A real estate and land tax source data management method and system based on data lineage

Abstract

The present invention provides a data lineage-based real estate tax source data management method and system, the method comprising: acquiring target real estate tax source data, acquiring data lineage relationship of the target real estate tax source data based on association relationship to obtain lineage relationship data; performing data processing on logarithmic lineage relationship data to obtain processed data; performing data aggregation on the processed data to obtain aggregated data; performing doubt analysis on the aggregated data and outputting the doubt analysis result to achieve the management of real estate tax source data. The present invention performs a series of processing on the real estate tax source data, that is, performs corresponding processing, conversion and merging of the data according to the data lineage relationship between the real estate tax source data, thereby improving the efficiency of real estate tax source data management and also improving the relevance and availability of the real estate tax source data, and then performs corresponding doubt analysis on the data to facilitate the management and verification of the real estate tax source data.

Description

Technical Field

[0001] The present invention belongs to the technical field of data management, and in particular relates to a real estate and land tax source data management method and system based on data lineage. Background Art

[0002] For the current taxpayers' real estate and land tax source verification, manual records were previously used, and the data lacked verification, which was not conducive to subsequent application. On the other hand, there are many real estate and land tax-related data, and most of the real estate and land tax source registration and modification are completed by taxpayers independently through the electronic tax bureau, and the quality of tax source registration is uneven. Among the existing real estate data, the completeness of owner information data accounts for about 65%, among which the lack of address information is more serious, mainly reflected in the incomplete address positioning, and the addresses are all located in a certain street / village / intersection / industrial park / area, etc.; the completeness of real estate information data accounts for about 70%, and some data can only be checked in Jinsan, such as the original value of the property, real estate tax source number, land tax source number, monthly rental amount, etc. Therefore, it can be seen that the existing real estate and land tax source data are usually completed manually, which has the problems of low efficiency and difficult management. Summary of the invention

[0003] In order to solve the above technical problems, the present invention provides a real estate tax source data management method and system based on data lineage, which is used to solve the technical problems raised in the prior art, so as to reduce the user's time cost and ensure that the user can find the target terminal in the shortest time.

[0004] In a first aspect, an embodiment of the present invention provides the following technical solution, a method for managing real estate and land tax source data based on data lineage, comprising:

[0005] Obtain target house and land tax source data, and obtain data lineage relationship of the target house and land tax source data based on the association relationship to obtain lineage relationship data;

[0006] Performing data processing on the blood relationship data to obtain processed data;

[0007] Aggregating the processed data to obtain aggregated data;

[0008] The aggregated data is subjected to doubt analysis and the doubt analysis result is output to realize the management of real estate and land tax source data.

[0009] Compared with the prior art, the beneficial effects of the present application are as follows: the present invention first obtains the target house and land tax source data, and obtains the data blood relationship of the target house and land tax source data based on the association relationship to obtain blood relationship data; then the data blood relationship data is processed to obtain processed data; then the processed data is aggregated to obtain aggregated data; then the aggregated data is analyzed for doubts and the doubt analysis results are output to achieve the management of the house and land tax source data. The present invention performs a series of processing on the house and land tax source data, that is, the data is processed, converted and merged accordingly through the data blood relationship between the house and land tax source data, so as to improve the efficiency of the house and land tax source data management and also improve the relevance and availability of the house and land tax source data. After that, the data is analyzed for doubts accordingly, and the specific analysis results can be displayed to the manager, which is convenient for the management and verification of the house and land tax source data.

[0010] Preferably, the step of acquiring the data blood relationship of the target house and land tax source data based on the association relationship to obtain the blood relationship data is specifically as follows:

[0011] The processing flow data of the target house and land tax source data is extracted using the taxpayer identification number as the first association relationship identifier and the property tax source code and the land tax source code as the second association relationship identifier, and an analysis data table is extracted from the target house and land tax source data, and the blood relationship data is determined based on the processing flow and the analysis data table.

[0012] Preferably, the processing flow data at least includes processing history data, flow information data, and flow path data of the target house and land tax source data.

[0013] Preferably, the analysis data table at least includes a tax source status analysis data table, an income analysis data table, a household data table, and a tax forecast data table.

[0014] Preferably, the step of processing the blood relationship data to obtain processed data includes:

[0015] Identifying data containing missing values ​​in the blood relationship data, and removing the data containing missing values ​​from the blood relationship data to obtain removed data;

[0016] Extracting attribute constraints from the blood relationship data, and performing data correction on the eliminated data based on the attribute constraints to obtain corrected data;

[0017] The blood relationship data is repeatedly cleaned, and a priority queue algorithm is used to retain the target data creation time as a priority strategy to obtain processed data.

[0018] Preferably, the step of aggregating the processed data to obtain aggregated data is specifically:

[0019] The content and dimension of the processed data are extracted, the processed data are converted into data views according to the data, and the data views are aggregated and merged based on the content and dimension of the processed data to obtain aggregated data.

[0020] Preferably, the step of performing doubt analysis on the aggregated data and outputting the doubt analysis result comprises:

[0021] Calculate the first doubt value A based on the aggregated data:

[0022] A=(a1―a2―a3) / (a2+a3);

[0023] In the formula, a1 represents the registered area of ​​real estate, a2 and a3 represent the registered building area of ​​the first real estate tax source and the registered building area of ​​the second real estate tax source respectively;

[0024] Calculate a second doubt value B based on the aggregated data;

[0025] B=(b1―b2) / b2;

[0026] In the formula, b1 represents the real estate rental data, and b2 represents the data on the basis of real estate tax calculation based on rent;

[0027] Calculate a third doubt value C based on the aggregated data;

[0028] C = c1-c2-c3-c4;

[0029] In the formula, c1 represents the area of ​​the leased village land, c2 represents the total area of ​​the leased village land, c3 represents the taxable land area, and c4 represents the assessed taxable land area;

[0030] If the first doubt point value is greater than the first preset value and the second doubt point value is greater than the second preset value and the third doubt point value is greater than the third preset value, then there is no doubt in the aggregated data; if the first doubt point value is not greater than the first preset value or the second doubt point value is not greater than the second preset value or the third doubt point value is not greater than the third preset value, then there is doubt in the aggregated data, and the doubt analysis result is output.

[0031] In a second aspect, an embodiment of the present invention provides the following technical solution, a real estate and land tax source management system based on data lineage, the system comprising:

[0032] An acquisition module is used to acquire target house and land tax source data, and acquire data blood relationship of the target house and land tax source data based on the association relationship to obtain blood relationship data;

[0033] A processing module, used for processing the blood relationship data to obtain processed data;

[0034] an aggregation module, used for aggregating the processed data to obtain aggregated data;

[0035] The management module is used to perform doubt analysis on the aggregated data and output the doubt analysis results to achieve the management of house and land tax source data.

[0036] In a third aspect, an embodiment of the present invention provides the following technical solution: a computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned data lineage-based real estate and land tax source data management method when executing the computer program.

[0037] In a fourth aspect, an embodiment of the present invention provides the following technical solution: a computer-readable storage medium having a computer program stored thereon, and the computer program, when executed by a processor, implements the above-mentioned data lineage-based real estate and land tax source data management method. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0039] Figure 1 A flow chart of a real estate and land tax source data management method based on data lineage provided by an embodiment of the present invention;

[0040] Figure 2 A structural block diagram of a real estate and land tax source management system based on data lineage provided by an embodiment of the present invention;

[0041] Figure 3 A schematic diagram of the hardware structure of a computer device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0042] Embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the embodiments of the present invention, and should not be construed as limiting the present invention.

[0043] Embodiment 1

[0044] In the first embodiment of the present invention, Figure 1 As shown, a real estate and land tax source data management method based on data lineage includes:

[0045] S1. Obtain target house and land tax source data, and obtain data lineage relationship of the target house and land tax source data based on the association relationship to obtain lineage relationship data;

[0046] Specifically, before obtaining the target house and land tax source data, you can obtain the recognition of the data source system on a public sharing platform, and obtain the land tax source table, invoice data table, agency house and land tax source table, taxpayer house and land tax source verification table, and verification result household table (including but not limited to the above tables) in the housing and construction system, the property rights system of the Natural Resources Management Bureau, the business entity registration system of the Market Supervision Administration, the water and electricity system, and the three financial systems (including but not limited to the above systems) to obtain the target house and land tax source data.

[0047] Wherein, the step S1 is specifically as follows:

[0048] Extracting the processing flow data of the target house and land tax source data using the taxpayer identification number as the first association relationship identifier and the property tax source code and the land tax source code as the second association relationship identifier, extracting an analysis data table from the target house and land tax source data, and determining the blood relationship data based on the processing flow and the analysis data table;

[0049] Specifically, the first association relationship identifier is the main identifier, the second association relationship identifier is the secondary identifier, and the processed flow data at least includes the processing history data, flow information data, and flow path data of the target house and land tax source data, and the analysis data table at least includes the tax source status analysis data table, the income analysis data table, the household data table, and the tax forecast data table. Through the historical records of data flow and processing and the system log, the processing history data, flow information data, and flow path data of the target house and land tax source data can be obtained, and then the processed flow data can be obtained. From the house and land tax source data, deed tax data, declaration and payment data, invoice data, through the taxpayer identification number, real estate tax source code, land tax source code and other fields, the tables can be associated to organize the tax source status analysis, income analysis, household data, tax forecast and other data tables.

[0050] S2, performing data processing on the digital blood relationship data to obtain processed data;

[0051] Wherein, the step S2 comprises:

[0052] S21, identifying data containing missing values ​​in the blood relationship data, and removing the data containing missing values ​​from the blood relationship data to obtain removed data;

[0053] Specifically, there may be missing data in blood relationship data, so it is necessary to eliminate missing values. The eliminated data may be taxpayer identification number, property tax source code, land tax source code, invoice identification number, etc.

[0054] S22, extracting attribute constraints from the blood relationship data, and performing data correction on the eliminated data based on the attribute constraints to obtain corrected data;

[0055] Specifically, for the data in the blood relationship data, the data itself has a data range, and there is a mutual constraint relationship between two or more data therein. Therefore, the abnormal data therein can be corrected according to the attribute constraint to obtain the corrected data.

[0056] S23, repeatedly cleaning the blood relationship data, and retaining the data using a priority queue algorithm with the target data creation time as a priority strategy to obtain processed data;

[0057] Specifically, in the present application, a conventional cleaning algorithm may be used to clean the data, and the data to be retained, ie, the processed data, may be determined based on the record creation time of the target data as a priority strategy.

[0058] S3, aggregating the processed data to obtain aggregated data;

[0059] Wherein, the step S3 is specifically as follows:

[0060] The content and dimension of the processed data are extracted, the processed data are converted into data views according to the data, and the data views are aggregated and merged based on the content and dimension of the processed data to obtain aggregated data.

[0061] Specifically, the following table is an example of a data table of aggregated data:

[0062]

[0063]

[0064]

[0065]

[0066]

[0067]

[0068] S4. Perform doubt analysis on the aggregated data and output the doubt analysis results to achieve the management of real estate and land tax source data.

[0069] Wherein, the step S4 comprises:

[0070] S41. Calculate a first doubt value A based on the aggregated data:

[0071] A=(a1―a2―a3) / (a2+a3);

[0072] In the formula, a1 represents the registered area of ​​real estate, a2 and a3 represent the registered building area of ​​the first real estate tax source and the registered building area of ​​the second real estate tax source respectively;

[0073] Specifically, the first property tax source registered building area and the second property tax source registered building area here respectively represent the property tax source registered building area collected from the Jinsan system in the most recent valid tax source in the system time and the property tax source registered building area entrusted for collection.

[0074] S42, calculating a second doubt value B based on the aggregated data;

[0075] B=(b1―b2) / b2;

[0076] In the formula, b1 represents the real estate rental data, and b2 represents the data on the basis of real estate tax calculation based on rent;

[0077] The real estate rental data is specifically the 30th item in the data table of the above aggregated data, and the real estate tax calculation basis data is specifically the 21st item in the data table of the above aggregated data.

[0078] S43, calculating a third doubt value C based on the aggregated data;

[0079] C = c1-c2-c3-c4;

[0080] In the formula, c1 represents the area of ​​the leased village land, c2 represents the total area of ​​the leased village land, c3 represents the taxable land area, and c4 represents the assessed taxable land area;

[0081] Specifically, the leased village land area refers to the leased village land area of ​​the same taxpayer in the same town or street in the one-household data ledger corresponding to the latest time point; the taxable land area refers to the taxable land area with the land grade of "level 11 land or other levels in the city" in the real estate and land tax source data ledger in the Jinsan system; the approved taxable land area refers to the approved taxable land area with the land grade of "level 11 land or other levels in the city" in the real estate and land tax source data ledger entrusted for collection.

[0082] S44. If the first doubt point value is greater than a first preset value, the second doubt point value is greater than a second preset value, and the third doubt point value is greater than a third preset value, then the aggregated data has no doubt points; if the first doubt point value is not greater than the first preset value, the second doubt point value is not greater than the second preset value, or the third doubt point value is not greater than the third preset value, then the aggregated data has doubt points, and the doubt point analysis result is output;

[0083] Specifically, the first preset value is 10%, the second preset value is 10%, and the third preset value is 100.

[0084] The first embodiment of the present invention provides a real estate tax source data management method based on data lineage. First, target real estate tax source data is acquired, and data lineage relationship acquisition is performed on the target real estate tax source data based on the association relationship to obtain lineage relationship data; then, data processing is performed on the data lineage relationship data to obtain processed data; then, the processed data is aggregated to obtain aggregated data; then, suspicious point analysis is performed on the aggregated data and the suspicious point analysis results are output to achieve the management of real estate tax source data. The present invention performs a series of processing on the real estate tax source data, that is, the data is processed, converted and merged accordingly according to the data lineage relationship between the real estate tax source data, so as to improve the efficiency of real estate tax source data management and also improve the relevance and availability of the real estate tax source data. Then, the data is subjected to corresponding suspicious point analysis, and the specific analysis results can be displayed to the manager, so as to facilitate the management and verification of the real estate tax source data.

[0085] Embodiment 2

[0086] like Figure 2 As shown, in the second embodiment of the present invention, a real estate and land tax source management system based on data lineage is provided, and the system includes:

[0087] The acquisition module 1 is used to acquire the target house and land tax source data, and acquire the data blood relationship of the target house and land tax source data based on the association relationship to obtain blood relationship data;

[0088] Processing module 2, used for processing the blood relationship data to obtain processed data;

[0089] Aggregation module 3, used for aggregating the processed data to obtain aggregated data;

[0090] Management module 4, used for performing doubt analysis on the aggregated data and outputting the doubt analysis results to achieve the management of house and land tax source data;

[0091] The acquisition module 1 is specifically used for:

[0092] The processing flow data of the target house and land tax source data is extracted using the taxpayer identification number as the first association relationship identifier and the property tax source code and the land tax source code as the second association relationship identifier, and an analysis data table is extracted from the target house and land tax source data, and the blood relationship data is determined based on the processing flow and the analysis data table.

[0093] The processing module 2 comprises:

[0094] A removal submodule, used for identifying data containing missing values ​​in the blood relationship data, and removing the data containing missing values ​​from the blood relationship data to obtain removed data;

[0095] A correction submodule, used for extracting attribute constraints from the blood relationship data, and performing data correction on the eliminated data based on the attribute constraints to obtain corrected data;

[0096] The cleaning submodule is used to repeatedly clean the blood relationship data and retain the target data creation time as a priority strategy using a priority queue algorithm to obtain processed data.

[0097] The aggregation module 3 is specifically used for:

[0098] The content and dimension of the processed data are extracted, the processed data are converted into data views according to the data, and the data views are aggregated and merged based on the content and dimension of the processed data to obtain aggregated data.

[0099] The management module 4 includes:

[0100] A first calculation submodule is used to calculate a first doubt value A based on the aggregated data:

[0101] A=(a1―a2―a3) / (a2+a3);

[0102] In the formula, a1 represents the registered area of ​​real estate, a2 and a3 represent the registered building area of ​​the first real estate tax source and the registered building area of ​​the second real estate tax source respectively;

[0103] A second calculation submodule, configured to calculate a second doubt value B based on the aggregated data;

[0104] B=(b1―b2) / b2;

[0105] In the formula, b1 represents the real estate rental data, and b2 represents the data on the basis of real estate tax calculation based on rent;

[0106] A third calculation submodule, configured to calculate a third doubt value C based on the aggregated data;

[0107] C = c1-c2-c3-c4;

[0108] In the formula, c1 represents the area of ​​the leased village land, c2 represents the total area of ​​the leased village land, c3 represents the taxable land area, and c4 represents the assessed taxable land area;

[0109] A management submodule is used to determine that if the first doubt point value is greater than a first preset value and the second doubt point value is greater than a second preset value and the third doubt point value is greater than a third preset value, then there is no doubt in the aggregated data; if the first doubt point value is not greater than the first preset value or the second doubt point value is not greater than the second preset value or the third doubt point value is not greater than the third preset value, then there is doubt in the aggregated data and output the doubt analysis result.

[0110] In some other embodiments of the present invention, the embodiments of the present invention provide the following technical solutions: a computer, comprising a memory 102, a processor 101, and a computer program stored in the memory 102 and executable on the processor 101; when the processor 101 executes the computer program, the real estate and land tax source data management method based on data lineage as described above is implemented.

[0111] Specifically, the processor 101 may include a central processing unit (CPU), or an application specific integrated circuit (ASIC), or may be configured to implement one or more integrated circuits of the embodiment of the present invention.

[0112] Among them, the memory 102 may include a large capacity memory for data or instructions. By way of example and not limitation, the memory 102 may include a hard disk drive (HDD), a floppy disk drive, a solid state drive (SSD), a flash memory, an optical disk, a magneto-optical disk, a magnetic tape, or a universal serial bus (USB) drive, or a combination of two or more of these. Where appropriate, the memory 102 may include a removable or non-removable (or fixed) medium. Where appropriate, the memory 102 may be inside or outside a data processing device. In a specific embodiment, the memory 102 is a non-volatile memory. In a specific embodiment, the memory 102 includes a read-only memory (ROM) and a random access memory (RAM). Where appropriate, the ROM may be a mask-programmed ROM, a programmable ROM (Programmable Read-Only Memory, PROM for short), an erasable PROM (ErasableProgrammable Read-Only Memory, EPROM for short), an electrically erasable PROM (Electrically ErasableProgrammable Read-Only Memory, EEPROM for short), an electrically alterable ROM (ElectricallyAlterable Read-Only Memory, EAROM for short) or a flash memory (FLASH) or a combination of two or more of these. Under appropriate circumstances, the RAM can be a static random access memory (SRAM) or a dynamic random access memory (DRAM), wherein the DRAM can be a fast page mode dynamic random access memory (FPMDRAM), an extended data output dynamic random access memory (EDODRAM), a synchronous dynamic random access memory (SDRAM), etc.

[0113] The memory 102 may be used to store or cache various data files that need to be processed and / or used for communication, as well as possible computer program instructions executed by the processor 101 .

[0114] The processor 101 implements the above-mentioned data lineage-based real estate and land tax source data management method by reading and executing computer program instructions stored in the memory 102.

[0115] In some embodiments, the computer may further include a communication interface 103 and a bus 100. Figure 3 As shown, the processor 101, the memory 102, and the communication interface 103 are connected via a bus 100 and communicate with each other.

[0116] The communication interface 103 is used to implement communication between the modules, devices, units and / or equipment in the embodiment of the present invention. The communication interface 103 can also implement data communication with other components such as: external devices, image / data acquisition equipment, databases, external storage, and image / data processing workstations.

[0117] The bus 100 includes hardware, software or both, and couples the components of the computer device to each other. The bus 100 includes but is not limited to at least one of the following: a data bus, an address bus, a control bus, an expansion bus, and a local bus. By way of example and not limitation, bus 100 may include Accelerated Graphics Port (AGP) or other graphics bus, Extended Industry Standard Architecture (EISA) bus, Front Side Bus (FSB), Hyper Transport (HT) interconnect, Industry Standard Architecture (ISA) bus, InfiniBand interconnect, Low Pin Count (LPC) bus, memory bus, Micro Channel Architecture (MCA) bus, Peripheral Component Interconnect (PCI) bus, PCI-Express (PCI-X) bus, Serial Advanced Technology Attachment (SATA) bus, Video Electronics Standards Association Local Bus (VLB) bus or other suitable bus or a combination of two or more of these. Where appropriate, bus 100 may include one or more buses. Although embodiments of the present invention describe and illustrate a particular bus, the present invention contemplates any suitable bus or interconnect.

[0118] The computer can execute the data lineage-based house and land tax source data management method of the present invention based on the acquisition of the data lineage-based house and land tax source management system, thereby realizing the data lineage-based house and land tax source management.

[0119] In some further embodiments of the present invention, in combination with the above-mentioned data lineage-based real estate tax source data management method, the embodiments of the present invention provide the following technical solutions: a storage medium having a computer program stored thereon, and the computer program implements the above-mentioned data lineage-based real estate tax source data management method when executed by a processor.

[0120] Those skilled in the art will appreciate that the logic and / or steps represented in the flowchart or otherwise described herein, for example, may be considered as an ordered list of executable instructions for implementing logical functions, and may be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For purposes of this specification, a "computer-readable medium" may be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0121] More specific examples of readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0122] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or a combination thereof: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0123] The technical features of the above-described embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0124] The above-mentioned embodiments only express several implementation methods of the present invention, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims.

Claims

1. A real estate and land tax source data management method based on data lineage, characterized in that: include: Obtain target house and land tax source data, and obtain data lineage relationship of the target house and land tax source data based on the association relationship to obtain lineage relationship data; Performing data processing on the blood relationship data to obtain processed data; Aggregating the processed data to obtain aggregated data; The aggregated data is subjected to doubt analysis and the doubt analysis result is output to realize the management of house and land tax source data.

2. The real estate and land tax source data management method based on data lineage according to claim 1 is characterized in that: The step of acquiring the data blood relationship of the target house and land tax source data based on the association relationship to obtain blood relationship data is specifically as follows: The processing flow data of the target house and land tax source data is extracted using the taxpayer identification number as the first association relationship identifier and the property tax source code and the land tax source code as the second association relationship identifier, and an analysis data table is extracted from the target house and land tax source data, and the blood relationship data is determined based on the processing flow and the analysis data table.

3. The real estate and land tax source data management method based on data lineage according to claim 2 is characterized in that: The processing flow data at least includes the processing history data, flow information data, and flow path data of the target house and land tax source data.

4. The real estate and land tax source data management method based on data lineage according to claim 2 is characterized in that: The analysis data tables at least include a tax source status analysis data table, an income analysis data table, a household data table, and a tax forecast data table.

5. The real estate and land tax source data management method based on data lineage according to claim 1 is characterized in that: The step of processing the blood relationship data to obtain processed data comprises: Identifying data containing missing values ​​in the blood relationship data, and removing the data containing missing values ​​from the blood relationship data to obtain removed data; Extracting attribute constraints from the blood relationship data, and performing data correction on the eliminated data based on the attribute constraints to obtain corrected data; The blood relationship data is repeatedly cleaned, and a priority queue algorithm is used to retain the target data creation time as a priority strategy to obtain processed data.

6. The real estate and land tax source data management method based on data lineage according to claim 1 is characterized in that: The step of aggregating the processed data to obtain aggregated data is specifically as follows: The content and dimension of the processed data are extracted, the processed data are converted into data views according to the data, and the data views are aggregated and merged based on the content and dimension of the processed data to obtain aggregated data.

7. The real estate and land tax source data management method based on data lineage according to claim 1 is characterized in that: The step of performing doubt analysis on the aggregated data and outputting the doubt analysis result comprises: Calculate the first doubt value A based on the aggregated data: <h2 style=";text-align:left;direction:ltr">A = (a1―a2―a3)<h2 style=";text-align:left;direction:ltr"> / <h2 style=";text-align:left;direction:ltr"> (a2+a3); In the formula, a1 represents the registered area of ​​real estate, a2 and a3 represent the registered building area of ​​the first real estate tax source and the registered building area of ​​the second real estate tax source respectively; Calculate a second doubt value B based on the aggregated data; <h2 style=";text-align:left;direction:ltr">B=(b1―b2)<h2 style=";text-align:left;direction:ltr"> / <h2 style=";text-align:left;direction:ltr"> b2; In the formula, b1 represents the real estate rental data, and b2 represents the data on the basis of the real estate tax calculation based on the rent; Calculate a third doubt value C based on the aggregated data; C = c1-c2-c3-c4; In the formula, c1 represents the area of ​​the leased village land, c2 represents the total area of ​​the leased village land, c3 represents the taxable land area, and c4 represents the assessed taxable land area; If the first doubt point value is greater than the first preset value and the second doubt point value is greater than the second preset value and the third doubt point value is greater than the third preset value, then there is no doubt in the aggregated data; if the first doubt point value is not greater than the first preset value or the second doubt point value is not greater than the second preset value or the third doubt point value is not greater than the third preset value, then there is doubt in the aggregated data, and the doubt analysis result is output.

8. A real estate and land tax source management system based on data lineage, characterized in that: include: An acquisition module is used to acquire target house and land tax source data, and acquire data blood relationship of the target house and land tax source data based on the association relationship to obtain blood relationship data; A processing module, used for processing the blood relationship data to obtain processed data; an aggregation module, used for aggregating the processed data to obtain aggregated data; The management module is used to perform doubt analysis on the aggregated data and output the doubt analysis results to achieve the management of house and land tax source data.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, it implements the real estate and land tax source data management method based on data lineage as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for managing house and land tax source data based on data lineage as described in any one of claims 1 to 7 is implemented.

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