks and files. File location only relies on the physical storage level and has no linkage with the status of certificates (such as "under change" or "expired"), which makes it impossible to quickly locate related files in the business process and lacks cross-module data collaboration capabilities; (2) Business process breaks down and manual intervention is required: the task, certificate and file modules operate independently and the process nodes rely on manual jumps. For example, after the certificate review is completed, the file archiving process needs to be manually triggered, which is easy to cause operation omissions or process interruptions, and cannot achieve automated closed-loop management of the entire business chain. (3) Insufficient filtering and batch processing capabilities: The filtering function is limited to single-field retrieval and cannot support multi-dimensional combined condition queries, making it difficult to meet the complex filtering needs in financial compliance audits (such as filtering by time range, department, task status, file storage location, etc.); Batch operations lack atomicity guarantees, and failure during operation can easily result in "dirty data" where some data is changed and some is not changed, and repeated execution of the same operation may lead to data inconsistency (such as repeatedly binding the same file). (4) Weak support for process traceability and compliance audit: The operation traceability is unclear, the log records are scattered, and there is a lack of full-link traceability capability, making it impossible to accurately track the status changes before and after data modification; the log query function is limited and it is difficult to meet the compliance requirements of the financial industry for auditable and traceable operation behavior.

[0003] In view of this, the present invention is hereby proposed. Summary of the Invention

[0004] To address the aforementioned technical problems in existing technologies, this invention provides a database management system and method for heavy asset REITs, resolving issues such as fragmented management of licenses and records, incomplete process traceability, and low efficiency in screening and processing in existing systems.

[0005] To achieve the above objectives, the technical solution of the present invention is as follows: Firstly, a database management system for asset-heavy REITs includes: The multi-dimensional task management module is used to handle the classification of pending items, the execution of business operations and the updating of task status, and to associate certificates and project-related data. The Certificate and License Lifecycle Management Module is used for the full-process management of certificates and licenses from data entry to archiving. The archival resource location module is used to establish the association between physical archives and electronic data, enabling archive location, retrieval, and information updates. The end-to-end operation audit module is used to record system operation behavior and provide log query function; The three-dimensional association module is used to establish dynamic linkage of business data among the multi-dimensional task management module, certificate lifecycle management module, archive resource positioning module, and full-link operation audit module through a unique identifier.

[0006] Furthermore, the multi-dimensional task management module includes: Task classification unit: used to categorize the to-do items into tabs according to business type; Filtering unit: Used to provide multi-condition combined filtering functions; Task processing unit: Used to perform business operations on pending items and update task status.

[0007] Furthermore, the task classification unit's tab categories include three types: project binding, certificate change, and process approval; The filtering unit supports input of combined filtering conditions such as approval status, time range, and applicant. When performing business operations, the task processing unit associates the business data corresponding to the certificate number, project name, and validity period.

[0008] Furthermore, the certificate lifecycle management module includes: Certificate and license display unit: used to display original images of certificates and licenses, a list of attachments, and attribute information; Attachment Operation Unit: Used to perform attachment download and association operations; Version control unit: Used to record the history of attachment operations; Validation verification unit: Used to verify the validity of certificates during the audit process.

[0009] Furthermore, the attachment operation unit establishes a file index using a unique certificate number, supporting batch association of multiple files; The attachment operation history recorded by the version control unit includes the attachment's upload time, deletion time, download time, and corresponding operator information.

[0010] Furthermore, the archive resource location module includes: Archive location unit: used to enable the retrieval of physical archives and electronic data; Batch operation unit: Used to perform batch association, deletion and location information export operations of files.

[0011] Furthermore, the file location unit adopts a three-level location system, which consists of the company level, the department file repository level, and the specific file level. The document location unit supports searching by certificate name, storage location, and document administrator.

[0012] Furthermore, the end-to-end operation audit module includes: Log classification unit: used to classify operation logs into login logs, change logs, and query logs according to type; Log recording unit: used to record specific information of the corresponding log type; Log retrieval unit: Used to perform log filtering and retrieval operations.

[0013] Furthermore, the login log information recorded by the log recording unit includes login IP, login time and account information; the change log information includes the old and new values ​​before and after data modification; and the query log information includes query conditions, the range of data involved and the operation time. The log retrieval unit supports filtering and retrieval by time, operator, and keywords, and supports exporting the retrieval results in Excel format.

[0014] Secondly, a database management method for asset-heavy REITs includes: S1. Construct a three-dimensional association model, establish a dynamic index system based on preset indexes, and configure the association rule engine and distributed transaction mechanism; S2. Perform multi-dimensional task processing: categorize user-triggered to-do items into tabs, receive multi-condition combination filtering input to locate the target task, update the task status and trigger log recording after completing the business operation; S3. Implement full lifecycle management of certificates and licenses: Display original images of certificates and licenses, a list of attachments and attribute information, realize batch association and version control of attachments through unique certificate and license numbers, and automatically verify the validity of certificates and licenses during the review process; S4. Perform archive resource location management: Based on the three-level location system, perform associated retrieval, perform batch archive association and deletion operations, and export location information; S5. Perform full-link operation audit: record login logs, change logs and query logs by category, receive filtering and search conditions and output structured search results; S6: The intelligent filtering engine converts natural language filtering conditions into SQL query statements and optimizes the query execution plan by combining covering indexes; the distributed transaction framework of the batch processing engine ensures the atomicity of batch operations, and the unique token and Redis caching design avoid duplicate execution.

[0015] Compared with existing technologies, the heavy asset REITs database management system and method provided by this invention include a three-dimensional relational model and modules for multi-dimensional task management, full lifecycle management of certificates and licenses, file resource location, and full-link operation auditing. The three-dimensional relational model serves as the central hub for dynamic data linkage across modules. The method includes constructing a three-dimensional dynamic index and transaction mechanism, performing task classification and filtering, full-process control of certificates and licenses, file association and location, and full-link operation traceability, combined with intelligent filtering and batch processing technologies. This invention enables integrated management and compliance auditing, providing efficient and compliant data support for REITs business. Attached Figure Description

[0016] Figure 1 An architecture diagram of the heavy asset REITs database management system provided in this embodiment of the invention; Figure 2 A flowchart illustrating the heavy asset REITs database management method provided in this embodiment of the invention. Detailed Implementation

[0017] The technical solution of the present invention will be clearly described below with reference to the accompanying drawings. Obviously, the described embodiments are not all embodiments of the present invention. All other embodiments obtained by those skilled in the art without creative effort are within the protection scope of the present invention.

[0018] It should be noted that, unless otherwise specifically stated, the relative arrangement and numerical expressions of the components and steps described in these embodiments should not be construed as limiting the scope of the invention.

[0019] The following description of exemplary embodiments is merely illustrative and is not intended to limit the invention or its application or use in any way. Techniques, methods, and apparatus known to those skilled in the art may not be discussed in detail herein, but where applicable, such techniques, methods, and apparatus should be considered part of this specification.

[0020] Example 1 See Figure 1 , Figure 1 This invention presents an architecture diagram of a heavy-asset REITs database management system, including a multi-dimensional task management module, a certificate and license lifecycle management module, an archive resource location module, a full-link operation audit module, and a three-dimensional association model of "certificate-task-archive" connecting the above four modules. Each module achieves data interaction through a distributed database, cross-module event linkage through message queues, and ensures high efficiency and consistency of data processing through index optimization and a distributed transaction framework. Specifically, it may include: M1, a multi-dimensional task management module, is used to handle the classification of pending tasks, the execution of business operations, and the updating of task status, as well as to link certificates and project-related data; specifically including: M11, Task Classification Unit: Used to classify the pending items into tabs according to business type; the tab classification of the task classification unit includes three categories: project binding, certificate change, and process approval; The system has three pre-defined tabs: project binding, certificate change, and process approval. When a user triggers a task (add / change / approval), the system automatically assigns the pending items to the corresponding tab based on the task type.

[0021] M12, Filtering Unit: Used to provide multi-condition combination filtering function; the filtering unit supports input of combined filtering conditions such as approval status, time range, and applicant; when the task processing unit performs business operations, it associates the business data corresponding to the certificate number, project name, and validity period.

[0022] It integrates multi-condition combination filtering function, supports users to input filtering conditions such as approval status, time range, and applicant, and form query commands by combining logical operators (AND / OR / NOT).

[0023] Specifically, the filtering function uses an intelligent filtering engine, implemented as follows: M121, Lexical and Syntactic Analysis: Receives natural language filtering conditions input by the user, performs lexical and syntactic analysis on them, and generates an Abstract Syntax Tree (AST). M122, SQL Conversion: Generates corresponding SQL query statements based on the abstract syntax tree, supporting range matching such as date ranges and numeric ranges; M123. Index Optimization: Create covering indexes for high-frequency filtering dimensions such as task status and certificate validity period, and use bitmap index technology to optimize the query execution plan and avoid full table scans.

[0024] M13, Task Processing Unit: Used to perform business operations on pending items and update task status.

[0025] It provides a task details page that displays business data such as certificate number, project name, and validity period. It supports users to perform operations such as binding, review, and submission. After the operation is completed, the task status is automatically updated and the operation log is triggered.

[0026] Specifically, task processing employs a batch processing engine, which implements transactional and idempotent batch operations, as detailed below: M131, Distributed Transaction Guarantee: Adopting a distributed transaction framework, batch operations are broken down into multiple sub-transactions such as "batch query of pending tasks → batch verification of compliance → batch update of data → batch logging", and the atomic execution of all sub-transactions is controlled by a global transaction ID; M132, Idempotency Design: Generate a unique token for each batch operation and store the token status in the Redis cache. The status includes "processing" and "completed". When a duplicate operation request is received, the token status in the Redis cache is queried to prevent duplicate execution.

[0027] M2, the Certificate and License Lifecycle Management Module, is used for the full-process management of certificates and licenses from data entry to archiving; specifically, it includes: M21, Certificate Display Unit: Used to display original images of certificates, a list of attachments, and attribute information; The system displays the original images of the certificates, a list of attachments, and attribute information through a graphical interface. The attribute information includes the certificate name, validity period, and associated project ID.

[0028] M22, Attachment Operation Unit: Used to perform attachment download and association operations; the Attachment Operation Unit establishes a file index through a unique certificate number and supports batch association of multiple files; The system establishes a file index using a unique certificate number, supports batch association of multiple files, and also provides an attachment download function.

[0029] M23, Version Control Unit: Used to record attachment operation history; The attachment operation history recorded by the Version Control Unit includes the attachment's upload time, deletion time, download time, and corresponding operator information; Record the upload time, deletion time, download time of attachments, and the corresponding operator information to form a complete attachment operation history.

[0030] M24. Validation Validation Unit: Used to verify the validity of certificates during the review process. The validation content of the validity validation unit includes the legality of the certificate's validity period and the relevance of the certificate to the project. The system automatically verifies the validity and legality of licenses and certificates, as well as their relevance to the project during the review process. Verification rules are preset through configuration files and can be dynamically adjusted.

[0031] M3, the archival resource location module, is used to establish the link between physical archives and electronic data, enabling archive location, retrieval, and information updates; specifically, it includes: M31, Archive Location Unit: Used to realize the association and retrieval of physical archives and electronic data; the archive location unit adopts a three-level location system; the three-level location system is as follows: company level, department file library level, and specific archive level; The archive location unit supports searching by certificate name, storage location, and archive administrator. It adopts a three-level location system of "company → department file library → specific archive", allowing users to search by certificate name, storage location, and archive administrator. The search results display the physical location of the archive and related electronic data information.

[0032] M32, Batch Operation Unit: Used to perform batch association, deletion, and location information export operations on files; It supports batch adding / deleting of file and electronic data associations, and provides a location information export function, with export formats including Excel.

[0033] M4, the end-to-end operation audit module, is used to record system operation behavior and provide log query functions; specifically, it includes: M41, Log Classification Unit: Used to divide operation logs into three categories of tabs: login logs, change logs, and query logs; M42, Log Recording Unit: Used to record specific information of the corresponding type of log; The login log information recorded by the log recording unit includes login IP, login time and account information; the change log information includes the old and new values ​​before and after data modification; and the query log information includes query conditions, the range of data involved and the operation time.

[0034] M43, Log Retrieval Unit, is used to perform log filtering and retrieval operations. The Log Retrieval Unit supports filtering and retrieval by time, operator, and keywords, and supports exporting the retrieval results in Excel format.

[0035] M5, the three-dimensional association module, is used to establish dynamic linkage of business data among the multi-dimensional task management module, the certificate lifecycle management module, the archive resource positioning module, and the full-link operation audit module through a unique identifier.

[0036] The three-dimensional association model constructs a dynamic index system using "certificate number (cert_id) - task ID (task_id) - archive ID (archive_id)" to achieve real-time data linkage across modules, specifically including: Data layer design: Configure the certificate_info table, project_task table, file association table and project_info table in the distributed database. The certificate_info table and project_task table are related by project_id foreign key. The certificate_info table and file association table are linked by cert_id bidirectional index to ensure the reachability of data association. Business logic layer configuration: Deploy an association rule engine to listen for data status change events in each module. When the data in a certain module is updated (such as when the cert_status field in the certificate_info table is changed), the data synchronization operation of the associated modules is automatically triggered. Transaction consistency guarantee: A distributed transaction processing mechanism is adopted to assign a global transaction ID to cross-module related operations. When any related operation fails, all executed sub-transactions are rolled back to avoid data silos.

[0037] Example 2 See Figure 2 , Figure 2 This is a flowchart of a heavy asset REITs database management method proposed in this invention. Based on a three-dimensional association logic of "licenses-tasks-files," combined with intelligent filtering and batch processing technologies, it achieves integrated management and compliance auditing of REITs project data. Specific steps include: S1. Construct a three-dimensional association model, establish a dynamic index system based on preset indexes, and configure the association rule engine and distributed transaction mechanism; specifically including: S11. Data Layer Index Design: Create the certificate_info table, project_task table, and archive association table in the distributed database. The certificate_info table and the project_task table are related through the project_id foreign key, and the certificate_info table and the archive association table are linked through the cert_id bidirectional index, forming a three-dimensional dynamic index system of "certificate number (cert_id) - task ID (task_id) - archive ID (archive_id)".

[0038] S12. Deployment of the association rule engine: Configure the association rule engine in the business logic layer and preset data linkage rules, including triggering conditions and response logic such as "synchronously update the status of associated tasks when the certificate status changes", "trigger certificate compliance verification when the task is created", and "trigger file information update after the certificate verification is passed".

[0039] S13. Distributed Transaction Mechanism Configuration: Adopt a distributed transaction framework (such as Seata) to assign a global transaction ID to cross-module related operations and set transaction rollback rules. When any related operation fails, a unified rollback of all executed sub-transactions is triggered to ensure cross-table data consistency.

[0040] S14. Cross-module collaborative configuration: Deploy message queues and cross-module state machines (StateMachines) to define the triggering conditions and branching logic of events in each module, such as the task flow redirection corresponding to the "pass / reject" status of certificate review and the file operation response rules.

[0041] S2. Perform multi-dimensional task processing: Categorize user-triggered to-do items into tabs, receive multi-condition combined filtering input to locate the target task, update the task status and trigger log recording after completing the business operation; specifically including: S21. Task Creation and Classification: After a user triggers a task (add / change / approval), the system generates a corresponding task record in the project_task table, automatically assigns a unique task_id, and classifies the task into the corresponding tabs of "Project Binding", "Certificate Change" and "Process Approval" according to the business type.

[0042] S22. Task Location and Filtering: Receive user input of approval status, time range, applicant, and other combined filtering conditions, and use logical operators (AND / OR / NOT) to form query instructions to locate target pending tasks.

[0043] S23. Task Execution and Status Update: When a user enters the task details page, the system displays business data such as certificate number, project name, and validity period. After the user completes operations such as binding, review, and submission, the system updates the task status in the project_task table in real time (such as "pending review", "approved", "completed") and triggers operation log recording.

[0044] S3. Implement full lifecycle management of certificates and licenses: Display original images of certificates and licenses, lists of attachments, and attribute information; achieve batch association and version control of attachments through unique certificate and license numbers; and automatically verify the validity of certificates and licenses during the review process; specifically including: S31. Certificate Information Input and Display: Input the original certificate images, attachments, and attribute information (including certificate name, validity period, associated item ID, etc.) into the system. The certificate_info table stores the corresponding data. The certificate details page displays the original images, attachment list, and attribute information in a structured manner.

[0045] S32. Attachment Operations and Version Control: A file index is established using a unique certificate number (cert_id), supporting batch association and download of multiple files; the upload time, deletion time, download time, and corresponding operator information of attachments are recorded to form a complete attachment operation history and achieve version traceability.

[0046] S33. Certificate Validity Verification: During the review process, the system automatically retrieves certificate data from the certificate_info table to verify the validity of the certificate (e.g., whether it is within the validity period, whether the validity period change logic is compliant) and its relevance to the project (e.g., whether the project to which the certificate belongs is consistent with the project bound to the task). The verification rules are preset through the configuration file and support dynamic adjustment.

[0047] S34. Certificate Archiving: When the life cycle of a certificate ends (such as expired or cancelled), the system locates the associated archive through the three-dimensional association model, automatically triggers the archive archiving instruction, and synchronously updates the association status between the certificate and the archive.

[0048] S4. Perform archive resource location management: Based on a three-level location system, perform associated retrieval, batch association and deletion operations of archives, and export location information; specifically including: S41. Archive Association and Location: A three-level location system of "Company → Department File Library → Specific Archive" is adopted. The electronic data of certificates and physical archives are associated through cert_id. Users can quickly locate the physical location of archives and associated electronic data by entering search conditions by certificate name, storage location and archive administrator.

[0049] S42. Batch File Operations: Receives batch file association / deletion operation instructions, batch queries pending file association tasks, verifies file association compliance (such as storage location permissions, association permissions), and then batch updates file association table data; supports exporting file location information in Excel format.

[0050] S5. Perform end-to-end operation auditing: Classify and record login logs, change logs, and query logs; receive filtered search criteria and output structured search results; specifically including: S51. Log Classification and Recording: Operation logs are divided into three categories: login logs, change logs, and query logs. Login logs record login IP, login time, and account information; change logs record the old and new values ​​of data before and after modification, the operator, and the operation time; query logs record query conditions, the range of data involved, and the operation time. All log data is stored in a distributed log database.

[0051] S52. Log Retrieval and Export: Users select the log type (login / change / query), enter filter conditions such as time, operator, and keywords, and the system retrieves data from the distributed log library, displays the log details in a structured manner, and supports exporting the search results to Excel format.

[0052] S6. The intelligent filtering engine converts natural language filtering conditions into SQL query statements, optimizing the query execution plan using covering indexes; the batch processing engine's distributed transaction framework ensures the atomicity of batch operations, and unique tokens and Redis caching prevent duplicate execution. Specifically, this includes: S61. Filtering Condition Parsing: Receives natural language filtering conditions input by the user (such as "certificate and license change tasks submitted by XX department within the last 3 months, with a status of 'pending review' and associated files located in warehouse A"), performs lexical and syntactic analysis through the intelligent filtering engine, and generates an abstract syntax tree (AST).

[0053] Specifically, the filtering criteria parsing process is as follows: S611, Lexical Analysis: Decompose the user-input string (e.g., expiration date > 2025-12-31) into a Token stream (Field = expiration date, Op =>, Value = 2025-12-31).

[0054] S612. Syntax Construction: Construct an AST tree using recursive descent parsing, with the root node representing logical operators (AND / OR) and the leaf nodes representing specific comparison expressions.

[0055] S613, SQL Generation: Traverse the AST tree, map Fields to database column names (valid_date), map Ops to SQL operators, and finally concatenate them into...<WHEREvalid_date> '2025-12-31'.

[0056] S614, Index Hints: If the filter condition is found to contain a high-frequency field (such as task_status), the FORCEINDEX hint will be automatically added when generating the SQL to force the use of a bitmap index.

[0057] S62, SQL Conversion and Optimization: Generates corresponding SQL query statements based on the abstract syntax tree, supporting range matching such as date range and numerical range; establishes covering indexes for high-frequency filtering dimensions such as task status and certificate validity period, and uses bitmap index technology to optimize the query execution plan and avoid full table scans.

[0058] S63. Result Return: The optimized SQL query statement is sent to the database for execution, the data results that meet the conditions are obtained and returned to the user, and the query response time is controlled in milliseconds.

[0059] In this step, the batch processing engine's operation flow specifically includes: Operation token generation and verification: When a user initiates a batch operation (such as batch file association), the system generates a unique operation token and stores the token status in the Redis cache, setting the status to "processing". If a duplicate operation request is received, the system queries the token status in the Redis cache. If it is "completed", the system directly returns the operation result to prevent duplicate execution.

[0060] Distributed transaction execution: A distributed transaction framework breaks down batch operations into multiple sub-transactions, which are then executed sequentially. ① Batch query pending tasks: Query the list of tasks that meet the conditions from the project_task table; ② Batch compliance verification: Verify the compliance of data associated with each task (such as the legality of the location of archives and the validity of certificates); ③ Batch data update: After verification, batch update the relevant data tables (such as the file association table and the task status table). ④ Batch logging: Records detailed log information for batch operations.

[0061] Transaction result processing: If all sub-transactions are executed successfully, the transaction is committed, and the token status in Redis is updated to "completed"; if any sub-transaction fails, the distributed transaction framework coordinates the rollback of all executed sub-transactions, returns error information, and ensures that no "dirty data" is generated.

[0062] Specifically, in the implementation of distributed transactions, the system adopts Seata's AT mode: Phase 1: When each sub-transaction (such as updating the task table or inserting into the log table) executes SQL, the Seata agent automatically generates a "rollback log" and commits it along with the local transaction; Two-phase commit: If all sub-transactions succeed, the Seata server (TC) notifies the deletion of the rollback log, and the transaction is complete; Phase 1: When each sub-transaction (such as updating the task table or inserting into the log table) executes SQL, the Seata agent automatically generates a "rollback log" and commits it along with the local transaction; Two-phase commit: If all sub-transactions succeed, the Seata server (TC) notifies the deletion of the rollback log, and the transaction is complete.

[0063] In summary, the present invention has the following advantages: 1. In response to the problem of the existing system's fragmented management of certificates and archives and the lack of full life cycle linkage, this invention achieves deep binding and full linkage between the two through a three-dimensional linkage model of "certificate-task-archive" and a full life cycle management mechanism, breaking down the barriers of fragmented management; 2. To address the issues of incomplete task process tracing and unclear operation traces in existing systems, this invention constructs a complete traceability chain through a full-link operation audit system, ensuring that operation traces are clear and verifiable; 3. To address the problem that existing systems have low efficiency in multi-dimensional screening and batch processing, making it difficult to meet compliance audit requirements, this invention significantly improves operational efficiency and accurately matches compliance audit requirements through an intelligent screening and batch processing engine.

[0064] The above specific embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to examples, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A database management system for asset-heavy REITs, characterized in that, include: The multi-dimensional task management module is used to handle the classification of pending items, the execution of business operations and the updating of task status, and to associate certificates and project-related data. The Certificate and License Lifecycle Management Module is used for the full-process management of certificates and licenses from data entry to archiving. The archival resource location module is used to establish the association between physical archives and electronic data, enabling archive location, retrieval, and information updates. The end-to-end operation audit module is used to record system operation behavior and provide log query function; The three-dimensional association module is used to establish dynamic linkage of business data among the multi-dimensional task management module, certificate lifecycle management module, archive resource positioning module, and full-link operation audit module through a unique identifier.

2. The heavy asset REITs database management system according to claim 1, characterized in that, The multi-dimensional task management module includes: Task classification unit: used to categorize the to-do items into tabs according to business type; Filtering unit: Used to provide multi-condition combined filtering functions; Task processing unit: Used to perform business operations on pending items and update task status.

3. The heavy asset REITs database management system according to claim 2, characterized in that, The task classification unit's tab categories include three types: project binding, certificate change, and process approval; The filtering unit supports input of combined filtering conditions such as approval status, time range, and applicant. When performing business operations, the task processing unit associates the business data corresponding to the certificate number, project name, and validity period.

4. The heavy asset REITs database management system according to claim 1, characterized in that, The certificate and license lifecycle management module includes: Certificate and license display unit: used to display original images of certificates and licenses, a list of attachments, and attribute information; Attachment Operation Unit: Used to perform attachment download and association operations; Version control unit: Used to record the history of attachment operations; Validation verification unit: Used to verify the validity of certificates during the audit process.

5. The heavy asset REITs database management system according to claim 4, characterized in that, The attachment operation unit establishes a file index using a unique certificate number, supporting batch association of multiple files; The attachment operation history recorded by the version control unit includes the attachment's upload time, deletion time, download time, and corresponding operator information.

6. The heavy asset REITs database management system according to claim 1, characterized in that, The archive resource location module includes: Archive location unit: used to enable the retrieval of physical archives and electronic data; Batch operation unit: Used to perform batch association, deletion and location information export operations of files.

7. The heavy asset REITs database management system according to claim 6, characterized in that, The file location unit adopts a three-level location system, which consists of the company level, the department file repository level, and the specific file level. The document location unit supports searching by certificate name, storage location, and document administrator.

8. The heavy asset REITs database management system according to claim 1, characterized in that, The end-to-end operation audit module includes: Log classification unit: used to classify operation logs into login logs, change logs, and query logs according to type; Log recording unit: used to record specific information of the corresponding log type; Log retrieval unit: Used to perform log filtering and retrieval operations.

9. The heavy asset REITs database management system according to claim 8, characterized in that, The login log information recorded by the log recording unit includes login IP, login time and account information; the change log information includes the old value and the new value before and after the data modification; and the query log information includes query conditions, the range of data involved and the operation time. The log retrieval unit supports filtering and retrieval by time, operator, and keywords, and supports exporting the retrieval results in Excel format.

10. A method for managing a database of asset-heavy REITs, characterized in that, include: S1. Construct a three-dimensional association model, establish a dynamic index system based on preset indexes, and configure the association rule engine and distributed transaction mechanism; S2. Perform multi-dimensional task processing: categorize user-triggered to-do items into tabs, receive multi-condition combination filtering input to locate the target task, update the task status and trigger log recording after completing the business operation; S3. Implement full lifecycle management of certificates and licenses: Display original images of certificates and licenses, a list of attachments and attribute information, realize batch association and version control of attachments through unique certificate and license numbers, and automatically verify the validity of certificates and licenses during the review process; S4. Perform archive resource location management: Based on the three-level location system, perform associated retrieval, perform batch archive association and deletion operations, and export location information; S5. Perform full-link operation audit: record login logs, change logs and query logs by category, receive filtering and search conditions and output structured search results; S6: The intelligent filtering engine converts natural language filtering conditions into SQL query statements and optimizes the query execution plan by combining covering indexes; the distributed transaction framework of the batch processing engine ensures the atomicity of batch operations, and the unique token and Redis caching design avoid duplicate execution.

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