Method and apparatus for merging metadata concepts

Abstract

An embodiment of the present invention discloses a method and device for merging metadata concepts. The method includes: obtaining the metadata to be tested and a comparison metadata set in a metadata management platform; wherein, the comparison metadata set includes at least one comparison metadata; matching the data of the blood relationship corresponding to the metadata to be tested with the data set of the comparison blood relationship corresponding to the comparison metadata set; wherein, the data set of the comparison blood relationship includes the data of the comparison blood relationship respectively corresponding to at least one comparison metadata; taking the comparison metadata corresponding to the successfully matched data of the comparison blood relationship as the target metadata, and performing a merging operation on the concept naming of the metadata to be tested and the concept naming of the target metadata. The embodiment of the present invention solves the problem that the existing metadata management platform cannot identify metadata with the same concept by performing matching of the data of the blood relationship and performing a merging operation on the concept naming of the successfully matched comparison metadata and the concept naming of the metadata to be tested.

Description

Technical Field

[0001] The embodiments of the present invention relate to the technical field of metadata, and in particular, to a method and device for merging metadata concepts. Background Art

[0002] Metadata is data that describes data and provides information support for business functions such as data quality management. In a hospital scenario, a hospital interfaces with multiple systems, and in different systems, there may be multiple description methods for metadata with the same concept or definition. When managing metadata or providing services to a third party, users need to understand the metadata with the same concept in different systems by themselves, and the cost of understanding deviation needs to be borne by the users themselves.

[0003] One of the main functions of the metadata management platform itself is to provide a unified centralized data service externally, and the existing technical routes cannot meet this requirement, so adjustment and optimization are needed. Summary of the Invention

[0004] The embodiments of the present invention provide a method and device for merging metadata concepts to solve the problem that the metadata management platform cannot recognize metadata with the same concept and optimize the management function of the metadata management platform.

[0005] In a first aspect, the embodiments of the present invention provide a method for merging metadata concepts, the method comprising:

[0006] Obtaining the metadata to be tested in the metadata management platform and a comparison metadata set; wherein, the comparison metadata set includes at least one comparison metadata;

[0007] Matching the blood relationship data corresponding to the metadata to be tested with the comparison blood relationship data set corresponding to the comparison metadata set; wherein, the comparison blood relationship data set includes comparison blood relationship data respectively corresponding to at least one comparison metadata;

[0008] Taking the comparison metadata corresponding to the successfully matched comparison blood relationship data as the target metadata, and performing a merging operation on the concept naming of the metadata to be tested and the concept naming of the target metadata.

[0009] In a second aspect, the embodiments of the present invention further provide a device for merging metadata concepts, the device comprising:

[0010] A module for obtaining the metadata to be tested, configured to obtain the metadata to be tested in the metadata management platform and a comparison metadata set; wherein, the comparison metadata set includes at least one comparison metadata;

[0011] A blood relationship data matching module to be measured, configured to match the blood relationship data to be measured corresponding to the metadata to be measured with the blood relationship data set for comparison corresponding to the comparison metadata set; wherein, the blood relationship data set for comparison includes blood relationship data for comparison corresponding to at least one piece of comparison metadata respectively;

[0012] A concept merging module, configured to use the comparison metadata corresponding to the successfully matched comparison blood relationship data as target metadata, and perform a merging operation on the concept naming of the metadata to be measured and the concept naming of the target metadata.

[0013] Thirdly, an embodiment of the present invention further provides an electronic device, which includes:

[0014] One or more processors;

[0015] A memory, configured to store one or more programs;

[0016] When the one or more programs are executed by the one or more processors, the one or more processors are caused to implement any of the above-mentioned metadata concept merging methods.

[0017] Fourthly, an embodiment of the present invention further provides a storage medium containing computer-executable instructions, and the computer-executable instructions are used to execute any of the above-mentioned metadata concept merging methods when executed by a computer processor.

[0018] In the embodiment of the present invention, by matching the blood relationship data to be measured of the metadata to be measured in the metadata management platform with the blood relationship data set for comparison corresponding to the comparison metadata set, and using the comparison metadata corresponding to the successfully matched comparison blood relationship data as target metadata, a merging operation is performed on the concept naming of the metadata to be measured and the concept naming of the target metadata, thereby solving the problem that the existing metadata management platform cannot identify metadata with the same concept, optimizing the management function of the metadata management platform, avoiding the understanding error caused by subjective judgment of users, and further improving the practicability of the metadata management platform. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 is a flowchart of a method for merging metadata concepts provided in Embodiment 1 of the present invention;

[0020] Figure 2 is a flowchart of a method for merging metadata concepts provided in Embodiment 2 of the present invention;

[0021] Figure 3 is a flowchart of a method for merging metadata concepts provided in Embodiment 3 of the present invention;

[0022] Figure 4It is a flowchart of a specific example of a method for merging metadata concepts provided in Embodiment 3 of the present invention;

[0023] Figure 5 It is a schematic diagram of a device for merging metadata concepts provided in Embodiment 4 of the present invention;

[0024] Figure 6 It is a schematic structural diagram of an electronic device provided in Embodiment 5 of the present invention. Detailed implementation manners

[0025] The present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It can be understood that the specific embodiments described herein are only used to explain the present invention, rather than limiting the present invention. Additionally, it should be noted that for the convenience of description, only the parts related to the present invention rather than all the structures are shown in the drawings.

[0026] Embodiment 1

[0027] Figure 1 It is a flowchart of a method for merging metadata concepts provided in Embodiment 1 of the present invention. This embodiment is applicable to the situation of judging the same concept for multiple metadata in a metadata management platform. This method can be executed by a device for merging metadata concepts, and this device can be implemented in a software and / or hardware manner. This device can be configured in a terminal device. Exemplarily, the terminal device can be an intelligent terminal such as a mobile terminal, a laptop computer, a desktop computer, and a tablet computer. The specific steps are as follows:

[0028] S110. Obtain the metadata to be tested and the comparison metadata set in the metadata management platform.

[0029] Metadata is data about data, which is a framework or a set of coding systems used to describe the basic characteristics and mutual relationships of digital information resources, especially network information resources, so as to ensure that these digital information can be recognized, decomposed, extracted, and analyzed and summarized by a computer machine network system. Metadata is one of the most important tools and methods for realizing data discovery, data conversion, data management, and data application.

[0030] Among them, the metadata management platform can be a platform for displaying and analyzing data assets in a certain application scenario, realizing a standardized, process-oriented, automated, and integrated data management system. Among them, exemplarily, the application scenario can be an enterprise or a hospital. Taking a hospital as an example, the characteristics of the data assets of a hospital are huge data volume, complex content, diverse forms, and scattered distribution. Embodiments of the present invention will be explained by taking the hospital scenario as an example.

[0031] Among them, exemplarily, the metadata to be tested can be the metadata newly collected by the metadata management platform or the metadata set by the metadata management platform during daily maintenance. In this embodiment, the comparison metadata set includes at least one comparison metadata.

[0032] S120. Match the blood relationship data corresponding to the metadata to be tested with the blood relationship data set corresponding to the comparison metadata set.

[0033] In this embodiment, the blood relationship data set corresponding to the comparison includes blood relationship data respectively corresponding to at least one comparison metadata.

[0034] In human society, blood relationship refers to the interpersonal relationship generated by reproduction. In the big data era, from the generation, processing, integration, circulation to the provision of applications of data, a relationship similar to blood relationship will naturally form among data. The data used to represent this kind of blood relationship among data is called blood relationship data. Among them, the blood relationship data can be used to represent the circulation information of a certain metadata in the metadata management platform. Specifically, the hierarchical structure of the blood relationship data includes data circulation levels, databases, data tables, and fields. Among them, the data circulation level is used to represent the circulation platform of the metadata in the metadata management platform, and the data circulation level will be specifically explained in the following embodiments. Exemplarily, the blood relationship data to be tested is data circulation level A - database 1 - data table 1 - data table 2 - data circulation level B - database 2 - data table 3.

[0035] Among them, specifically, it is judged whether there is blood relationship data in the comparison metadata set that is the same as the blood relationship data to be tested. If so, it means that the matching is successful, and the blood relationship data in the comparison metadata set that is the same as the blood relationship data to be tested is the successfully matched blood relationship data. Among them, specifically, the number of target metadata can be one or multiple. If not, it means that the matching fails.

[0036] For example, assume that the metadata to be measured is "primary diagnosis", and the comparison metadata set includes "first diagnosis", "primary diagnosis", "diagnosis (primary)", and "historical used drugs". Among them, the blood relationship data to be measured corresponding to "primary diagnosis" is data transfer level A - patient database - admission file data table - data transfer level B - surgery database - surgical instrument preparation data table. The comparison blood relationship data corresponding to "first diagnosis", "primary diagnosis", and "diagnosis (primary)" in the comparison blood relationship data set are respectively data transfer level A - patient database - admission file data table - data transfer level B - surgery database - surgical instrument preparation data table. The comparison blood relationship data corresponding to "historical used drugs" is data transfer level A - patient database - admission file data table. Specifically, although the comparison blood relationship data of "historical used drugs" is partially the same as the blood relationship data to be measured of "primary diagnosis", only when the blood relationship data to be measured is exactly the same as the comparison blood relationship data, it is considered that the blood relationship data to be measured and the comparison blood relationship data are successfully matched.

[0037] S130. Use the comparison metadata corresponding to the successfully matched comparison blood relationship data as the target metadata, and perform a merging operation on the concept naming of the metadata to be measured and the concept naming of the target metadata.

[0038] Specifically, the concept naming is the name of the metadata in the metadata management platform.

[0039] Taking the above example as an example, the metadata to be measured is "primary diagnosis". According to the matching result of the blood relationship data to be measured and the comparison blood relationship data set, the successfully matched comparison metadata includes "first diagnosis", "primary diagnosis", and "diagnosis (primary)". Among them, the concept naming of the metadata to be measured is "primary diagnosis", and the concept naming of the target metadata includes "first diagnosis", "primary diagnosis", and "diagnosis (primary)".

[0040] In one embodiment, optionally, before performing the merging operation on the concept naming of the metadata to be measured and the concept naming of the target metadata, it includes: generating a merging prompt message based on the concept naming of the metadata to be measured and the concept naming of the target metadata. When receiving the merging instruction input by the user based on the merging prompt message, perform the merging operation on the concept naming of the metadata to be measured and the concept naming of the target metadata. The advantage of this setting is that it reduces the merging error caused by misidentification and ensures the accuracy of the concept naming of the metadata.

[0041] In one embodiment, when the number of target metadata is one, a merging operation is performed on the concept naming of the metadata to be tested and the concept naming of the target metadata, including: changing the concept naming of the metadata to be tested to the concept naming of the target metadata, or changing the concept naming of the target metadata to the concept naming of the metadata to be tested, or generating a new concept naming based on the concept naming of the metadata to be tested and the concept naming of the target metadata, and using the new concept naming as the concept naming of the metadata to be tested and the target metadata. For example, assume that the concept naming of the metadata to be tested is "First Diagnosis" and the concept naming of the target metadata is "Primary Diagnosis". Then, the concept naming of the metadata to be tested and the target metadata after the merging operation are both "First Diagnosis", "Primary Diagnosis", or "Main Diagnosis", where "Main Diagnosis" is the generated new concept naming. Exemplarily, the new concept naming can be input by the user based on the merging prompt information.

[0042] In another embodiment, when the number of target metadata is multiple, a merging operation is performed on the concept naming of the metadata to be tested and the concept naming of the target metadata, including: using any one of the concept namings corresponding to the metadata to be tested and at least two target metadata as the target concept naming, and changing the concept naming of the other metadata except the metadata corresponding to the target concept naming to the target concept naming, or generating a new concept naming based on the concept naming of the metadata to be tested and the concept naming of the target metadata, and using the new concept naming as the concept naming of the metadata to be tested and the target metadata. For example, assume that the concept naming of the metadata to be tested is "First Diagnosis" and the concept namings of the target metadata include "Primary Diagnosis" and "Diagnosis (Main)". Then, the concept naming of the metadata to be tested and the target metadata after the merging operation are both "First Diagnosis", "Primary Diagnosis", "Diagnosis (Main)", or "Main Diagnosis", where "Main Diagnosis" is the generated new concept naming. Exemplarily, the new concept naming can be input by the user based on the merging prompt information.

[0043] Based on the above embodiments, optionally, after performing the merging operation on the concept naming of the metadata to be tested and the concept naming of the target metadata, the method further includes: merging the data corresponding to the metadata to be tested and the data corresponding to the target metadata. The advantage of this setting is that it realizes the normalization and collation of metadata data from multiple to one, reduces data redundancy, and when providing application services externally, a unified usage interface can be adopted, meeting the data collection requirements of the business side and improving the application efficiency of the metadata.

[0044] The technical solution of this embodiment matches the to-be-tested lineage data of the to-be-tested metadata in the metadata management platform with the corresponding comparison lineage data set of the comparison metadata set, and uses the comparison metadata corresponding to the successfully matched comparison lineage data as the target metadata, and performs a merging operation on the concept naming of the to-be-tested metadata and the concept naming of the target metadata, which solves the problem that the existing metadata management platform cannot identify metadata with the same concept, optimizes the management function of the metadata management platform, avoids the understanding error caused by the user's subjective judgment, and thus improves the practicality of the metadata management platform.

[0045] Embodiment 2

[0046] Figure 2 FIG. is a flowchart of a method for merging metadata concepts provided in Embodiment 2 of the present invention. The technical solution of this embodiment is a further refinement based on the above embodiment. Optionally, the metadata management platform includes at least one data flow level. Correspondingly, the obtaining of the to-be-tested metadata and the comparison metadata set in the metadata management platform includes: for each data flow level in the metadata management platform, obtaining the to-be-tested metadata and the comparison metadata set corresponding to the data flow level; wherein, the data flow level is used to represent the transfer platform of the metadata in the metadata management platform.

[0047] The specific implementation steps of this embodiment include:

[0048] S210. For each data flow level in the metadata management platform, obtain the to-be-tested metadata and the comparison metadata set corresponding to the data flow level.

[0049] In this embodiment, the data flow level is used to represent the transfer platform of the metadata in the metadata management platform. Specifically, the metadata management platform provides at least one data flow level for performing management operations on the metadata in the platform. Exemplarily, the management operations can be querying, storing, calculating, and so on. In one embodiment, optionally, the data flow level includes at least one of a collection adaptation layer, a storage directory layer, a derived view layer, a business view layer, a product view layer, and an index view layer.

[0050] Specifically, the acquisition adaptation layer is used to acquire metadata from at least one source database included in the metadata management platform. Exemplarily, the source database may be a database of a Hospital Information System (HIS), a database of a Laboratory Information System (LIS), a database of a Picture Archiving and Communication System (PACS), a database of a Radiology Information System (RIS), and so on.

[0051] Specifically, the storage directory layer is used to store the metadata acquired by the acquisition adaptation layer. In one embodiment, optionally, the storage directory layer includes a data lake layer, a data center layer, a data domain layer, and a data mart layer. Among them, the metadata in the data center layer, the data domain layer, and the data mart all originate from the previous layer. Specifically, the Data Lake (DL) layer is used to store all the metadata acquired by the acquisition adaptation layer; the Data Center (DC) layer is used to store the data that may flow to the next data flow level extracted from the DL layer; the Data Domain (DOMAIN) layer contains multiple domains, and each domain stores the metadata related to that domain. Exemplarily, the domain may be a clinical data center, an operation data center, a scientific research data center, and so on; the Data Mart (DATAMARKTET) layer belongs to the derivative layer and can be used to store the new metadata generated by the metadata management platform.

[0052] Specifically, the derivative view layer can be used to represent the transfer platform of the metadata of the derivative dimension. The metadata of the derivative dimension in the derivative view layer can be used to describe the new metadata generated based on the original metadata. Exemplarily, the original metadata includes the hospitalization expenses on the first day and the hospitalization expenses on the second day, and the metadata included in the derivative view layer may be the total hospitalization expenses, where the total hospitalization expenses are the new metadata obtained by adding the hospitalization expenses on the first day and the hospitalization expenses on the second day.

[0053] Specifically, the business view layer is used to represent the transfer platform of the metadata of the business dimension. The metadata of the business dimension in the business view layer may be at least one metadata aggregated based on business requirements. Exemplarily, if the business requirement is a patient file, the metadata in the business view layer may include the patient's name, the patient's gender, the patient's medical insurance account, and so on. If the business requirement is medical research, the metadata in the business view layer may include the diagnosis result, the recovery situation, the treatment method, and the patient's age, and so on.

[0054] Specifically, the product view layer can be used as a metadata transfer platform for the product dimension. The metadata of the product dimension in the product view layer can be metadata defined by a third-party application. Exemplarily, if the third-party application is a hospital system, the metadata in the product view layer may include patient name, patient medical insurance account, patient diagnosis result, treatment cost, and so on. If the third-party application is an Internet enterprise system, the metadata in the product view layer may include device name, network security series, firewall series, developers, operators, and so on.

[0055] Specifically, the metric view layer can be used as a metadata transfer platform for the metric dimension. The metadata of the metric dimension in the metric view layer can be metadata defined for analysis purposes such as accounting and treatment. Exemplarily, the metadata in the metric view layer may include medical cost, medical quality, medical record quality, outpatient income, and so on.

[0056] In one embodiment, optionally, obtaining the metadata to be tested and the comparison metadata set corresponding to the data transfer level includes: when a metadata addition instruction is detected, using the metadata corresponding to the metadata addition instruction as the metadata to be tested; and obtaining the comparison metadata set in the database based on the level identifier corresponding to the data transfer level.

[0057] Specifically, in the current data transfer level, when a new piece of metadata flows to the current data transfer level, a metadata addition instruction corresponding to the metadata will be generated. By parsing the SQL statement corresponding to the metadata to be tested, the blood relationship data corresponding to the metadata to be tested and the current data process level can be obtained. Exemplarily, if the metadata to be tested flows from Table 1 in data transfer level A to Table 2 in data transfer level B, then in data transfer level B, the blood relationship data of the metadata to be tested is "data transfer level A - Table 1 - data transfer level B - Table 2". When the metadata to be tested continues to flow to Table 3 in data transfer level C, then in data transfer level C, the blood relationship data of the metadata to be tested is "data transfer level A - Table 1 - data transfer level B - Table 2 - data transfer level C - Table 3".

[0058] Specifically, when metadata is circulated in the metadata management platform, each time the metadata enters a data circulation level, a level identifier corresponding to the current data circulation level will be recorded. The level identifier can be at least one of numbers, capital letters, special characters, lowercase letters, and words. The specific setting of the level identifier is not limited here. Exemplarily, the level identifiers include collection adaptation, DL, DC, DOMAIN, DATAMARKTET, derived view, business view, product view, and metric view. Suppose the metadata enters the derived view layer and the product view layer in sequence. Then, the level identifiers of the metadata recorded in the database include "derived view" and "product view". Suppose the metadata to be tested is in the product view layer. Then, the above metadata is added to the comparison metadata set. Suppose the metadata to be tested is in the metric view layer. Then, the above metadata is not included in the comparison metadata set.

[0059] In one embodiment, optionally, obtaining the metadata to be tested and the comparison metadata set corresponding to the data circulation level includes: when it is detected that the current time meets the preset time point, based on the level identifier corresponding to the data circulation level, obtaining at least two metadata in the database; for each metadata, using the metadata as the metadata to be tested and adding the metadata other than the metadata to be tested to the comparison metadata set.

[0060] This embodiment can periodically perform the same-concept detection on the metadata in the data circulation level. Specifically, obtaining at least two metadata corresponding to the current data circulation level, using each metadata as the metadata to be tested in sequence, and using the metadata other than the metadata to be tested as the comparison metadata.

[0061] S220. Match the to-be-tested blood relationship data corresponding to the to-be-tested metadata with the comparison blood relationship data set corresponding to the comparison metadata set.

[0062] Specifically, parsing the SQL statement of the database to obtain the result set returned by the database. Each column in the result set may come from different tables, and these tables depend on other tables. Specifically, the result set includes the to-be-tested blood relationship data and at least one comparison blood relationship data. Exemplarily, the types of databases include mysql databases and / or greenPlum databases.

[0063] Among them, specifically, the blood relationship data in the result set is the blood relationship data corresponding to the current data transfer level. Exemplarily, the blood relationship data of metadata A in the metadata management platform is data transfer level A - database 1 - data table 1 - data table 2 - data transfer level B - database 2 - data table 3. If the current data transfer level is data transfer level A, the blood relationship data of metadata A used for matching is data transfer level A - database 1 - data table 1 - data table 2. If the current data transfer level is data transfer level B, the blood relationship data of metadata A used for matching is data transfer level A - database 1 - data table 1 - data table 2 - data transfer level B - database 2 - data table 3.

[0064] S230. Use the comparison metadata corresponding to the successfully matched comparison blood relationship data as the target metadata, and perform a merging operation on the concept naming of the metadata to be tested and the concept naming of the target metadata.

[0065] The technical solution of this embodiment, by obtaining the metadata to be tested and the comparison metadata set corresponding to each data transfer level in the metadata management platform, and respectively performing the operations of blood relationship data matching and concept merging in each data transfer level, solves the problem of excessive amount of comparison metadata, reduces the collection range of comparison metadata, and improves the efficiency of metadata concept merging while ensuring the comprehensiveness of the matching range.

[0066] Embodiment III

[0067] Figure 3 FIG. is a flowchart of a method for merging metadata concepts provided in Embodiment III of the present invention. The technical solution of this embodiment is a further refinement based on the above embodiments. Optionally, the method further includes: if the blood relationship data to be tested fails to match the comparison blood relationship data set, then match the value range data to be tested corresponding to the metadata to be tested with the comparison value range data set corresponding to the comparison metadata set; wherein, the comparison value range data set includes comparison value range data respectively corresponding to at least one comparison metadata; use the comparison metadata corresponding to the successfully matched comparison value range data as the target metadata, and perform a merging operation on the concept naming of the metadata to be tested and the concept naming of the target metadata.

[0068] The specific implementation steps of this embodiment include:

[0069] S310. Obtain the metadata to be tested and the comparison metadata set in the metadata management platform.

[0070] S320. Match the blood relationship data to be tested corresponding to the metadata to be tested with the comparison blood relationship data set corresponding to the comparison metadata set.

[0071] S330. Determine whether the matching result is a successful match. If so, execute S340; if not, execute S350.

[0072] Specifically, if the comparison blood relationship data set contains comparison blood relationship data that is the same as the to-be-tested blood relationship data, the matching result is a successful match; if the comparison blood relationship data set does not contain comparison blood relationship data that is the same as the to-be-tested blood relationship data, the matching result is a failed match. In one embodiment, the to-be-tested blood relationship data is empty, that is, there is no to-be-tested blood relationship data in the to-be-tested metadata.

[0073] S340. Use the comparison metadata corresponding to the successfully matched comparison blood relationship data as the target metadata, and perform a merging operation on the concept naming of the to-be-tested metadata and the concept naming of the target metadata.

[0074] S350. Match the to-be-tested value range data corresponding to the to-be-tested metadata with the comparison value range data set corresponding to the comparison metadata set.

[0075] In this embodiment, the comparison value range data set contains comparison value range data corresponding to at least one comparison metadata respectively. Specifically, the value range data can be used to represent the value range of the metadata. Exemplarily, when the metadata is "age", the value range data can be 0 - 100; when the metadata is "gender", the value range data is "male, female, and unknown".

[0076] Based on the above embodiment, optionally, the type of the comparison value range data is a dictionary - type value range or a formatted text value range. Correspondingly, the method further includes: for each comparison metadata, when the type of the comparison value range data of the comparison metadata is a dictionary - type value range, obtain the comparison value range data corresponding to the comparison metadata in the foreign key relationship table corresponding to the database where the comparison metadata is located; when the type of the comparison value range data of the comparison metadata is a formatted text value range, obtain the comparison value range data corresponding to the comparison metadata in the database.

[0077] Although a list (data row or data column) can store data, when a user needs to know the value range of the list, they need to know all the elements in the list. Therefore, in order to accurately index the value range of the data, a dictionary data type is used to store the value range data. Specifically, the dictionary - type value range can be used to describe the value range data with a clear value range. Exemplarily, the comparison metadata corresponding to the dictionary - type value range can be "gender", "age", "weight", etc. Specifically, the foreign key relationship table can be used to represent the associated data table associated with the comparison metadata in the database, and the comparison value range data of the comparison metadata is stored in the foreign key relationship table.

[0078] Among them, specifically, the formatted text value range can be used to describe value range data for which there is no clear value range. That is to say, the comparison value range data of the formatted text value range cannot be classified and described by a finite set of parameter values. Exemplarily, the comparison metadata corresponding to the formatted text value range can be "name", "ID number", "medical insurance account", etc. Specifically, the comparison value range data is directly obtained by reading the data columns or data rows in the database corresponding to the comparison metadata.

[0079] It should be noted that the above process describes the steps for obtaining the comparison value range data. This obtaining step is also applicable to obtaining the value range data to be measured. The specific implementation is similar to the above process and will not be elaborated here.

[0080] Based on the above embodiments, optionally, before matching the value range data to be measured corresponding to the metadata to be measured with the comparison value range data set corresponding to the comparison metadata set, the method further includes: obtaining a whitelist data set corresponding to the metadata to be measured; where the whitelist data set includes at least one metadata, and the value range data corresponding to each metadata is the same as the value range data to be measured, but the conceptual naming of each metadata is different from the value range data to be measured; deleting the comparison metadata in the comparison metadata set that is the same as the whitelist data set to obtain a filtered comparison metadata set.

[0081] Among them, specifically, the whitelist data set includes comparison metadata with the same comparison value range data as the value range data to be measured, but this comparison metadata and the metadata to be measured do not belong to the same concept. For example, assume that the metadata to be measured is "diagnosis", and the comparison metadata set includes "discharge diagnosis" and "admission diagnosis". The value range data of these three metadata is the same, but they belong to different concept metadata.

[0082] Among them, specifically, the whitelist data set can be pre-set by the user.

[0083] In one embodiment, optionally, obtaining a whitelist data set corresponding to the metadata to be measured includes: obtaining the whitelist data set corresponding to the metadata to be measured in the whitelist data list, where the whitelist data list includes at least one metadata and the whitelist data set corresponding to each metadata respectively. Exemplarily, the whitelist data list includes metadata A, metadata B, and the whitelist data set A and whitelist data set B corresponding to metadata A and metadata B respectively. Assume that the metadata to be measured is metadata A, then the whitelist data set is whitelist data set A.

[0084] In another embodiment, optionally, obtaining a whitelist data set corresponding to the metadata to be measured includes: obtaining the whitelist data set input by the user based on the metadata to be measured.

[0085] Based on the above embodiments, optionally, before matching the data in the value range corresponding to the metadata to be tested with the data in the value range corresponding to the comparison metadata set, the method further includes: comparing the comparison metadata set with at least one preset whitelist data set respectively. For each preset whitelist data set, if there are at least two comparison metadata in the comparison metadata set that are the same as the preset whitelist data set, then delete the at least two identical comparison metadata from the comparison metadata set; wherein, the preset whitelist data set includes at least two metadata with the same data in the value range but different concept names.

[0086] For example, assume that the preset whitelist data set is [diagnosis of discharge diagnosis of admission]. If the comparison metadata set is [name diagnosis of discharge diagnosis of admission], then delete "diagnosis of discharge" and "diagnosis of admission" from the comparison metadata set, and the resulting comparison metadata set is [name]. If the comparison metadata set is [name diagnosis of admission], it means that there are no at least two comparison metadata in the comparison metadata set with the same data in the value range but different concept names, and the resulting comparison metadata set remains [name diagnosis of admission].

[0087] Due to the complexity and diversity of medical data, it is easy to have metadata with the same data in the value range but different concept names. If no whitelist is set and concept merging is performed only based on the matching results of the data in the value range, it is very easy to merge metadata with different concepts together, resulting in data chaos and large errors in concept understanding. The advantage of setting it like this is to ensure the accuracy of concept merging of metadata.

[0088] S360. Use the comparison metadata corresponding to the successfully matched comparison data in the value range as the target metadata, and perform a merging operation on the concept name of the metadata to be tested and the concept name of the target metadata.

[0089] The technical solution of this embodiment, when the matching of the blood relationship data to be tested and the comparison blood relationship fails, continues to match the data in the value range corresponding to the metadata to be tested with the data in the value range corresponding to the comparison metadata set, and uses the comparison metadata corresponding to the successfully matched comparison data in the value range as the target metadata, and performs a merging operation on the concept name of the metadata to be tested and the concept name of the target metadata, solves the problem of low accuracy of concept merging with a single matching condition, finds as many metadata with the same concept name as possible and merges their concepts, improves the accuracy of concept merging of metadata, and further optimizes the management function of the metadata management platform.

[0090] Figure 4It is a flowchart of a specific example of a method for merging metadata concepts provided in Embodiment 3 of the present invention. Specifically, taking the scenario where a metadata addition instruction is detected as an example, at least two metadata corresponding to the data flow hierarchy identifier are obtained, and the metadata to be tested and the comparison metadata set are determined. Specifically, the metadata corresponding to the metadata addition instruction among the at least two metadata is used as the metadata to be tested, and the metadata other than the metadata to be tested constitutes the comparison metadata set. Taking the scenario where it is detected that the current time meets the preset time point as an example, at least two metadata corresponding to the data flow hierarchy identifier are obtained, and the metadata to be tested and the comparison metadata set are determined. Specifically, any one of the at least two metadata is used as the metadata to be tested, and the metadata other than the metadata to be tested constitutes the comparison metadata set.

[0091] Match the to-be-tested blood relationship data of the metadata to be tested with the corresponding comparison blood relationship data set of the comparison metadata set. If there is comparison blood relationship data in the comparison blood relationship data set that is the same as the to-be-tested blood relationship data, it is considered a successful match, and a merging operation is performed on the concept naming of the metadata to be tested and the concept naming of the comparison metadata with a successful match. If there is no comparison blood relationship data in the comparison blood relationship data set that is the same as the to-be-tested blood relationship data, it is considered a failed match, and the to-be-tested value range data of the metadata to be tested is matched with the corresponding comparison value range data set of the comparison metadata set. If the comparison value range data set contains comparison value range data that is the same as the to-be-tested value range data, it is considered a successful match, and a merging operation is performed on the concept naming of the metadata to be tested and the concept naming of the comparison metadata with a successful match. If there is no comparison value range data in the comparison value range data set that is the same as the to-be-tested blood relationship data, it is considered a failed match, and the concept naming of the metadata to be tested is retained.

[0092] In the scenario where a metadata addition instruction is detected, after completing the above matching process of the metadata to be tested, it is considered that the metadata corresponding to the current data flow hierarchy has been matched, and the hierarchy identifier of the next data flow hierarchy is obtained, and the step of obtaining at least two metadata corresponding to the hierarchy identifier of the data flow hierarchy is repeatedly executed. In the scenario where it is detected that the current time meets the preset time point, after completing the above matching process of the metadata to be tested, it is judged whether the number of metadata that have not been used as the metadata to be tested is 1. If so, it is considered that the metadata corresponding to the current data flow hierarchy has been matched, and the hierarchy identifier of the next data flow hierarchy is obtained, and the step of obtaining at least two metadata corresponding to the hierarchy identifier of the data flow hierarchy is repeatedly executed. If not, it is considered that the matching of the metadata corresponding to the current data flow hierarchy is not completed, and the steps of determining the metadata to be tested and the comparison metadata set are repeatedly executed. Specifically, the next metadata is used as the metadata to be tested, and the metadata other than the metadata to be tested constitutes the comparison metadata set.

[0093] The advantage of such a setting is that since the blood relationship data can uniquely mark the metadata, although the value domain data can also uniquely mark the metadata, the uniqueness accuracy of the value domain data is lower than that of the blood relationship data. Therefore, the technical solution of this embodiment first performs the matching of the blood relationship data. On the one hand, it can ensure that the compared metadata obtained by the matching and the metadata to be tested are metadata of the same concept, improving the accuracy of the concept merging result. On the other hand, since the data transfer hierarchy is included in the blood relationship data and the data transfer hierarchy of the metadata has been obtained during the parsing of the blood relationship data, during the matching of the value domain data, the value domain data of the metadata to be tested and the compared metadata set at the same data transfer hierarchy can be directly matched, without having to re-execute the step of parsing the blood relationship data of the metadata to obtain the data transfer hierarchy, thereby improving the efficiency of the metadata concept merging.

[0094] Embodiment 4

[0095] Figure 5 FIG. 7 is a schematic diagram of an apparatus for merging metadata concepts provided in Embodiment 4 of the present invention. This embodiment is applicable to the situation of judging whether multiple metadata in a metadata management platform are of the same concept. The apparatus can be implemented in a software and / or hardware manner and can be configured in a terminal device. The apparatus for merging metadata concepts includes: a metadata-to-be-tested acquisition module 410, a blood relationship data matching module 420 for the metadata-to-be-tested, and a concept merging module 430.

[0096] Among them, the metadata-to-be-tested acquisition module 410 is configured to acquire the metadata-to-be-tested in the metadata management platform and a set of compared metadata; wherein, the set of compared metadata includes at least one piece of compared metadata;

[0097] The blood relationship data matching module 420 for the metadata-to-be-tested is configured to match the blood relationship data corresponding to the metadata-to-be-tested with the set of blood relationship data corresponding to the set of compared metadata; wherein, the set of blood relationship data corresponding to the set of compared metadata includes blood relationship data respectively corresponding to at least one piece of compared metadata;

[0098] The concept merging module 430 is configured to use the compared metadata corresponding to the successfully matched blood relationship data as the target metadata and perform a merging operation on the concept naming of the metadata-to-be-tested and the concept naming of the target metadata.

[0099] In the technical solution of this embodiment, by matching the to-be-tested lineage data of the to-be-tested metadata in the metadata management platform with the corresponding comparison lineage data set of the comparison metadata set, taking the comparison metadata corresponding to the successfully matched comparison lineage data as the target metadata, and performing a merging operation on the concept naming of the to-be-tested metadata and the concept naming of the target metadata, the problem that the existing metadata management platform cannot identify metadata with the same concept is solved, the management function of the metadata management platform is optimized, the understanding error caused by subjective judgment of users is avoided, and thus the practicability of the metadata management platform is improved.

[0100] Based on the above technical solution, optionally, the metadata management platform includes at least one data transfer level. Correspondingly, the to-be-tested metadata acquisition module 410 includes:

[0101] A to-be-tested metadata acquisition unit, configured to, for each data transfer level in the metadata management platform, acquire the to-be-tested metadata corresponding to the data transfer level and the comparison metadata set; wherein, the data transfer level is used to represent the transfer platform of the metadata in the metadata management platform.

[0102] Based on the above technical solution, optionally, the to-be-tested metadata acquisition unit includes:

[0103] A first to-be-tested metadata acquisition subunit, configured to, when detecting a metadata addition instruction, take the metadata corresponding to the metadata addition instruction as the to-be-tested metadata; and acquire the comparison metadata set in the database based on the level identifier corresponding to the data transfer level.

[0104] Based on the above technical solution, optionally, the to-be-tested metadata acquisition unit includes:

[0105] A second to-be-tested metadata acquisition subunit, configured to, when detecting that the current time meets a preset time point, acquire at least two metadata in the database based on the level identifier corresponding to the data transfer level; for each metadata, take the metadata as the to-be-tested metadata, and add the metadata other than the to-be-tested metadata to the comparison metadata set.

[0106] Based on the above technical solution, optionally, the device further includes:

[0107] A to-be-tested value range data matching module, configured to, if the to-be-tested lineage data fails to match the comparison lineage data set, match the to-be-tested value range data corresponding to the to-be-tested metadata with the comparison value range data set corresponding to the comparison metadata set; wherein, the comparison value range data set includes comparison value range data respectively corresponding to at least one comparison metadata;

[0108] Use the comparison metadata corresponding to the successfully matched comparison value range data as the target metadata, and perform a merging operation on the concept naming of the metadata to be measured and the concept naming of the target metadata.

[0109] Based on the above technical solution, optionally, the type of the comparison value range data is a dictionary type value range or a formatted text value range. Correspondingly, the device further includes:

[0110] A comparison value range data acquisition module, configured to, for each piece of comparison metadata, when the type of the comparison value range data of the comparison metadata is a dictionary type value range, acquire the comparison value range data corresponding to the comparison metadata in the foreign key relationship table corresponding to the database where the comparison metadata is located;

[0111] When the type of the comparison value range data of the comparison metadata is a formatted text value range, acquire the comparison value range data corresponding to the comparison metadata in the database.

[0112] Based on the above technical solution, optionally, the device further includes:

[0113] A comparison metadata set screening module, configured to, before matching the value range data to be measured corresponding to the metadata to be measured with the comparison value range data set corresponding to the comparison metadata set, acquire a whitelist data set corresponding to the metadata to be measured; wherein, the whitelist data set includes at least one piece of metadata, and the value range data corresponding to each piece of metadata is the same as the value range data to be measured, but the concept naming of each piece of metadata is different from the value range data to be measured;

[0114] Delete the comparison metadata in the comparison metadata set that is the same as the whitelist data set to obtain a screened comparison metadata set.

[0115] The device for merging metadata concepts provided by the embodiments of the present invention can be used to execute the method for merging metadata concepts provided by the embodiments of the present invention, and has the corresponding functions and beneficial effects for executing the method.

[0116] It should be noted that in the embodiments of the above device for merging metadata concepts, the various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of the functional units are only for the convenience of mutual distinction and do not limit the protection scope of the present invention.

[0117] Embodiment Five

[0118] Figure 6 It is a schematic structural diagram of an electronic device provided by Embodiment Five of the present invention. The embodiments of the present invention provide services for implementing the method for merging metadata concepts in the above embodiments of the present invention, and can configure the device for merging metadata concepts in the above embodiments. Figure 6A block diagram of an exemplary electronic device 12 suitable for implementing embodiments of the present invention is shown. Figure 6 The illustrated electronic device 12 is merely an example and should not impose any limitation on the functions and scope of use of the embodiments of the present invention.

[0119] As Figure 6 shown, the electronic device 12 is presented in the form of a general-purpose computing device. The components of the electronic device 12 may include, but are not limited to: one or more processors or processing units 16, a system memory 28, and a bus 18 connecting different system components (including the system memory 28 and the processing unit 16).

[0120] The bus 18 represents one or more of several types of bus architectures, including a memory bus or memory controller, a peripheral bus, a graphics acceleration port, a processor, or a local bus using any of the various bus architectures. By way of example, these architectures include, but are not limited to, Industry Standard Architecture (ISA) bus, Micro Channel Architecture (MAC) bus, Enhanced ISA bus, Video Electronics Standards Association (VESA) local bus, and Peripheral Component Interconnect (PCI) bus.

[0121] The electronic device 12 typically includes a variety of computer system-readable media. These media can be any available media accessible by the electronic device 12, including volatile and non-volatile media, removable and non-removable media.

[0122] The system memory 28 may include computer system-readable media in the form of volatile memory, such as random access memory (RAM) 30 and / or cache memory 32. The electronic device 12 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, a storage system 34 may be used for reading and writing on non-removable, non-volatile magnetic media ( Figure 6 not shown, commonly referred to as a "hard disk drive"). Although Figure 6 not shown in the figure, a disk drive for reading and writing on a removable non-volatile disk (such as a "floppy disk") and an optical disk drive for reading and writing on a removable non-volatile optical disk (such as a CD-ROM, DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to the bus 18 through one or more data media interfaces. The memory 28 may include at least one program product having a set (e.g., at least one) of program modules configured to perform the functions of the embodiments of the present invention.

[0123] A program / utilities 40 having a set (at least one) of program modules 42 can be stored, for example, in a memory 28. Such program modules 42 include, but are not limited to, an operating system, one or more application programs, other program modules, and program data. Each or some combination of these examples may include an implementation of a network environment. The program modules 42 generally execute the functions and / or methods in the embodiments described in the present invention.

[0124] The electronic device 12 can also communicate with one or more external devices 14 (such as a keyboard, a pointing device, a display 24, etc.), can also communicate with one or more devices that enable a user to interact with the electronic device 12, and / or can communicate with any device that enables the electronic device 12 to communicate with one or more other computing devices (such as a network card, a modem, etc.). Such communication can be carried out through an input / output (I / O) interface 22. Moreover, the electronic device 12 can also communicate with one or more networks (such as a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) through a network adapter 20. As Figure 6 shown, the network adapter 20 communicates with other modules of the electronic device 12 through a bus 18. It should be understood that, although not shown in the figure, other hardware and / or software modules can be used in combination with the electronic device 12, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, etc.

[0125] The processing unit 16 executes various functional applications and data processing by running programs stored in the system memory 28, such as implementing the method for merging metadata concepts provided in the embodiments of the present invention.

[0126] Through the above-mentioned electronic device, the problem that the existing metadata management platform cannot recognize metadata with the same concept is solved, the management function of the metadata management platform is optimized, the understanding error caused by the user's subjective judgment is avoided, and thus the practicability of the metadata management platform is improved.

[0127] Embodiment Six

[0128] Embodiment Six of the present invention also provides a storage medium containing computer-executable instructions, and the computer-executable instructions are used to execute a method for merging metadata concepts when executed by a computer processor. The method includes:

[0129] Obtain the metadata to be tested and the comparison metadata set in the metadata management platform; wherein, the comparison metadata set contains at least one comparison metadata;

[0130] Match the blood relationship data corresponding to the metadata to be tested with the blood relationship data set corresponding to the comparison metadata set; wherein, the blood relationship data set contains blood relationship data corresponding to at least one comparison metadata respectively.

[0131] Use the comparison metadata corresponding to the successfully matched blood relationship data as the target metadata, and perform a merging operation on the concept naming of the metadata to be tested and the concept naming of the target metadata.

[0132] The computer storage medium of the embodiments of the present invention may adopt any combination of one or more computer-readable media. The computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples (non-exhaustive list) of the computer-readable storage medium include: an electrical connection having one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this document, the computer-readable storage medium may be any tangible medium that contains or stores a program, and the program may be used by or in combination with an instruction execution system, apparatus, or device.

[0133] The computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries the computer-readable program code. Such a propagated data signal may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. The computer-readable signal medium may also be any computer-readable medium other than the computer-readable storage medium, and the computer-readable medium may send, propagate, or transmit a program for use by or in combination with an instruction execution system, apparatus, or device.

[0134] The program code contained on the computer-readable medium may be transmitted by any suitable medium, including but not limited to wireless, wire, optical cable, RF, etc., or any suitable combination of the above.

[0135] Computer program code for performing the operations of the present invention may be written in one or more programming languages or combinations thereof. The programming languages include object-oriented programming languages such as Java, Smalltalk, C++, and also include conventional procedural programming languages such as the "C" language or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, executed as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., connected through the Internet using an Internet service provider).

[0136] Of course, the computer-executable instructions provided by the embodiments of the present invention in a storage medium are not limited to the above method operations, and may also execute the related operations in the method for merging metadata concepts provided by any embodiment of the present invention.

[0137] Note that the above are only the preferred embodiments of the present invention and the technical principles applied. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein. Various obvious changes, re-adjustments, and substitutions can be made by those skilled in the art without departing from the protection scope of the present invention. Therefore, although the present invention has been described in detail through the above embodiments, the present invention is not limited to the above embodiments. Without departing from the concept of the present invention, more other equivalent embodiments may be included, and the scope of the present invention is determined by the scope of the appended claims.

Claims

1. A method for merging metadata concepts, characterized in that Including: Obtain the metadata to be tested and the comparison metadata set in the metadata management platform; wherein, the comparison metadata set includes at least one comparison metadata. Match the blood relationship data corresponding to the metadata to be tested with the blood relationship data set corresponding to the comparison metadata set; wherein, the blood relationship data set corresponding to the comparison metadata set includes the blood relationship data corresponding to at least one comparison metadata respectively, and the blood relationship data represents the transfer information of the metadata in the metadata management platform. Use the comparison metadata corresponding to the successfully matched blood relationship data as the target metadata, and perform a merging operation on the concept naming of the metadata to be tested and the concept naming of the target metadata. The method further includes: If the blood relationship data corresponding to the metadata to be tested fails to match the blood relationship data set corresponding to the comparison metadata set, then match the value range data corresponding to the metadata to be tested with the value range data set corresponding to the comparison metadata set; wherein, the value range data set corresponding to the comparison metadata set includes the value range data corresponding to at least one comparison metadata respectively. Use the comparison metadata corresponding to the successfully matched value range data as the target metadata, and perform a merging operation on the concept naming of the metadata to be tested and the concept naming of the target metadata. Before matching the value range data corresponding to the metadata to be tested with the value range data set corresponding to the comparison metadata set, the method further includes: Obtain the white list data set corresponding to the metadata to be tested. Filter the comparison metadata set according to the white list data set to obtain the filtered comparison metadata set. Wherein, the white list data set includes at least one metadata, the value range data corresponding to each metadata is the same as the value range data corresponding to the metadata to be tested but the concept naming of each metadata is different from that of the metadata to be tested, or the white list data set includes at least two metadata with the same value range data but different concept namings.

2. The method according to claim 1, wherein The metadata management platform includes at least one data transfer layer. Correspondingly, obtaining the metadata to be tested and the comparison metadata set in the metadata management platform includes: For each data transfer layer in the metadata management platform, obtain the metadata to be tested and the comparison metadata set corresponding to the data transfer layer; wherein, the data transfer layer is used to represent the transfer platform of the metadata in the metadata management platform.

3. The method according to claim 2, wherein The obtaining of the metadata to be tested and the comparison metadata set corresponding to the data transfer layer includes: When detecting a metadata addition instruction, use the metadata corresponding to the metadata addition instruction as the metadata to be tested. Based on the layer identifier corresponding to the data transfer layer, obtain the comparison metadata set in the database.

4. The method according to claim 2, characterized in that, The obtaining of the metadata to be tested and the comparison metadata set corresponding to the data transfer layer includes: When detecting that the current time meets the preset time point, based on the layer identifier corresponding to the data transfer layer, obtain at least two metadata in the database. For each metadata, use the metadata as the metadata to be tested, and add the metadata other than the metadata to be tested to the comparison metadata set.

5. The method according to claim 1, characterized in that, The type of the comparison value range data is a dictionary - type value range or a formatted text value range. Correspondingly, the method further includes: For each comparison metadata, when the type of the comparison value range data of the comparison metadata is a dictionary - type value range, obtain the comparison value range data corresponding to the comparison metadata in the foreign key relationship table corresponding to the database where the comparison metadata is located; When the type of the comparison value range data of the comparison metadata is a formatted text value range, obtain the comparison value range data corresponding to the comparison metadata in the database.

6. The method according to claim 1, wherein The screening of the comparison metadata set according to the white - list data set to obtain a screened comparison metadata set includes: When the white - list data set contains at least one metadata, and the value range data corresponding to each metadata is the same as the to - be - measured value range data but the concept names of each metadata are different from the to - be - measured value range data, delete the comparison metadata in the comparison metadata set that is the same as the white - list data set to obtain a screened comparison metadata set.

7. An apparatus for merging metadata concepts, characterized in that, Including: A to - be - measured metadata acquisition module, configured to acquire the to - be - measured metadata and the comparison metadata set in the metadata management platform; wherein, the comparison metadata set contains at least one comparison metadata; A to - be - measured blood - relationship data matching module, configured to match the to - be - measured blood - relationship data corresponding to the to - be - measured metadata with the comparison blood - relationship data set corresponding to the comparison metadata set; wherein, the comparison blood - relationship data set contains comparison blood - relationship data respectively corresponding to at least one comparison metadata, and the blood - relationship data represents the transfer information of the metadata in the metadata management platform; A concept merging module, configured to use the comparison metadata corresponding to the successfully matched comparison blood - relationship data as the target metadata, and perform a merging operation on the concept name of the to - be - measured metadata and the concept name of the target metadata; The device further includes: A to - be - measured value range data matching module, configured to, if the to - be - measured blood - relationship data fails to match the comparison blood - relationship data set, match the to - be - measured value range data corresponding to the to - be - measured metadata with the comparison value range data set corresponding to the comparison metadata set; wherein, the comparison value range data set contains comparison value range data respectively corresponding to at least one comparison metadata; Use the comparison metadata corresponding to the successfully matched comparison value range data as the target metadata, and perform a merging operation on the concept name of the to - be - measured metadata and the concept name of the target metadata; A comparison metadata set screening module, configured to obtain a white - list data set corresponding to the to - be - measured metadata before matching the to - be - measured value range data corresponding to the to - be - measured metadata with the comparison value range data set corresponding to the comparison metadata set; Screen the comparison metadata set according to the white - list data set to obtain a screened comparison metadata set; Wherein, the white - list data set contains at least one metadata, the value range data corresponding to each metadata is the same as the to - be - measured value range data but the concept names of each metadata are different from the to - be - measured metadata, or the white - list data set contains at least two metadata with the same value range data but different concept names.

8. An electronic device, characterized in that, The electronic device includes: One or more processors; A memory for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the method for merging metadata concepts as described in any one of claims 1-6.

9. A storage medium containing computer-executable instructions, characterized in that, The computer-executable instructions are used to execute the method for merging metadata concepts as described in any one of claims 1-6 when executed by a computer processor.

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