Data rights confirmation method and system based on data tags

Abstract

The present invention provides a data rights confirmation method and system based on data tags, which belongs to the field of big data technology. By associating the original processed data of the data tags, analyzing the characteristics and features of the related processed data themselves, and calculating the contribution ratio of the data tags, the contribution ownership of the data tags has a reliable quantitative basis and measurement standard, so that the tag users or maintainers can measure the rights ownership of the tags according to the contribution of the tags and clarify the contribution components of the data tags.

Description

Technical Field

[0001] The present invention belongs to the field of big data technology, and specifically relates to a data rights confirmation method, system, electronic device and storage medium based on data tags. Background Art

[0002] Data tags, a form of data resource, are widely used in data processing, analysis, and modeling due to their targeted and interpretable nature for business analysis, such as online transaction scenarios in e-commerce and background checks in the financial and insurance sectors. The widespread use of data tags has led to a growing interest in their business value. The owners or maintainers of tags hope to convert their business value into tangible monetary benefits, thereby alleviating the labor and equipment costs associated with tag processing and maintenance. Therefore, data tag ownership verification and assessment are necessary.

[0003] Data resource rights confirmation is the process of authenticating the data resources involved in transactions to determine the true owner of the data resources (i.e., the data source). Data resource rights confirmation is a prerequisite for ensuring the security and reliability of data resources. Only data that has undergone data resource rights confirmation can clarify the true source of the data, ensure the security and reliability of data resources, and unleash the true value of data resources. Data labels are usually processed and calculated from multiple copies of basic data. Basic data has a certain contribution to data labels; however, basic data may come from different data owners, making it difficult to confirm the contribution of data labels, and thus making the process of converting the business value of data labels into monetary benefits more difficult to achieve.

[0004] In the existing technology, there are technical solutions for using blockchain technology to evaluate the value and confirm the ownership of data, but the disadvantages are as follows: 1) Because the use of blockchain technology to confirm the ownership of data requires reliance on blockchain technology encryption and digital authentication technology, it cannot be implemented for many data that are not on the chain; 2) There is no clear ownership analysis for data tags, a special data asset. The data can only be assigned to a certain entity in a one-size-fits-all manner based on digital authentication, and the contribution of data tags cannot be confirmed efficiently and accurately.

[0005] Therefore, there is an urgent need for a more accurate data ownership confirmation method based on data labels. Summary of the Invention

[0006] The present invention provides a data rights confirmation method, system, electronic device and storage medium based on data tags, so as to overcome at least one technical problem existing in the prior art.

[0007] To achieve the above-mentioned object, the present invention provides a data rights confirmation method based on data tags, the method comprising: obtaining metadata information and storage location information of the target data tag;

[0008] Recalling the blood relationship information of the target data tag according to the metadata information; wherein the blood relationship information includes all original data parameters associated with the target data tag;

[0009] Calling the storage location information and ownership of each original data associated with the target data tag according to the blood relationship information;

[0010] Recalling each original data associated with the target data tag according to storage location information corresponding to each original data associated with the target data tag, and forming associated data with each original data;

[0011] Determine the contribution ratio of each original data to the target data label based on the associated data using the preset characteristic factors and the weights corresponding to each characteristic factor;

[0012] According to the contribution ratio and the owner of each original data, the contribution ratio of the owner to the target data label is determined, and the target data label is confirmed according to the contribution ratio of the owner to the target data label.

[0013] Furthermore, preferably, the method of forming associated data from the target data tags and the respective original data includes:

[0014] Obtain the database name and data table name of each original data associated with the called target data tag;

[0015] Forming an associated combination of the target data label and each original data;

[0016] For each association combination, a new inner connection is constructed according to the inner connection conditions of the database and data table in the association combination in the SQL operation statement to obtain the associated data consisting of the target data label and each original data.

[0017] Furthermore, preferably, the method for determining the contribution ratio of each original data to the target data label based on the associated data using preset characteristic factors and weights corresponding to each characteristic factor includes:

[0018] According to the preset characteristic factors and the weights corresponding to the characteristic factors, the weights corresponding to the characteristic factors of the associated data are obtained;

[0019] Perform weighted summation on each characteristic factor of each associated data and the weight corresponding to each characteristic factor;

[0020] The weighted summation results corresponding to each associated data are normalized to determine the contribution ratio of each original data to the target data label.

[0021] Furthermore, preferably, according to the preset characteristic factors and the weights corresponding to the characteristic factors, the weights corresponding to the characteristic factors of the respective associated data are obtained;

[0022] Setting the characteristic factors and the weights corresponding to the characteristic factors; wherein the characteristic factors include saturation, information entropy and consistency;

[0023] Expose the API interface for obtaining the weights corresponding to each characteristic factor of the associated data through the JAVA program;

[0024] The weights corresponding to the characteristic factors of each associated data are obtained through the API interface.

[0025] Furthermore, preferably, the method of calling the blood relationship information of the target data tag according to the metadata information includes:

[0026] Expose the API interface for calling the blood relationship information of data tags through JAVA program;

[0027] The metadata information of the target data tag is used to call the blood relationship information of the target data tag through the API interface to obtain all the original data parameters associated with the target data tag; wherein, the metadata information of the target data tag includes the cluster, database, data table and field information where the target data tag is located.

[0028] Further, preferably, the method of calling each original data associated with the target data tag according to the storage location information corresponding to each original data associated with the target data tag includes:

[0029] Assembling an SQL operation statement for data reading according to the target data tag and the storage location information of each original data associated with the target data tag;

[0030] Pass the SQL operation statement as a parameter into the corresponding database interface;

[0031] Obtain the target data tag and detailed data of each original data associated with the target data tag in the corresponding database;

[0032] The acquired target data tags and detailed data of each original data associated with the target data tags are returned for contribution analysis.

[0033] In order to solve the above problems, the present invention also provides a data rights confirmation system based on data tags, comprising:

[0034] A metadata information acquisition unit, used to acquire metadata information and storage location information of the target data tag;

[0035] An associated data acquisition unit is configured to call the blood relationship information of the target data tag according to the metadata information; wherein the blood relationship information includes all raw data parameters associated with the target data tag; call the storage location information and the owner corresponding to each raw data associated with the target data tag according to the blood relationship information; call each raw data associated with the target data tag according to the storage location information corresponding to each raw data associated with the target data tag, and respectively form associated data with the target data tag and each raw data;

[0036] The contribution ratio acquisition unit is used to determine the contribution ratio of each original data to the target data label based on the associated data using the preset characteristic factors and the weights corresponding to each characteristic factor; determine the contribution ratio of the owner to the target data label according to the contribution ratio and the owner of each original data, and confirm the ownership of the target data label according to the contribution ratio of the owner to the target data label.

[0037] Furthermore, preferably, the associated data acquisition unit further includes a calling module, an associated combination module and an associated data module;

[0038] The calling module is used to obtain the database name and data table name of each original data associated with the called target data tag;

[0039] The association combination module is used to form an association combination between the target data label and each original data;

[0040] The associated data module is used to construct a new inner join for each associated combination according to the inner join conditions of the database and data table in the associated combination in the SQL operation statement, and obtain associated data consisting of the target data label and each original data.

[0041] In order to solve the above problem, the present invention further provides an electronic device, the electronic device comprising:

[0042] a memory storing at least one instruction; and

[0043] The processor executes the instructions stored in the memory to implement the steps in the above-mentioned data rights confirmation method based on data tags.

[0044] In order to solve the above problems, the present invention also provides a computer-readable storage medium, which stores at least one instruction, and the at least one instruction is executed by a processor in an electronic device to implement the above-mentioned data tag-based data rights confirmation method.

[0045] The present invention provides a data rights confirmation method, system, electronic device and storage medium based on data tags. By associating the original processed data of the data tags, analyzing the characteristics and features of the related processed data themselves, and calculating the contribution ratio of the data tags, the contribution ownership of the data tags has a reliable quantitative basis and measurement standard, so that the tag users or maintainers can measure the rights ownership of the tags according to the contribution of the tags and clarify the contribution components of the data tags. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. 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 any creative work.

[0047] Figure 1 A flowchart of a data rights confirmation method based on data tags provided by one embodiment of the present invention;

[0048] Figure 2 A schematic diagram illustrating the principle of a data rights confirmation method based on data tags provided in one embodiment of the present invention;

[0049] Figure 3 A schematic diagram of a data rights confirmation system based on data tags according to an embodiment of the present invention;

[0050] Figure 4 A schematic diagram of the internal structure of an electronic device for implementing a data rights confirmation method based on data tags according to an embodiment of the present invention;

[0051] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings and in conjunction with the embodiments. DETAILED DESCRIPTION

[0052] It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0053] Figure 1 This is a flow chart of a data rights confirmation method based on data tags provided by an embodiment of the present invention. The method can be executed by a system, which can be implemented by software and / or hardware.

[0054] The data rights confirmation method based on data tags of the present invention is mainly applicable to data transaction systems in scenarios such as finance or insurance that require a large amount of application data query and analysis. Data transaction system: a system used to provide a data transaction platform, which aims to promote data circulation, standardize data transaction behavior, maintain data transaction market order, protect the legitimate rights and interests of all parties involved in data transactions, and provide the whole society with complete data transaction, settlement, delivery and security services; at the same time, it meets some data processing functions. The composition architecture of the data transaction system may include a data transaction mall module, an operation management module, a data processing module, a data map module, a clearing and settlement module, etc., and may also include a payment interface, such as various bank channel interfaces, a third-party payment interface, etc. The data transaction system provides a data transaction platform, and can formulate various business rules that are adapted to each business in the data transaction platform as needed. When business data is collected, the business data can be globally and effectively audited and managed through the adapted business rules. This can achieve effective management of the entire process of each business in the data transaction platform, and improve business security and management strength. In addition, the business data that has been audited and managed can be converted into standard data elements according to the standard data specifications in the data transaction system, and added to the data map of the data transaction system. This can achieve standardized and unified management of business data, thereby achieving monitoring and management of business data from data collection to the entire life cycle of data transaction. The present invention analyzes the characteristics and features of the relevant processing data itself through the original processing data of the associated data tag, calculates and obtains the contribution ratio of the data tag, so that the contribution attribution of the data tag has a reliable quantitative basis and measurement standard, so that the tag user or maintenance party can measure the rights and interests of the tag according to the contribution of the tag, and clarify the contribution component of the data tag.

[0055] like Figure 1 As shown, in this embodiment, the invention is described in detail. The data ownership confirmation method based on data tags includes steps S110 to S150.

[0056] S110: Obtain metadata information and storage location information of the target data tag.

[0057] During implementation, data labeling not only categorizes data features but also pre-processes the data using at least one of the following methods: data warehouse processing, data desensitization, and data cleansing. Data warehouse processing can include ETL processing, which involves extracting, transforming, and loading data from the source to the destination. Data desensitization involves reshaping certain sensitive information using desensitization rules to reliably protect sensitive privacy data. In cases involving customer security data or commercially sensitive data, real data needs to be modified and provided for testing without violating the transaction rules of the data trading platform. For example, personal information such as ID numbers, mobile phone numbers, card numbers, and customer numbers, as well as financial limits, require data desensitization. Data cleansing can include re-examination and verification of the data, such as completing incomplete data, deleting duplicate data, and correcting erroneous data.

[0058] Specifically, the data tags are organized into a data tag library, which supports creating tags for data from multiple dimensions. The tags are then graded and categorized to form a tag library, which is then documented to form metadata in XML format. The tag library and metadata need to be dynamically updated.

[0059] Figure 2 Schematic diagram of the principle of a data rights confirmation method based on data tags provided by an embodiment of the present invention; Figure 2 As shown, the user initiates an analysis request to the data tag contribution analysis system of the present invention through the data gateway. In a specific implementation process, the data tag contribution analysis system 200 can be composed of a data storage module 210, a metadata management module 220, a contribution analysis module 230 and a feature & weight setting module 240.

[0060] Specifically, the data storage module 210 is usually a general-purpose big data storage component, such as Hive, PostgreSql, Mysql, etc., which is used to store the data label details to be analyzed and the original data associated therewith; it generally interacts with the contribution analysis module through the database interface interaction method. It should be noted that, under normal circumstances, the contribution analysis module will write SQL (Structured Query Language), send the SQL language as a parameter to the JDBC database interface, execute it in the big data storage module, read and return the detailed data to the contribution analysis module. The metadata management module 220 is usually a current general-purpose metadata governance / management component, such as Amundsen, Datahub, Atlas, etc., which is used to parse and provide the blood relationship information between the data label and its original processed data, as well as the storage information and ownership information of the corresponding original data, and interact with the contribution analysis module by providing an external interface. The contribution analysis module 230 is a component with big data processing functions (such as spark, clickhouse, etc.) and a corresponding interactive code module. The contribution analysis system analyzes the contribution ratios of stakeholders to the target data tag based on its related lineage information, detailed data, features to be analyzed, and weights. The Feature & Weight Setting Module 240, typically an application interaction module, provides a visual interface for users to set features for data tag analysis, such as saturation, information entropy, and consistency, as well as the corresponding calculation weights for each analysis feature. This module interacts with the Contribution Analysis Module via the system's internal interface.

[0061] S120. Call the blood relationship information of the target data tag according to the metadata information; wherein the blood relationship information includes all original data parameters associated with the target data tag; call the storage location information and the owner corresponding to each original data associated with the target data tag according to the blood relationship information.

[0062] In a specific implementation process, the method of calling the blood relationship information of the target data tag according to the metadata information includes: S121, the metadata management module exposes the Restful API interface through the JAVA program; S122, using the metadata information of the target data tag to call the blood relationship information of the target data tag through the Restful API interface to obtain all the original data parameters associated with the target data tag; wherein the metadata information of the target data tag includes the cluster, database, data table and field information where the target data tag is located.

[0063] An example explanation is as follows: based on the metadata information of the target data label (assuming it is label A), the interactive interface provided by the metadata management module is called to obtain the lineage information of the data label, thereby clarifying the original data associated with the label. It should be noted that the metadata management module exposes the Restful API interface to other modules through the JAVA program, and returns the lineage information of the label based on the metadata information of the input label A, such as the cluster, database, data table, field, etc. The lineage information will include the source of the processed data of label A. For example, if label A is processed by data B and data C through certain calculation logic, then the returned information will have a source parameter, and the parameter content is data B and data C, from which the original data associated with label A can be parsed.

[0064] S130 , calling each original data associated with the target data tag according to storage location information corresponding to each original data associated with the target data tag, and forming associated data with the target data tag and each original data.

[0065] The method of calling each original data associated with the target data tag according to the storage location information corresponding to each original data associated with the target data tag includes: S1311, assembling an SQL operation statement for data reading according to the target data tag and the storage location information of each original data associated with the target data tag; S1312, passing the SQL operation statement as a parameter to the corresponding database interface; S1313, obtaining the target data tag and the detailed data of each original data associated with the target data tag in the data storage module in the corresponding database; S1314, returning the obtained detailed data of the target data tag and the each original data associated with the target data tag to the contribution analysis module.

[0066] The method of forming associated data with the target data tag and each original data includes: S1321, obtaining the database name and data table name of each original data associated with the called target data tag; S1322, forming an associated combination with the target data tag and each original data; S1323, for each associated combination, constructing a new inner join according to the inner join conditions of the database and data table in the associated combination in the SQL operation statement, to obtain the associated data consisting of the target data tag and each original data.

[0067] An exemplary explanation is as follows: Based on the metadata information of the original data provided in the bloodline information, the interactive interface provided by the metadata management module is called to obtain the storage location information and ownership information of the original data, assuming that there is original data B (owned by b) and original data C (owned by c); (Explanation: The metadata management module exposes the Restful API interface to other modules through the JAVA program. Based on the metadata information of the input original data, such as the cluster, database, data table, etc., the interface returns the corresponding structured result, and the storage location and ownership information of the original data are provided in the result). Furthermore, based on the storage location information of label A, original data B, and original data C, the database interactive interface provided by the data storage module is called to read the detailed data of label A, original data B, and original data C. Specifically, the internal program of the contribution analysis module assembles data reading SQL, and passes the SQL as a parameter to the database interface to execute the reading of the detailed data of label A, original data B, and original data C in the data storage module, and returns it to the contribution analysis module.

[0068] S140 : Determine the contribution ratio of each original data to the target data label based on the associated data using preset characteristic factors and weights corresponding to each characteristic factor.

[0069] The method for determining the contribution ratio of each original data to the target data label based on associated data using preset characteristic factors and weights corresponding to each characteristic factor includes: S1411, obtaining the weight corresponding to each characteristic factor of each associated data according to the preset characteristic factors and the weights corresponding to each characteristic factor; S1412, performing weighted summation on each characteristic factor of each associated data and the weight corresponding to each characteristic factor; S1413, normalizing the weighted summation results corresponding to each associated data to determine the contribution ratio of each original data to the target data label.

[0070] Specifically, the Contribution Analysis Module retrieves the characteristic factors to be analyzed and the corresponding calculation weights from the Feature & Weight Setting Module via an internal application interface call. In other words, users interact with the front-end interface and set the features involved in the calculation and the corresponding calculation weights in the Feature & Weight Setting Module interface. Simultaneously, the Feature & Weight Setting Module exposes a RESTful API interface to other modules via a Java program. The Contribution Analysis Module calls this interface to retrieve the characteristic factors to be analyzed and the corresponding calculation weights (assuming saturation, information entropy, and consistency, with weights of 2:1:1, respectively) to prepare for the subsequent contribution analysis.

[0071] According to the preset characteristic factors and the weights corresponding to each characteristic factor, the method for obtaining the weights corresponding to each characteristic factor of each related data includes: S1421, using the characteristic & weight setting module to set the characteristic factors and the weights corresponding to each characteristic factor; wherein the characteristic factors include saturation, information entropy and consistency; S1422, the characteristic & weight setting module exposes the Restful API interface through the JAVA program; S1423, the contribution analysis module obtains the weights corresponding to each characteristic factor of each related data through the Restful API interface.

[0072] An exemplary description is as follows: the contribution analysis module assembles the calculation SQL code based on the library name and data table name of the read tag A, original data B and original data C, and uses the inner join method in SQL to calculate the associated data between tag A and original data B, which is associated data ab. The associated data between tag A and original data C is calculated in the same way, which is associated data ac. The calculation code (usually in SQL or Scala) is further executed to calculate the saturation, information entropy, and consistency of the associated data ab, assuming them to be 0.33, 0.68, and 0.54; the saturation, information entropy, and consistency of the associated data ac are calculated, assuming them to be 0.18, 0.01, and 0.21; the characteristic factors and calculation weights of the associated data ab and ac are weighted and summed, respectively: 0.33 × 2 + 0.68 × 1 + 0.54 × 1 = 1.88; and 0.18 × 2 + 0.01 × 1 + 0.21 × 1 = 0.58; the weighted sum of the two sets of associated data is then normalized to obtain the contribution ratios of the original data B and original data C to label A, which are 76.42% and 23.58%, respectively.

[0073] S150. Determine the contribution ratio of the owner to the target data label based on the contribution ratio and the owner of each original data, and confirm the ownership of the target data label based on the contribution ratio of the owner to the target data label.

[0074] Specifically, each piece of raw data has a corresponding owner, and the contribution ratio of raw data B and raw data C to label A is the contribution ratio of the owners of raw data B and raw data C to label A. For example, since raw data B belongs to owner b and raw data C belongs to owner c, the contribution ratios of owner b and owner c to label A are 76.42% and 23.58% respectively.

[0075] In general, users input metadata information and storage location information of target data labels into the system through interface interaction. Users set the features to be analyzed and the corresponding weights in the Feature & Weight Setting Module interface through interface interaction. The contribution analysis module obtains the blood relationship information of the data labels and the original data information associated in the blood relationship, such as storage information and data ownership information, in the metadata management module based on the metadata information. The contribution analysis module reads the corresponding detailed data from the data storage module through the storage information of the data labels and original data. The contribution analysis module calculates the associated detailed data of the data labels and the original data and calculates the corresponding feature values based on the selected features. The calculated feature values and the set weights are weighted and summed to calculate the final component values and normalized to generate the final contribution ratio; finally, the contribution ratio results are displayed.

[0076] In a specific embodiment, the contribution ratio of the attribution party to the target data label is displayed.

[0077] Specifically, the results of data label confirmation are displayed on the interactive interface. The display method is not limited to data, charts, or even videos. By confirming the ownership of data labels, it is possible to promote the innovative application of data in various industries, promote the rapid and healthy development of the data industry, and achieve win-win cooperation in the data industry. Then, based on functions such as data storage, data processing, data mining, and data analysis, a data transaction support platform is built to provide customized data transaction services and API services for governments and enterprises, providing comprehensive application support services for a large number of data transaction service developers. For example, based on data collection, cleaning, and processing, developers are provided with data modeling, mining, analysis, and presentation for specific application scenarios. Focusing on data transactions, the platform provides government departments and enterprises with asset management of the entire data life cycle, from data collection, processing, storage, analysis, sharing, openness, security, archiving, and destruction, to achieve data asset management and value-added.

[0078] The data rights confirmation method based on data tags proposed in the present invention can flexibly and conveniently analyze the contribution ratio of data tags. By analyzing the characteristics of the original data associated with the data tags, the data quality assessment is better integrated into the contribution assessment of the data tags, thereby reflecting that high-value, high-quality original data has a higher contribution to the derived data tags. In addition, the contribution ratio can better demonstrate and evaluate the ownership components of the tags for the users and maintainers of the data tags, providing a more reliable basis for the subsequent management of the data tags and the division of benefits, thereby further promoting the effective closed loop of data tag sharing → value benefits → continuous management.

[0079] In summary, the data rights confirmation method based on data tags of the present invention associates the original processed data of the data tags, analyzes the characteristics and features of the related processed data themselves, and calculates the contribution ratio of the data tags, so that the contribution ownership of the data tags has a reliable quantitative basis and measurement standard, so that the tag users or maintainers can measure the rights ownership of the tags according to the contribution of the tags and clarify the contribution components of the data tags.

[0080] like Figure 3 As shown, the present invention provides a data rights confirmation system 300 based on data tags, which can be installed in an electronic device. Depending on the functions implemented, the data rights confirmation system 300 based on data tags can include a metadata information acquisition unit 310, an associated data acquisition unit 320, and a contribution ratio acquisition unit 330. The unit described in the present invention can also be called a module, which refers to a series of computer program segments that can be executed by an electronic device processor and can perform fixed functions, which are stored in the memory of the electronic device.

[0081] In this embodiment, the functions of each module / unit are as follows:

[0082] The metadata information acquisition unit 310 is used to acquire metadata information and storage location information of the target data tag;

[0083] The associated data acquisition unit 320 is configured to retrieve the blood relationship information of the target data tag based on the metadata information; wherein the blood relationship information includes all raw data parameters associated with the target data tag; retrieve the storage location information and ownership of each raw data associated with the target data tag based on the blood relationship information; retrieve each raw data associated with the target data tag based on the storage location information corresponding to each raw data associated with the target data tag, and form associated data with the target data tag and each raw data;

[0084] The contribution ratio acquisition unit 330 is used to determine the contribution ratio of each original data to the target data label based on the associated data using the preset characteristic factors and the weights corresponding to each characteristic factor; determine the contribution ratio of the owner to the target data label according to the contribution ratio and the owner of each original data, and confirm the ownership of the target data label according to the contribution ratio of the owner to the target data label.

[0085] Furthermore, the associated data acquisition unit 320 further includes a calling module, an associated combination module and an associated data module;

[0086] The calling module is used to obtain the database name and data table name of each original data associated with the called target data tag;

[0087] The association combination module is used to form an association combination between the target data label and each original data;

[0088] The associated data module is used to construct a new inner join for each associated combination according to the inner join conditions of the database and data table in the associated combination in the SQL operation statement, and obtain associated data consisting of the target data label and each original data.

[0089] The data rights confirmation system 300 based on data tags of the present invention calculates the contribution ratio of the data tags by associating the original processed data of the data tags, analyzing the characteristics and features of the related processed data themselves, so that the contribution ownership of the data tags has a reliable quantitative basis and measurement standard, so that the tag users or maintainers can measure the rights ownership of the tags according to the contribution of the tags and clarify the contribution components of the data tags.

[0090] like Figure 4 As shown, the present invention provides an electronic device 4 for a data rights confirmation method based on data tags.

[0091] The electronic device 4 may include a processor 40, a memory 41, and a bus. It may also include a computer program stored in the memory 41 and executable on the processor 40, such as a data tag-based data ownership confirmation program 42. The memory 41 may also include both an internal storage unit of the data tag-based data ownership confirmation system and an external storage device. The memory 41 may be used not only to store application software and various types of data, such as the code for the data tag-based data ownership confirmation program, but also to temporarily store data that has been output or is about to be output.

[0092] Among them, the memory 41 includes at least one type of readable storage medium, and the readable storage medium includes a flash memory, a mobile hard disk, a multimedia card, a card-type memory (for example, SD or DX memory, etc.), a magnetic memory, a disk, an optical disk, etc. In some embodiments, the memory 41 can be an internal storage unit of the electronic device 4, such as a mobile hard disk of the electronic device 4. In other embodiments, the memory 41 can also be an external storage device of the electronic device 4, such as a plug-in mobile hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. equipped on the electronic device 4. Furthermore, the memory 41 can also include both an internal storage unit of the electronic device 4 and an external storage device. The memory 41 can not only be used to store application software and various types of data installed on the electronic device 4, such as the code of the data right confirmation program based on the data tag, but can also be used to temporarily store data that has been output or is to be output.

[0093] In some embodiments, the processor 40 may be composed of an integrated circuit, such as a single packaged integrated circuit, or a plurality of packaged integrated circuits with the same or different functions, including one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and a combination of various control chips. The processor 40 is the control core (Control Unit) of the electronic device, connecting the various components of the entire electronic device using various interfaces and lines, and executing the programs or modules stored in the memory 41 (such as data rights confirmation programs based on data tags, etc.), as well as calling the data stored in the memory 41, to perform various functions of the electronic device 4 and process data.

[0094] The bus may be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc. The bus is configured to enable connection and communication between the memory 41 and at least one processor 40, etc.

[0095] Figure 4 Only the electronic device with components is shown, and it can be understood by those skilled in the art that Figure 4 The structure shown does not constitute a limitation on the electronic device 4 , and may include fewer or more components than shown in the figure, or combine certain components, or arrange the components differently.

[0096] For example, although not shown, the electronic device 4 may further include a power source (such as a battery) for powering various components. Preferably, the power source may be logically connected to the at least one processor 40 via a power management system, thereby implementing functions such as charge management, discharge management, and power consumption management through the power management system. The power source may further include any components such as one or more DC or AC power sources, a recharging system, a power failure detection circuit, a power converter or inverter, and a power status indicator. The electronic device 4 may further include various sensors, Bluetooth modules, Wi-Fi modules, etc., which will not be described in detail here.

[0097] Furthermore, the electronic device 4 may also include a network interface. Optionally, the network interface may include a wired interface and / or a wireless interface (such as a WI-FI interface, a Bluetooth interface, etc.), which is usually used to establish a communication connection between the electronic device 4 and other electronic devices.

[0098] Optionally, the electronic device 4 may further include a user interface, which may be a display or an input unit (such as a keyboard). Optionally, the user interface may also be a standard wired interface or a wireless interface. Optionally, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, or an OLED (Organic Light-Emitting Diode) touchscreen. The display may also be appropriately referred to as a display screen or a display unit, which is used to display information processed in the electronic device 4 and to display a visual user interface.

[0099] It should be understood that the embodiment is for illustration only and the scope of the patent application is not limited to this structure.

[0100] The data tag-based data rights confirmation program 42 stored in the memory 41 in the electronic device 4 is a combination of multiple instructions. When running in the processor 40, it can achieve: obtaining metadata information and storage location information of the target data tag; calling the blood relationship information of the target data tag according to the metadata information; wherein the blood relationship information includes all original data parameters associated with the target data tag; calling the storage location information and the owner corresponding to each original data associated with the target data tag according to the blood relationship information; calling each original data associated with the target data tag according to the storage location information corresponding to each original data associated with the target data tag, and forming the target data tag and each original data into associated data respectively; based on the associated data, using preset characteristic factors and the weights corresponding to each characteristic factor, determining the contribution ratio of each original data to the target data tag; according to the contribution ratio and the owner of each original data, determining the contribution ratio of the owner to the target data tag, and confirming the target data tag according to the contribution ratio of the owner to the target data tag.

[0101] Specifically, the specific implementation method of the processor 40 for the above instructions can refer to Figure 1 The description of the relevant steps in the corresponding embodiment is not repeated here. It should be emphasized that in order to further ensure the privacy and security of the above-mentioned data rights confirmation procedure based on data tags, the above-mentioned database high-availability processing data is stored in the node of the blockchain where this server cluster is located.

[0102] Furthermore, if the modules / units integrated in the electronic device 4 are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. The computer-readable medium may include any entity or system capable of carrying the computer program code, a recording medium, a USB flash drive, a mobile hard drive, a magnetic disk, an optical disk, a computer memory, or a read-only memory (ROM).

[0103] An embodiment of the present invention also provides a computer-readable storage medium, which can be non-volatile or volatile, and stores a computer program. When the computer program is executed by a processor, it implements: obtaining metadata information and storage location information of the target data tag; calling the blood relationship information of the target data tag according to the metadata information; wherein the blood relationship information includes all original data parameters associated with the target data tag; calling the storage location information and the owner corresponding to each original data associated with the target data tag according to the blood relationship information; calling each original data associated with the target data tag according to the storage location information corresponding to each original data associated with the target data tag, and forming the target data tag and each original data into associated data respectively; based on the associated data, using preset characteristic factors and the weights corresponding to each characteristic factor, determining the contribution ratio of each original data to the target data tag; determining the contribution ratio of the owner to the target data tag according to the contribution ratio and the owner of each original data, and confirming the ownership of the target data tag according to the contribution ratio of the owner to the target data tag.

[0104] Specifically, the specific implementation method when the computer program is executed by the processor can refer to the description of the relevant steps in the data rights confirmation method based on data tags in the embodiment, which will not be repeated here.

[0105] In the several embodiments provided herein, it should be understood that the disclosed devices, systems, and methods may be implemented in other ways. For example, the system embodiments described above are merely illustrative. For example, the module division is merely a logical functional division, and actual implementation may employ other division methods.

[0106] The modules described as separate components may or may not be physically separate, and the components shown as modules may or may not be physical units, that is, they may be located in one place or distributed across multiple network elements. Some or all of the modules may be selected to achieve the purpose of the solution of this embodiment according to actual needs.

[0107] In addition, the functional modules in various embodiments of the present invention may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or hardware plus software functional modules.

[0108] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0109] Therefore, the embodiments should be considered in all respects as illustrative and non-restrictive, and the scope of the invention is defined by the appended claims rather than the foregoing description, and all changes that come within the meaning and range of equivalents of the claims are intended to be embraced therein. Any reference to a figure in a claim should not be construed as limiting the claim to which it relates.

[0110] Blockchain, as used in this article, refers to a novel application model for computer technologies such as distributed data storage, peer-to-peer transmission, consensus mechanisms, and encryption algorithms. Blockchain is essentially a decentralized database, a series of data blocks generated using cryptographic methods. Each block contains information about a batch of online transactions, used to verify the validity of this information (to prevent counterfeiting) and generate the next block. Blockchain can include the underlying blockchain platform, the platform product service layer, and the application service layer.

[0111] Furthermore, it is clear that the word "comprising" does not exclude other units or steps, and the singular does not exclude the plural. Multiple units or systems recited in a system claim may also be implemented by a single unit or system through software or hardware. Second-order terms are used to indicate names and do not imply any particular order.

[0112] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not limiting. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A data rights confirmation method based on data tags, characterized in that: Methods include: Obtain metadata information and storage location information of the target data tag; Recalling the blood relationship information of the target data tag according to the metadata information; wherein the blood relationship information includes all original data parameters associated with the target data tag; Calling the storage location information and ownership of each original data associated with the target data tag according to the blood relationship information; Recalling each original data associated with the target data tag according to storage location information corresponding to each original data associated with the target data tag, and forming associated data with each original data; Determine the contribution ratio of each original data to the target data label based on the associated data using preset characteristic factors and weights corresponding to each characteristic factor; According to the contribution ratio and the owner of each original data, the contribution ratio of the owner to the target data label is determined, and the target data label is confirmed according to the contribution ratio of the owner to the target data label.

2. The data rights confirmation method based on data tags according to claim 1 is characterized in that: The method of forming associated data from the target data tag and each original data includes: Obtain the database name and data table name of each original data associated with the called target data tag; Forming an associated combination of the target data label and each original data; For each association combination, a new inner connection is constructed according to the inner connection conditions of the database and data table in the association combination in the SQL operation statement to obtain the associated data consisting of the target data label and each original data.

3. The data rights confirmation method based on data tags according to claim 1 is characterized in that: The method of determining the contribution ratio of each original data to the target data label based on the associated data using the preset characteristic factors and the weights corresponding to the characteristic factors includes: According to the preset characteristic factors and the weights corresponding to the characteristic factors, the weights corresponding to the characteristic factors of the associated data are obtained; Perform weighted summation on each characteristic factor of each associated data and the weight corresponding to each characteristic factor; The weighted summation results corresponding to each associated data are normalized to determine the contribution ratio of each original data to the target data label.

4. The data rights confirmation method based on data tags according to claim 3 is characterized in that: According to the preset characteristic factors and the weights corresponding to the characteristic factors, the weights corresponding to the characteristic factors of the associated data are obtained; Setting the characteristic factors and the weights corresponding to the characteristic factors; wherein the characteristic factors include saturation, information entropy and consistency; Expose the API interface for obtaining the weights corresponding to each characteristic factor of the associated data through the JAVA program; The weights corresponding to the characteristic factors of each associated data are obtained through the API interface.

5. The data rights confirmation method based on data tags according to claim 1 is characterized in that: The method of calling the blood relationship information of the target data tag according to the metadata information includes: Expose the API interface for calling the blood relationship information of data tags through JAVA program; The metadata information of the target data tag is used to call the blood relationship information of the target data tag through the API interface to obtain all the original data parameters associated with the target data tag; wherein, the metadata information of the target data tag includes the cluster, database, data table and field information where the target data tag is located.

6. The data rights confirmation method based on data tags according to claim 1 is characterized in that: The method of calling each original data associated with the target data tag according to the storage location information corresponding to each original data associated with the target data tag includes: Assembling an SQL operation statement for data reading according to the target data tag and the storage location information of each original data associated with the target data tag; Pass the SQL operation statement as a parameter into the corresponding database interface; Obtain the target data tag and detailed data of each original data associated with the target data tag in the corresponding database; The acquired target data tags and detailed data of each original data associated with the target data tags are returned for contribution analysis.

7. A data rights confirmation system based on data tags, characterized by: include: A metadata information acquisition unit, used to acquire metadata information and storage location information of the target data tag; an associated data acquisition unit, configured to call the blood relationship information of the target data tag according to the metadata information; wherein the blood relationship information includes all raw data parameters associated with the target data tag; call the storage location information and the owner corresponding to each raw data associated with the target data tag according to the blood relationship information; call each raw data associated with the target data tag according to the storage location information corresponding to each raw data associated with the target data tag, and form associated data with the target data tag and each raw data; A contribution ratio acquisition unit is used to determine the contribution ratio of each original data to the target data label based on the associated data using preset characteristic factors and the weights corresponding to each characteristic factor; determine the contribution ratio of the owner to the target data label according to the contribution ratio and the owner of each original data; and confirm the ownership of the target data label according to the contribution ratio of the owner to the target data label.

8. The data rights confirmation system based on data tags according to claim 7 is characterized in that: The associated data acquisition unit further includes a calling module, an associated combination module and an associated data module; The calling module is used to obtain the database name and data table name of each original data associated with the called target data tag; The association combination module is used to form an association combination between the target data label and each original data; The associated data module is used to construct a new inner join for each associated combination according to the inner join conditions of the database and data table in the associated combination in the SQL operation statement, and obtain associated data consisting of the target data label and each original data.

9. An electronic device, characterized in that: The electronic device comprises: at least one processor; and, a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the steps in the data rights confirmation method based on data tags as described in any one of claims 1 to 6.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the data rights confirmation method based on data tags as described in any one of claims 1 to 6 is implemented.

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