Server, data processing method, data processing system and electronic equipment

Abstract

The embodiment of the invention provides a server, a data processing method, a data processing system and electronic equipment. The server comprises a data field used for standardized processing of input data; the model domain is used for standardly defining a data processing model; and the rule field is used for defining a data processing rule. Through the server provided by the embodiment of the invention, the data barriers among different enterprises in the industry are effectively broken, and the data processing standards of the different enterprises in the industry are unified, so that the problem of difficulty in data intercommunication among the enterprises is overcome, and a reliable data basis is provided for industry co-construction.

Description

Server, data processing method, data processing system and electronic equipment Technical Field

[0001] The present application relates to the field of data processing, and in particular to a server, a data processing method, a data processing system, and an electronic device. Background Art

[0002] With the rapid development of the new energy industry, industry data is becoming diverse and dispersed, resulting in different data processing standards across different companies. Furthermore, each company within the industry specializes in different data processing areas. For example, some companies possess data access capabilities, others provide data algorithm services, and still others specialize in troubleshooting. Data barriers exist between companies, making them reluctant to expose their data externally.

[0003] It can be seen that due to the different data processing standards of various enterprises and the existence of data barriers, it is difficult to achieve data interoperability between enterprises, which leads to the inability of enterprises in the industry to effectively participate in industry co-construction, affecting industry development.

[0004] Summary of the Invention

[0005] The present application provides a server, a data processing method, a data processing system and an electronic device, which solve the problem of difficulty in achieving data intercommunication between enterprises in the industry in the prior art.

[0006] To achieve the above objectives, this application adopts the following technical solutions:

[0007] In a first aspect, a server is provided, comprising:

[0008] Data domain, used to standardize input data;

[0009] Model domain, used to standardize the definition of data processing models;

[0010] Rule domain, used to define data processing rules.

[0011] In the embodiment of this application, the server-side system architecture is divided into three domains, each corresponding to a data processing field, and data standardization services are provided for different data processing fields. The server provided by the embodiment of this application effectively breaks down the data barriers between different companies in the industry and unifies the data processing standards of different companies in the industry, thereby overcoming the problem of data interoperability between companies and providing a reliable data foundation for industry co-construction.

[0012] In an implementation of the first aspect, the server includes a first interface;

[0013] The first interface is used to input data to be processed into the data domain.

[0014] In this embodiment of the present application, the data domain exchanges data with the server via the first interface, which is equivalent to assuming a separate data input channel for the data domain. This effectively avoids confusion between data in the data domain and data in other domains, thereby improving the reliability and efficiency of data interaction between the data domain and external data.

[0015] In an implementation of the first aspect, the server includes a second interface;

[0016] The second interface is used to output the data to be processed after the data domain has normalized the data to be processed.

[0017] In this embodiment of the present application, the data domain exchanges data with the server through the second interface, which is equivalent to assuming a separate data output channel for the data domain. This effectively avoids confusion between data in the data domain and data in other domains, and helps improve the reliability and efficiency of data interaction between the data domain and external data.

[0018] In an implementation of the first aspect, the server includes a third interface;

[0019] The third interface is used to output model definition information of the data processing model.

[0020] In this embodiment of the present application, the model domain exchanges data with the server through the third interface, effectively establishing a separate communication channel between the model domain and the server. This effectively prevents confusion between the model domain's model definition information and data from other domains, thereby improving the reliability and efficiency of the data domain's interaction with external data.

[0021] In an implementation of the first aspect, the server includes a fourth interface;

[0022] The fourth interface is used to provide an execution engine for the data processing rules.

[0023] In an embodiment of the present application, the rule domain performs standardized processing on external rule data through the fourth interface, which can effectively avoid confusion between the data of the rule domain and the data of other domains, and is beneficial to improving the reliability and efficiency of the interaction between the rule domain and external data. At the same time, it unifies the rule data flowing into the server, facilitating subsequent data processing.

[0024] In an implementation of the first aspect, the server includes a fifth interface, and the fifth interface is used to output the data processed by the rule domain.

[0025] The fifth interface is equivalent to the query interface for data processing results. In the embodiment of the present application, the rule domain provides data processing results to the outside through the fifth interface, which can effectively avoid confusion between the rule domain's data and data from other domains, and is conducive to improving the reliability and efficiency of the interaction between the rule domain and external data.

[0026] In an implementation of the first aspect, the data domain includes at least two data layers, and different data layers are used to store data at different processing stages during the standardization process.

[0027] In the embodiments of the present application, the data domain standardization process can include multiple processing stages, such as normalization, data cleaning, and data aggregation. Storing data from different processing stages in different data layers is equivalent to categorizing and storing data from different processing stages, and organizing and arranging the data during the standardization process. This facilitates data tracing and subsequent troubleshooting.

[0028] In an implementation of the first aspect, the data layer includes at least two storage media, and different storage media are used to store different categories of data.

[0029] In the embodiments of the present application, the data in each data layer is classified and processed, and stored in a classified manner, which is equivalent to summarizing and organizing the data during the standardization process. This method is conducive to data traceability and subsequent troubleshooting. In addition, since different companies have different types of industry data, through the above method, companies can selectively connect to the server based on their own data types, making the server have flexible access capabilities and able to be compatible with and standardize the relevant data of various companies.

[0030] In a second aspect, a data processing method is provided, applied to the server as described in any one of the first aspects, the data processing method comprising:

[0031] Standardize the input data to be processed;

[0032] Processing the standardized data according to the data processing model;

[0033] The data processed by the data processing model is processed according to the data processing rules.

[0034] In the embodiment of the present application, the server can standardize data from different data sources and process the standardized data based on standardized data processing models and data processing rules, thereby achieving standardization in three dimensions: data, models (algorithms), and rules. It effectively breaks down the data barriers between different companies in the industry and unifies the data processing standards of different companies in the industry, thereby overcoming the problem of difficulty in data intercommunication between companies and providing a reliable data foundation for industry co-construction.

[0035] In an implementation of the second aspect, before standardizing the input data to be processed, the data processing method further includes:

[0036] The data definition is sent to the client, so that the client converts the data format according to the data definition and obtains the data to be processed.

[0037] Through this preprocessing process, the data definition is delivered to the client, which then converts the data format. This allows the server's data domain to exchange data with a variety of client types, facilitating subsequent data standardization. Furthermore, this preprocessing process effectively standardizes the client's data, effectively reducing the amount of data processing required by the server's data domain.

[0038] In an implementation of the second aspect, the data domain standardization processing of the input data to be processed includes:

[0039] Performing data cleaning on the data to be processed to obtain cleaned data;

[0040] Data aggregation is performed on the cleaned data to obtain standardized data.

[0041] Through the above data processing process, data from different data sources are integrated, and standardized processing of data from various enterprises is achieved.

[0042] In an implementation of the second aspect, the data processing method further includes:

[0043] The data to be processed, the cleaned data and the standardized data are stored in different data layers respectively.

[0044] In the embodiments of the present application, the data domain standardization process can include multiple processing stages, such as normalization, data cleaning, and data aggregation. Storing data from different processing stages in different data layers is equivalent to categorizing and storing data from different processing stages, and organizing and arranging the data during the standardization process. This facilitates data tracing and subsequent troubleshooting.

[0045] In an implementation of the second aspect, the data processing method further includes:

[0046] For each of the data layers, dividing the data stored in the data layer into at least two categories;

[0047] Different types of data are stored in different storage media in the data layer.

[0048] In the embodiments of the present application, the data in each data layer is classified and processed, and stored in a classified manner, which is equivalent to summarizing and organizing the data during the standardization process. This method is conducive to data traceability and subsequent troubleshooting. In addition, since different companies have different types of industry data, through the above method, companies can selectively connect to the server based on their own data types, making the server have flexible access capabilities and able to be compatible with and standardize the relevant data of various companies.

[0049] In an implementation of the second aspect, the data processing model includes a plurality of operators;

[0050] The data processing method further includes:

[0051] Operators in the data processing model are defined according to an operator specification language.

[0052] In the embodiment of the present application, the operator definition can be provided by the model domain and can be called by upper-layer applications without having to adapt algorithms from different sources. By defining the operator, the standardization of the data processing model is achieved.

[0053] In an implementation of the second aspect, processing the standardized data according to the data processing rule includes:

[0054] Combining and sorting the plurality of data processing models according to the data processing rules to obtain a model sequence;

[0055] The standardized data is processed according to the model sequence.

[0056] In an implementation of the second aspect, the data processing method further includes:

[0057] Standardize the input sample data;

[0058] Set labels for the standardized sample data to obtain training data;

[0059] The data processing model is trained according to the training data.

[0060] In an implementation of the second aspect, the data processing method further includes:

[0061] Get encrypted data from the blockchain;

[0062] Decrypting the encrypted data to obtain a data directory, wherein the data directory includes a data summary of the sample data in the client;

[0063] Standardizing the data directory;

[0064] The data processing model is trained based on the standardized data catalog.

[0065] In the embodiment of the present application, since the data directory only includes the data summary of the sample data in the client and does not include the specific information of the sample data, it is equivalent to the client not providing its own detailed data to the server, thereby improving the privacy and security of the data in the client.

[0066] In an implementation of the second aspect, training the data processing model according to the standardized data catalog includes:

[0067] Establishing a general processing model based on the standardized data catalog;

[0068] Sending the general processing model to the client, so that the client can train the general processing model according to the sample data corresponding to the standardized data directory to obtain intermediate data;

[0069] Acquiring the intermediate data;

[0070] The general processing model is updated according to the intermediate data to obtain the data processing model.

[0071] In the embodiments of this application, each enterprise trains a universal processing model based on its own data without exposing its own data to the server, thus ensuring the privacy and security of enterprise data. Furthermore, the intermediate data reported by each enterprise to the server is equivalent to the processing results of each enterprise on the universal processing model. The server and other enterprises cannot obtain the enterprise's sample data through the intermediate data. Through the above method, the privacy and security of enterprise data are further guaranteed while ensuring the data processing model.

[0072] In a third aspect, a data processing system is provided, comprising a server and a client; wherein the server implements the data processing method as described in any one of the second aspects.

[0073] In the embodiment of the present application, the data processing system composed of the above-mentioned server and client effectively breaks down the data barriers between different enterprises in the industry, unifies the data processing standards of different enterprises in the industry, thereby overcoming the problem of difficulty in data intercommunication between enterprises and providing a reliable data foundation for industry co-construction.

[0074] In a fourth aspect, an electronic device is provided, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the data processing method as described in any one of the second aspects when executing the computer program.

[0075] In a fifth aspect, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the data processing method as described in any one of the second aspects is implemented.

[0076] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0077] FIG1 is a schematic diagram of the system architecture of the server provided in an embodiment of the present application;

[0078] FIG2 is a schematic diagram of the structure of the server interface provided in an embodiment of the present application;

[0079] FIG3 is a schematic diagram of tiered storage provided by an embodiment of the present application;

[0080] FIG4 is a flow chart of a data processing method according to an embodiment of the present application;

[0081] FIG5 is a schematic diagram of the interaction between the server and the client provided in an embodiment of the present application;

[0082] FIG6 is a schematic diagram of the structure of a data processing system provided in an embodiment of the present application. DETAILED DESCRIPTION

[0083] It is only used to more clearly illustrate the technical solution of the present application and is therefore only an example and cannot be used to limit the scope of protection of the present application.

[0084] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this application belongs; the terms used herein are for the purpose of describing specific embodiments only and are not intended to limit this application; the terms "including" and "having" and any variations thereof in the specification and claims of this application and the above-mentioned figure descriptions are intended to cover non-exclusive inclusions.

[0085] In the description of the embodiments of this application, the technical terms "first" and "second" are used only to distinguish different objects and should not be understood to indicate or imply relative importance or implicitly specify the quantity, specific order, or primary and secondary relationship of the indicated technical features. In the description of the embodiments of this application, the meaning of "plurality" is more than two, unless otherwise clearly and specifically defined.

[0086] References herein to "embodiments" mean that a particular feature, structure, or characteristic described in connection with the embodiments may be included in at least one embodiment of the present application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute an independent or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0087] In the description of the embodiments of this application, the term "and / or" is simply a description of the association relationship between associated objects, indicating that three relationships can exist. For example, A and / or B can represent the following three situations: A exists alone, A and B exist simultaneously, and B exists alone. In addition, the character " / " in this document generally indicates that the associated objects are in an "or" relationship.

[0088] With the rapid development of the new energy industry, industry data is becoming diverse and fragmented. For example, battery manufacturers possess basic static data, including various pre-shipment initialization data and raw material data. Vehicle manufacturers possess comprehensive dynamic data on battery charging and discharging, including battery voltage, current, temperature, operating time, differential pressure and temperature, and fast charging, but lack basic static data, including pre-shipment initialization data and raw material data. Some charging station manufacturers possess operational data for charging stations, but lack dynamic data from vehicle manufacturers and static data from battery manufacturers. For the entire industry, building a complete battery application system requires basic static data, dynamic data on charging and discharging, and operational data from charging stations. Currently, different companies within the industry have different data processing standards, making data interoperability difficult. This prevents companies from effectively participating in industry collaboration and hinders industry development.

[0089] Furthermore, different companies within the industry are involved in different data processing areas. For example, some companies possess basic battery data and data access capabilities; some companies possess data processing algorithm service capabilities, but lack basic battery data; and others can provide solutions to fault scenarios and have troubleshooting capabilities, but lack basic battery data and data processing algorithm service capabilities. Building a complete battery application system is essential in each data processing area. Currently, data barriers exist between companies, and they are reluctant to expose their data externally. This makes data interoperability difficult, preventing companies from effectively participating in industry co-construction and hindering industry development.

[0090] Based on the above considerations, in order to solve the problem of data intercommunication between enterprises in the industry, the embodiment of the present application provides a server. The server divides the system into reasonable functions according to different fields of data processing, and provides data standardization services for each functional domain of the system. The server provided by the embodiment of the present application effectively breaks down the data barriers between different enterprises in the industry, unifies the data processing standards of different enterprises in the industry, thereby overcoming the problem of data intercommunication between enterprises and providing a reliable data foundation for industry co-construction.

[0091] The server end in the embodiment of the present application can be a server or a server cluster composed of multiple servers. Specifically, the server end can be a single server containing several storage upgrade packages, or a distributed server cluster containing distributed storage upgrade packages, group configuration information or upgrade policy information. For example, a distributed server can be a server cluster composed of multiple servers, and the cluster can include cloud computer servers, content delivery network (Content Delivery Network, CDN) servers, network time protocol (Network Time Protocol, NTP), domain name resolution system (Domain Name System, DNS) servers, etc. Among them, the servers in the server cluster coordinate with each other to jointly complete functions such as computing, data storage, and communication. For the convenience of description, in the embodiment of the present application, a single server, a distributed server, and a server cluster are collectively referred to as a server end.

[0092] The server is introduced below with a specific embodiment.

[0093] Referring to Figure 1, a schematic diagram of the server system architecture provided by an embodiment of the present application is shown. As shown in Figure 1, server 1 includes a data domain 11, a model domain 12, and a rule domain 13. The data domain 11 is used to standardize input data, the model domain 12 is used to standardize the definition of data processing models, and the rule domain 13 is used to define data processing rules.

[0094] It is understandable that in the embodiments of the present application, the "domain" in "data domain", "model domain" and "rule domain" can refer to a field. Specifically, the three domains correspond to different data processing fields, and accordingly, the three domains connect to enterprises belonging to different data processing fields. For example: data domain 11 corresponds to the data access field, which is used to connect to enterprises that have basic battery data and data access capabilities; model domain 12 corresponds to the algorithm processing field, which is used to connect to enterprises with data processing algorithm service capabilities; rule domain 13 corresponds to the fault resolution field, which is used to connect to enterprises with fault resolution capabilities.

[0095] In some implementations, the data domain 11, model domain 12, and rule domain 13 can be implemented by different modules or units in the server. For example, if the server is a single server, the three domains can be implemented by three different computing modules in the server. If the server is a server cluster, the three domains can be implemented by different servers in the server cluster. The three domains can process data serially or in parallel.

[0096] In the embodiment of the present application, the data domain 11 can obtain the data to be processed from the outside through the interface of the server and perform standardized processing on the data to be processed.

[0097] In the embodiment of the present application, the model domain 12 can provide standardized operator definitions and transmit these operator definitions to the outside world through a server-side interface, so that enterprises can standardize their own data processing models based on the operator definitions. Of course, the model domain 12 can also obtain non-standardized data processing models from the outside world through a server-side interface, standardize the non-standardized data processing models based on the standardized operator definitions, and obtain a standardized data processing model. An operator is the smallest unit of a data processing model.

[0098] In this embodiment of the present application, rule domain 13 can obtain fault models (fault models are used to detect and / or resolve faults) from the outside through a server-side interface and define the relationship between the fault models and the data processing models, namely, data processing rules. It is understood that data processing rules are an arrangement of algorithms (data processing models) based on the fault models and are the rules for determining faults.

[0099] In the embodiment of this application, the server-side system architecture is divided into three domains, each corresponding to a data processing field, and data standardization services are provided for different data processing fields. The server provided by the embodiment of this application effectively breaks down the data barriers between different companies in the industry and unifies the data processing standards of different companies in the industry, thereby overcoming the problem of data interoperability between companies and providing a reliable data foundation for industry co-construction.

[0100] As described in the above embodiments, the server exchanges data with the outside world through an interface. In some application scenarios, the server may include a receiving interface and a sending interface. The receiving interface is used to obtain data from the outside world, and the sending interface is used to send data to the outside world. For example, the data domain obtains data to be processed from the outside world through the receiving interface and transmits the standardized data to the outside world through the sending interface. The model domain obtains non-standardized data processing models from the outside world through the receiving interface and transmits standardized data processing models to the outside world through the sending interface. The rule domain obtains fault models from the outside world through the receiving interface and transmits data processing results to the outside world through the sending interface.

[0101] It can be seen that in the above data transmission method, since the server only provides two external interfaces, data congestion and data confusion are easily caused during the process of the three domains transmitting data externally.

[0102] To solve the above problem, in one embodiment, the server includes a first interface and a second interface, wherein the first interface is used to input the data to be processed into the data domain, and the second interface is used to output the standardized data.

[0103] In some application scenarios, the data domain obtains unprocessed data from the outside through the first interface, standardizes the unprocessed data, and then transmits the standardized data to the outside through the second interface. For example, the unprocessed data can be various types of battery data, vehicle data, charging pile data, or energy storage data. In the embodiment of the present application, the data domain of the server integrates multiple data storage devices through the first interface and the second interface, transparently providing various data services to the upper layer business.

[0104] In this embodiment of the present application, the data domain exchanges data with the server through the first and second interfaces, effectively establishing separate communication channels between the data domain and the server. This effectively avoids confusion between data in the data domain and data in other domains, thereby improving the reliability and efficiency of data exchange between the data domain and the outside world.

[0105] In other embodiments, the server includes a first interface or a second interface. For example, the server includes a first interface. In this case, the first interface is used to input the data to be processed into the data domain and to output the standardized data to the outside.

[0106] Compared to a server-side approach that includes either the first or second interface, this approach effectively establishes separate interaction channels between the data domain and the external server. This approach effectively avoids confusion between input and output data in the data domain, improving the reliability and efficiency of data interaction between the data domain and the external server.

[0107] In one embodiment, the server includes a third interface for outputting model definition information of the data processing model.

[0108] The model definition information includes operator definition, model definition, and definition of parameters required by the model, etc. In the embodiment of the present application, the model domain of the server provides a standard operator specification language (OSL) for upper-layer applications to call without having to adapt algorithms from different sources.

[0109] In some application scenarios, the model domain outputs the model definition information of the data processing model to the outside through the third interface, so that the enterprise can standardize its own data processing model according to the model definition information.

[0110] In this embodiment of the present application, the model domain exchanges data with the server through the third interface, effectively establishing a separate communication channel between the model domain and the server. This effectively prevents confusion between the model domain's model definition information and data from other domains, thereby improving the reliability and efficiency of the data domain's interaction with external data.

[0111] In one embodiment, the model domain is further used to process the data after the data domain is standardized according to the data processing model. Accordingly, the third interface is further used to output the data processed by the data processing model.

[0112] In some application scenarios, the model domain transmits the intermediate calculation results of the data processing model to the outside through the third interface, which can be used for training the data processing model.

[0113] In the embodiment of the present application, the model domain provides the intermediate calculation results of the data processing model to the outside world through the third interface. When the data processing model needs to be jointly constructed by multiple enterprises, this method can achieve data interoperability between enterprises while ensuring the security of enterprise data, thereby facilitating the construction of the data processing model.

[0114] In one embodiment, the server includes a fourth interface for providing an execution engine for data processing rules.

[0115] The execution engine's task is to convert input data into data that can be recognized by the recipient, which is equivalent to the process of standardizing external data. In some application scenarios, the rule domain calls an external fault model through the fourth interface.

[0116] In an embodiment of the present application, the rule domain performs standardized processing on external rule data through the fourth interface, which can effectively avoid confusion between the data of the rule domain and the data of other domains, and is beneficial to improving the reliability and efficiency of the interaction between the rule domain and external data. At the same time, it unifies the rule data flowing into the server, facilitating subsequent data processing.

[0117] In one embodiment, the server includes a fifth interface, and the fifth interface is used to output data processed by the rule domain.

[0118] The fifth interface is equivalent to the query interface for data processing results. In the embodiment of the present application, the rule domain provides data processing results to the outside through the fifth interface, which can effectively avoid confusion between the rule domain's data and data from other domains, and is conducive to improving the reliability and efficiency of the interaction between the rule domain and external data.

[0119] It should be noted that, in some embodiments, the server may include any one or more of the first through fifth interfaces described above. When the server includes all of the first through fifth interfaces, the data domain, model domain, and rule domain in the server interact with the external world independently and more flexibly, making data between the three domains less likely to be confused, and thus improving the reliability and efficiency of data interaction between the server and the external world.

[0120] For example, see Figure 2, which is a structural diagram of the server interface provided by an embodiment of the present application. As shown in Figure 2, the server 1 includes a first interface 21, a second interface 22, a third interface 23, a fourth interface 24 and a fifth interface 25. Among them, inside the server, the data domain is connected to the model domain, and the model domain is connected to the rule domain. During the data processing process, the data domain obtains the data to be processed from the outside through the first interface, and outputs the first processed data after the standardized processing of the data to be processed to the outside through the second interface; the model domain obtains the first processed data from the data domain, processes the first processed data through the data processing model, obtains the second processed data, and outputs the second processed data through the third interface; the rule domain obtains the second processed data from the model domain, processes the second processed data according to the data processing rules, obtains the third processed data, and outputs the third processed data through the fifth interface; in addition, the model domain also provides the model definition information of the model processing model to the outside through the third interface, and the rule domain also provides the execution engine of the data processing rules to the outside through the fourth interface.

[0121] It should be noted that the above is only an example of the server interface structure and does not specifically limit the data, location, name, etc. of the server interface.

[0122] In one embodiment, the data domain includes at least two data layers, and different data layers are used to store data at different processing stages during the standardization process.

[0123] For example, a data layer may refer to a storage medium, i.e., different data layers correspond to different storage media. For another example, a data layer may refer to a storage unit or storage partition in a storage medium, i.e., different data layers correspond to different storage units or storage partitions in the same storage medium.

[0124] In the embodiments of the present application, the data domain standardization process can include multiple processing stages, such as normalization, data cleaning, and data aggregation. Storing data from different processing stages in different data layers is equivalent to categorizing and storing data from different processing stages, and organizing and arranging the data during the standardization process. This facilitates data tracing and subsequent troubleshooting.

[0125] In actual applications, industry data is diverse. For example, the new energy industry includes vehicle data, battery data, cell data, charging station data, energy storage data, and configuration data, among others. Storing all types of data within an industry on the same storage medium is equivalent to mixing all the data together, which is not conducive to subsequent data processing. Furthermore, each enterprise may only be involved in one or several types of industry data. After the enterprise and the server are connected, if all types of data are mixed and stored together, data leakage is likely to occur during the data transmission process (such as transferring one enterprise's data to another), and data security and privacy are low.

[0126] To solve the above problem, in one embodiment, the data layer includes at least two storage media, and different storage media are used to store different types of data.

[0127] For example, see Figure 3, which is a schematic diagram of tiered storage provided by an embodiment of the present application. As shown in Figure 3, the data domain standardization process includes a raw data stage, a cleansed data stage, and an aggregated data stage. Each processing stage corresponds to a data layer, and each data layer includes multiple storage media, each of which stores different types of data.

[0128] As shown in Figure 3, the "raw data" stage is the data to be processed that the data domain obtains from various external companies through the first interface, including passenger car data, commercial vehicle data, charging pile data, energy storage data, and configuration data; this data is divided into three types of data: vehicle data, battery pack data, and battery cell data; and these three types of data are then stored in different storage media on the raw data layer.

[0129] During the data cleaning phase, the three types of data are cleaned separately. Each type of data can be further divided into subcategories, each of which is cleaned separately. As shown in Figure 3, in the "data cleaning" phase, vehicle data can be divided into two subcategories: vehicle alarms and vehicle events. Battery pack data can be divided into three subcategories: battery alarms, current data, and temperature data. Cell data can be divided into two subcategories: battery alarms and voltage data. The cleaned data corresponding to the three types of data, vehicle data, battery pack data, and cell data, is stored in separate storage media on the cleaned data layer. Each storage medium can also be further divided into multiple storage units / storage areas to store cleaned data from different subcategories within the same data type. For example, a storage medium storing vehicle data can be divided into two storage areas: one for storing the cleaned data from the vehicle alarm subcategory and the other for storing the cleaned data from the vehicle event subcategory.

[0130] During the data aggregation phase, three types of data are aggregated separately. Each type of data can be further divided into subcategories, and each subcategory is aggregated separately. As shown in Figure 3, the "aggregation data" phase for vehicle data includes vehicle speed aggregation (aggregating vehicle speed-related data), alarm aggregation (aggregating alarm-related data), and insulation resistance aggregation (aggregating insulation resistance-related data). For battery pack data, the phase includes system-on-chip (SOC) operating condition aggregation (aggregating SOC-related operating condition data), total voltage operating condition aggregation (aggregating total voltage-related operating condition data), and battery pack temperature operating condition data (aggregating battery pack temperature-related operating condition data). Battery pack operating condition data refers to the operating status data of the battery pack under conditions related to its operation (such as charging and discharging). For cell data, the phase includes battery cell voltage operating condition aggregation (aggregating battery cell voltage-related operating condition data). The aggregated data corresponding to the three types of data—vehicle data, battery pack data, and cell data—are stored in different storage media on the aggregated data layer. Each storage medium can also be further divided into multiple storage units / storage areas to store different subcategories of aggregated data within the same data type. For example, a storage medium storing vehicle data can be divided into three storage areas: the first storage area is used to store aggregated vehicle data, the second storage area is used to store aggregated alarm data, and the third storage area is used to store aggregated insulation resistance data.

[0131] It should be noted that FIG3 only shows an example of classified storage of different data layers. In the embodiment of the present application, there is no specific limitation on the data division of each data layer.

[0132] In the embodiments of the present application, the data in each data layer is classified and processed, and stored in a classified manner, which is equivalent to summarizing and organizing the data during the standardization process. This method is conducive to data traceability and subsequent troubleshooting. In addition, since different companies have different types of industry data, through the above method, companies can selectively connect to the server based on their own data types, making the server have flexible access capabilities and able to be compatible with and standardize the relevant data of various companies.

[0133] Based on the server provided in the above embodiment, an embodiment of the present application provides a data processing method applied to the server.

[0134] See Figure 4, which is a flow chart of a data processing method provided in an embodiment of the present application. As an example and not a limitation, as shown in Figure 4, the data processing method may include the following steps:

[0135] S401, standardize the input data to be processed.

[0136] In the embodiment of the present application, the above-mentioned S401 can be executed by the data domain in the server. Specifically, the data domain obtains the data to be processed from the outside of the server and executes S401. Of course, the data to be processed can also be sent from outside the server to the data domain, and the data domain executes S401 after receiving the data to be processed.

[0137] In some embodiments, the data processing method may further include a pre-processing process, which may specifically include the following steps:

[0138] Before the standardization process is performed on the input data to be processed, the data definition is sent to the client, so that the client converts the data format according to the data definition and obtains the data to be processed.

[0139] The data definition complies with the transmission protocol of the first interface between the data domain and the external server. The data definition can be provided by the data domain and sent to the client by the data domain. The data format of the data to be processed complies with the data definition.

[0140] Through this preprocessing process, the data definition is delivered to the client, which then converts the data format. This allows the server's data domain to exchange data with a variety of client types, facilitating subsequent data standardization. Furthermore, this preprocessing process effectively standardizes the client's data, effectively reducing the amount of data processing required by the server's data domain.

[0141] In some embodiments, an implementation of S401 may include:

[0142] Performing data cleaning on the data to be processed to obtain cleaned data;

[0143] Data aggregation is performed on the cleaned data to obtain standardized data.

[0144] Data cleaning refers to the steps of discovering and correcting identifiable errors in data files, including checking data consistency, handling invalid and missing values, etc. Consistency checking is to check whether the data meets the requirements based on the reasonable value range and mutual relationship of each variable, and to discover data that exceeds the normal range, is logically unreasonable, or contradictory. Invalid and missing values ​​can be handled by estimation, whole-case deletion, or variable deletion. For example, the estimation method refers to replacing the invalid or missing values ​​of a variable with the sample mean, median, or mode of the variable. The whole-case deletion method refers to eliminating samples with missing values. The variable deletion method means that if a variable has a large number of invalid and missing values ​​and the variable is not particularly important for the research problem, then the variable can be considered for deletion.

[0145] Data aggregation involves integrating data from different data sources, grouping and merging them. For example, as shown in Figure 3, vehicle-related data from different companies is grouped into three categories: vehicle, alarm, and insulation resistance. Each category is then merged separately.

[0146] Through the above data processing process, data from different data sources are integrated, and standardized processing of data from various enterprises is achieved.

[0147] Optionally, before data cleaning, the data to be processed can be normalized. Normalization unifies data from different data sources into a standard, limited data range, facilitating subsequent data processing.

[0148] In some embodiments, the data to be processed, the cleaned data, and the standardized data are stored in different data layers respectively.

[0149] Here, a data layer may refer to a storage medium, i.e., different data layers correspond to different storage media. For another example, a data layer may refer to a storage unit or storage partition in a storage medium, i.e., different data layers correspond to different storage units or storage partitions in the same storage medium.

[0150] In the embodiments of the present application, the data domain standardization process can include multiple processing stages, such as normalization, data cleaning, and data aggregation. Storing data from different processing stages in different data layers is equivalent to categorizing and storing data from different processing stages, and organizing and arranging the data during the standardization process. This facilitates data tracing and subsequent troubleshooting.

[0151] In some embodiments, for each of the data layers, the data stored in the data layer is divided into at least two categories; and the data of different categories are stored in different storage media in the data layer.

[0152] The relevant contents of the embodiment of the present application are detailed in the description of the embodiment in Figure 3 above, and will not be repeated here.

[0153] In the embodiments of the present application, the data in each data layer is classified and processed, and stored in a classified manner, which is equivalent to summarizing and organizing the data during the standardization process. This method is conducive to data traceability and subsequent troubleshooting. In addition, since different companies have different types of industry data, through the above method, companies can selectively connect to the server based on their own data types, making the server have flexible access capabilities and able to be compatible with and standardize the relevant data of various companies.

[0154] S402: Process the standardized data according to the data processing model.

[0155] In the embodiment of the present application, the above S402 can be executed by the model domain in the server. Specifically, the data domain sends the standardized data to the model domain, and the model domain executes S402. Of course, the model domain can also actively obtain the standardized data from the data domain and execute S402.

[0156] In some embodiments, the data processing model includes a plurality of operators, wherein an operator is the smallest unit of the data processing model. Accordingly, the data processing method further includes: defining the operators in the data processing model according to an operator specification language (OSL).

[0157] In the embodiment of the present application, the operator definition can be provided by the model domain and can be called by upper-layer applications without having to adapt algorithms from different sources. By defining the operator, the standardization of the data processing model is achieved.

[0158] In some application scenarios, the model domain sends operator definitions to enterprises with algorithm service capabilities, so that these enterprises can standardize data processing models according to the algorithm definitions; the enterprises send the standardized data processing models to the model domain; and the model domain processes the standardized data according to the standardized data processing models.

[0159] In other application scenarios, the model domain obtains data processing models from enterprises with algorithm service capabilities, standardizes the data processing models according to the algorithm definition, and then processes the standardized data according to the standardized data processing models.

[0160] S403: Process the data processed by the data processing model according to the data processing rules.

[0161] In this embodiment of the present application, the above-mentioned S403 can be executed by the rule domain in the server. Specifically, the model domain sends the data processed by the data processing model to the rule domain, and the rule domain executes S403. Of course, the rule domain can also actively obtain the data processed by the data processing model from the model domain and execute S403.

[0162] In the embodiment of the present application, the data processing rules are essentially the arrangement of data processing models according to the fault scenario, which is used to determine the fault. In some embodiments, an implementation of S403 includes:

[0163] The plurality of data processing models are combined and sorted according to the data processing rules to obtain a model sequence; and data processing is performed on the data processed by the data processing models according to the model sequence.

[0164] In one example, assume that the model sequence includes three data processing models, A, B, and C. The data after data domain normalization is input into A, B, and C, respectively, to obtain output a for A, output b for B, and output c for C. Fault diagnosis is then performed based on a, b, and c in the model sequence to obtain a diagnosis result.

[0165] In another example, assume that the model sequence includes three data processing models A, B, and C. First, the data after data domain standardization is input into A to obtain the output of A; the output of A is input into B to obtain the output of B; and the output of B is input into C to obtain the output of C.

[0166] The data processing method described in the embodiment of Figure 4 above enables the server to perform standardized processing on data from different data sources, and process the standardized data based on standardized data processing models and data processing rules, thereby achieving standardization in three dimensions: data, models (algorithms), and rules. This effectively breaks down the data barriers between different companies in the industry, unifies the data processing standards of different companies in the industry, and thus overcomes the problem of difficulty in data intercommunication between companies, providing a reliable data foundation for industry co-construction.

[0167] In some embodiments, the data processing method further includes:

[0168] The input sample data is standardized; labels are set on the standardized sample data to obtain training data; and the data processing model is trained based on the training data.

[0169] In an embodiment of the present application, the data domain in the server can standardize the sample data and set labels; then the data domain sends the training data to the model domain, and the model domain trains the data processing model based on the training data.

[0170] In some applications, the above training data can also be used to verify the training results of the data processing model.

[0171] In some application scenarios, companies are reluctant to expose their own data (such as industry data, algorithm models, and rules). In order to further improve the privacy and security of data processing, in one embodiment, see Figure 5, which is a schematic diagram of the interaction between the server and the client provided in the embodiment of this application. As shown in Figure 5, the data processing method may include:

[0172] Get encrypted data from the blockchain;

[0173] Decrypting the encrypted data to obtain a data directory, wherein the data directory includes a data summary of the sample data in the client;

[0174] Standardizing the data directory;

[0175] The data processing model is trained based on the standardized data catalog.

[0176] In an embodiment of the present application, the data domain in the server can obtain encrypted data from the blockchain, decrypt the encrypted data, obtain a data directory, and standardize the data directory. Finally, the standardized data directory is sent to the model domain; the model domain trains the data processing model based on the standardized data directory.

[0177] Accordingly, on the client side, encrypted data needs to be generated in advance, including:

[0178] Generate a data directory based on the data summary of the sample data; encrypt the data directory to obtain encrypted data; and upload the encrypted data to the blockchain.

[0179] In the embodiment of the present application, since the data directory only includes the data summary of the sample data in the client and does not include the specific information of the sample data, it is equivalent to the client not providing its own detailed data to the server, thereby improving the privacy and security of the data in the client.

[0180] In some embodiments, the step of training the data processing model based on the fifth processed data may include:

[0181] Establish a common processing model based on the standardized data catalog;

[0182] Sending the general processing model to the client, so that the client can train the general processing model according to the sample data corresponding to the data directory and obtain intermediate data;

[0183] Acquiring the intermediate data;

[0184] The general processing model is updated according to the intermediate data to obtain the data processing model.

[0185] In the embodiment of the present application, the above steps can be executed by the model domain in the server.

[0186] Accordingly, on the client side, the process of training a general data processing model may include:

[0187] Obtain a general processing model sent by the server; train the general processing model according to sample data corresponding to the standardized data directory to obtain intermediate data; and upload the intermediate data to the server.

[0188] In the embodiment of the present application, the terminal used by each enterprise to store / process data is called a client.

[0189] Optionally, the model domain uploads the general processing model to the blockchain, and the client obtains the general processing model from the blockchain. The client uploads the intermediate data to the blockchain, and the model domain obtains the intermediate data from the blockchain.

[0190] In this way, the security of data transmission can be guaranteed by signatures during the process of data being uploaded or downloaded from the chain.

[0191] In an embodiment of the present application, the data domain obtains encrypted data from different clients, and after processing, obtains the standardized data directory corresponding to each client, which is equivalent to obtaining the data summary of each different enterprise; the model domain establishes a universal processing model based on the data summary of each enterprise, and then sends the universal processing model to each enterprise respectively; each enterprise trains the universal processing model based on its own data (sample data), obtains intermediate data, and uploads the intermediate data to the model domain; the model domain updates the universal processing model based on the intermediate data uploaded by each enterprise to obtain the final data processing model.

[0192] In one example, see Figure 5, which is a schematic diagram of the interaction between the server and the client provided by an embodiment of the present application. As shown in Figure 5, the process of data interaction between the server and a client may include:

[0193] S501: The client generates a data directory based on the data summary of the sample data.

[0194] S502: The client encrypts the data directory to obtain encrypted data.

[0195] S503: The client uploads the encrypted data to the blockchain.

[0196] S504, the data domain obtains encrypted data from the blockchain.

[0197] S505: The data domain decrypts the encrypted data to obtain a data directory.

[0198] S506: Data domain standardization processing of the data directory.

[0199] S507: The model domain establishes a general processing model based on the standardized data directory.

[0200] S508: The model domain sends the general processing model to the client.

[0201] S509: The client trains the general processing model according to the sample data corresponding to the standardized data directory to obtain intermediate data.

[0202] S510: The client uploads the intermediate data to the model domain of the server.

[0203] S511: The model domain updates the general processing model according to the intermediate data to obtain the data processing model.

[0204] In the embodiments of this application, each enterprise trains a universal processing model based on its own data without exposing its own data to the server, thus ensuring the privacy and security of enterprise data. Furthermore, the intermediate data reported by each enterprise to the server is equivalent to the processing results of each enterprise on the universal processing model. The server and other enterprises cannot obtain the enterprise's sample data through the intermediate data. Through the above method, the privacy and security of enterprise data are further guaranteed while ensuring the data processing model.

[0205] Corresponding to the data processing method described in the above embodiment, the embodiment of the present application provides a data processing device. For ease of description, only the parts related to the embodiment of the present application are described.

[0206] The device includes:

[0207] The data domain unit is used to standardize the input data to be processed.

[0208] The model domain unit is used to process the standardized data according to the data processing model.

[0209] The rule domain unit is used to process the data processed by the data processing model according to the data processing rules.

[0210] Optionally, the data domain unit is further configured to send the data definition to the client, so that the client converts the data format according to the data definition and obtains the data to be processed.

[0211] Optionally, the data field unit is also used to:

[0212] Performing data cleaning on the data to be processed to obtain cleaned data;

[0213] Data aggregation is performed on the cleaned data to obtain standardized data.

[0214] Optionally, the data field unit is also used to:

[0215] The data to be processed, the cleaned data and the standardized data are stored in different data layers respectively.

[0216] Optionally, the data field unit is also used to:

[0217] For each of the data layers, dividing the data stored in the data layer into at least two categories;

[0218] Different types of data are stored in different storage media in the data layer.

[0219] Optionally, the model domain unit is also used to:

[0220] Operators in the data processing model are defined according to an operator specification language.

[0221] Optionally, the rule domain unit is also used to:

[0222] Combining and sorting the plurality of data processing models according to the data processing rules to obtain a model sequence;

[0223] The standardized data is processed according to the model sequence.

[0224] Optionally, the data field unit is also used to:

[0225] Standardize the input sample data;

[0226] Set labels for the standardized sample data to obtain training data;

[0227] The data processing model is trained according to the training data.

[0228] Optionally, the data field unit is also used to:

[0229] Get encrypted data from the blockchain;

[0230] Decrypting the encrypted data to obtain a data directory, wherein the data directory includes a data summary of the sample data in the client;

[0231] The data directory is standardized.

[0232] Optionally, the model domain unit is further used to train the data processing model based on the standardized data directory.

[0233] Optionally, the model domain unit is also used to:

[0234] Establishing a general processing model based on the standardized data catalog;

[0235] Sending the general processing model to the client, so that the client can train the general processing model according to the sample data corresponding to the standardized data directory to obtain intermediate data;

[0236] Acquiring the intermediate data;

[0237] The general processing model is updated according to the intermediate data to obtain the data processing model.

[0238] It should be noted that the information interaction, execution process, etc. between the above-mentioned devices / units are based on the same concept as the method embodiment of this application. Their specific functions and technical effects can be found in the method embodiment section and will not be repeated here.

[0239] In addition, the above-mentioned data processing device can be a software unit, hardware unit, or a combination of software and hardware units built into the existing terminal equipment, or can be integrated into the terminal equipment as an independent accessory, or can exist as an independent terminal equipment.

[0240] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0241] The server and client provided in the embodiment of the present application constitute a data processing system. The data processing system is described below using an embodiment. Referring to FIG6 , it is a schematic diagram of the structure of the data processing system provided in the embodiment of the present application. As shown in FIG6 , the data processing system includes a server 61 and a client 62. The server implements the data processing method applied to the server as described in the embodiment of FIG4 , and the client implements the data processing method applied to the client as described in the embodiment of FIG5 . In actual applications, the data processing system may include multiple clients 62, and only three are shown in FIG6 .

[0242] In Figure 6, the server is represented as a cloud server. In some application scenarios, the server may also be referred to as the cloud side or the cloud side, etc., which is not specifically limited here.

[0243] The server 61 is connected to each client 62 via a wireless network. The wireless network can be based on the fourth generation mobile communication technology (4G), the fifth generation mobile communication technology (5G), or the sixth generation mobile communication technology (6G), and may even be applicable to future communication networks, which are not specifically limited here.

[0244] In one example, the data domain of the server 61 receives basic battery data (data to be processed) uploaded by a client 62 with data access capabilities and standardizes the received basic battery data. The model domain of the server 61 receives data processing models uploaded by a client 62 with algorithm service capabilities and standardizes the data processing models according to standardized operator definitions. The rule domain of the server 61 receives fault models uploaded by a client 62 with fault resolution capabilities, defines the relationship between the fault model and the data processing model, and obtains data processing rules.

[0245] It should be noted that the same client can connect to at least one domain on the server. For example, if client A has both data access capabilities and algorithm service capabilities, client A can connect to the data domain to upload basic data and the model domain to upload data processing models.

[0246] It is understandable that the data domain, model domain, and rule domain in the server can process data serially or in parallel.

[0247] For example, in a fault diagnosis application scenario, the data domain obtains unprocessed data from the client, performs standardization on the unprocessed data to obtain first processed data, and sends the first processed data to the model domain. The model domain processes the first processed data according to the standardized data processing model to obtain second processed data. The rule domain processes the second processed data according to the data processing rules to obtain third processed data. This third processed data is recorded as the fault diagnosis result. In this application scenario, the data domain, model domain, and rule domain process data serially.

[0248] For another example, in a data standardization application scenario, the data domain, model domain, and rule domain can each perform standardization on received external data. Specifically, the data domain standardizes the basic data received from client A and transmits the standardized data to client A; the model domain standardizes the data processing model received from client B and transmits the standardized data processing model to client B; and the rule domain standardizes the fault model received from client C and provides the corresponding execution engine to client C. In this application scenario, the data domain, model domain, and rule domain process data in parallel.

[0249] In the embodiment of the present application, the data processing system composed of the above-mentioned server and client effectively breaks down the data barriers between different enterprises in the industry, unifies the data processing standards of different enterprises in the industry, thereby overcoming the problem of difficulty in data intercommunication between enterprises and providing a reliable data foundation for industry co-construction.

[0250] An embodiment of the present application provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the data processing method in each of the above embodiments is implemented.

[0251] An embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the data processing method in the above embodiments is implemented.

[0252] This embodiment further provides a computer program product, wherein the computer-readable storage medium stores program code. When the computer program product is run on a computer, the computer is caused to execute the above-mentioned related steps to implement the data processing method in the above-mentioned embodiment.

[0253] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of modules or units is merely a logical functional division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another device, or some features can be ignored or not implemented. In addition, the mutual coupling or direct coupling or communication connection shown or discussed can be through some interface, and the indirect coupling or communication connection of devices or units can be electrical, mechanical, or other forms.

[0254] Finally, it should be noted that the above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

Claims

1. A server, characterized in that: include: Data domain, used to standardize input data; Model domain, used to standardize the definition of data processing models; The rule domain is used to define data processing rules.

2. The server according to claim 1, characterized in that: The server includes a first interface; The first interface is used to input the data to be processed into the data domain.

3. The server according to claim 1 or 2, characterized in that: The server includes a second interface; The second interface is used to output the data obtained by the data domain after the data to be processed is standardized.

4. The server according to claim 1 or 2, characterized in that: The server includes a third interface; The third interface is used to output model definition information of the data processing model.

5. The server according to any one of claims 1 to 4, characterized in that: The server includes a fourth interface; The fourth interface is used to provide an execution engine for the data processing rules.

6. The server according to any one of claims 1 to 5, characterized in that: The server includes a fifth interface, and the fifth interface is used to output the data processed by the rule domain.

7. The server according to any one of claims 1 to 6, characterized in that: The data domain includes at least two data layers, and different data layers are used to store data at different processing stages during the standardization process.

8. The server according to claim 7, characterized in that: The data layer includes at least two storage media, and different storage media are used to store different types of data.

9. A data processing method, characterized in that: Applied to the server according to any one of claims 1 to 8, the data processing method comprises: Standardize the input data to be processed; Processing the standardized data according to the data processing model; The data processed by the data processing model is processed according to the data processing rules.

10. The data processing method according to claim 9, characterized in that: Before standardizing the input data to be processed, the data processing method further includes: The data definition is sent to the client, so that the client converts the data format according to the data definition and obtains the data to be processed.

11. The data processing method according to claim 9 or 10, characterized in that: The standardization process of the input data to be processed includes: Performing data cleaning on the data to be processed to obtain cleaned data; Data aggregation is performed on the cleaned data to obtain standardized data.

12. The data processing method according to claim 11, characterized in that: The data processing method further includes: The data to be processed, the cleaned data and the standardized data are stored in different data layers respectively.

13. The data processing method according to claim 12, characterized in that: The data processing method further includes: For each of the data layers, dividing the data stored in the data layer into at least two categories; Different types of data are stored in different storage media in the data layer.

14. The data processing method according to any one of claims 9 to 13, characterized in that: The data processing model includes a plurality of operators; The data processing method further includes: Operators in the data processing model are defined according to an operator specification language.

15. The data processing method according to any one of claims 9 to 14, characterized in that: The step of processing the standardized data according to the data processing rules includes: Combining and sorting the plurality of data processing models according to the data processing rule to obtain a model sequence; The standardized data is processed according to the model sequence.

16. The data processing method according to any one of claims 9 to 15, characterized in that: The data processing method further includes: Standardize the input sample data; Set labels for the standardized sample data to obtain training data; The data processing model is trained according to the training data.

17. The data processing method according to any one of claims 9 to 15, characterized in that: The data processing method further includes: Get encrypted data from the blockchain; Decrypting the encrypted data to obtain a data directory, wherein the data directory includes a data summary of the sample data in the client; Standardizing the data directory; The data processing model is trained according to the standardized data catalog.

18. The data processing method according to claim 16, characterized in that: The step of training the data processing model according to the standardized data directory includes: Establishing a general processing model based on the standardized data directory; Sending the general processing model to a client, so that the client can train the general processing model according to the sample data corresponding to the standardized data directory to obtain intermediate data; Acquiring the intermediate data; The general processing model is updated according to the intermediate data to obtain the data processing model.

19. A data processing system, characterized in that: It comprises a server and a client; wherein the server implements the data processing method as described in any one of claims 9 to 18.

20. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the data processing method according to any one of claims 9 to 18 is implemented.

21. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the data processing method according to any one of claims 9 to 18 is implemented.

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