Data processing method and device, equipment, storage medium and computer program product

Abstract

The invention discloses a data processing method and device, equipment, a storage medium and a computer program product. The method comprises the following steps: acquiring original data sent by a first data node; packaging the original data to obtain a target data volume; the target data volume comprises one or more of the following information: data attribute information; the data use control information; data security information; and transmitting the target data volume to a data space so as to generate a data volume application corresponding to the target data volume through a data volume service in the data space, and sending the data volume application to a second data node so as to enable the second data node to perform use control on the data volume application.

Description

Technical Field

[0001] The present application relates to the field of data service technology, and in particular to a data processing method, device, equipment, storage medium and computer program product. Background Art

[0002] With the rapid development of digitalization, the demand for data circulation and services is increasing, such as the widespread application of the service system of the Data Switching Service Network (DSSN). The Data Switching Service Network is oriented to the data element circulation market, building a next-generation intensive and efficient data circulation infrastructure across industries, regions, fields, and entities, providing a low-cost, high-efficiency, and reliable circulation environment for centralized transactions on the exchange and decentralized transactions over the exchange, meeting common needs in terms of connectivity, computing power, security, and compliance, and supporting the efficient and healthy development of the national data element circulation market.

[0003] Data space is the core solution to achieve secure and reliable data circulation. It is a data element circulation space that connects multiple data providers and data demanders. The current mainstream data space solution is established with reference to the International Data Space (IDS) standard. Among them, the connector is the core component of IDS, which provides data integration, data usage control, computing and consumption capabilities, and realizes the circulation and controllable use of data between different domains through the connector.

[0004] However, each data transaction flow process requires the nodes involved in the process (including data providers and data demanders) to provide connectors in order to enter the IDS, so as to control the use of data. It can be seen that the data flow solution based on the connector technology architecture of the relevant technology requires the setting of additional components to carry out data flow, and after the development of functions such as data governance after circulation is completed, it is packaged into a data space application and distributed to the connector through the application store before it can be used. The development of data space applications is difficult and costly, and it is difficult to maximize the use value of data. Summary of the invention

[0005] To solve the technical problems existing in the related art, the embodiments of the present invention provide a data processing method, apparatus, device, storage medium and computer program product.

[0006] To achieve the above purpose, the technical solution of the embodiment of the present application is implemented as follows:

[0007] In a first aspect, an embodiment of the present application provides a data processing method, the method comprising:

[0008] Obtaining original data sent by the first data node;

[0009] The original data is packaged to obtain a target data body; the target data body includes one or more of the following information: data attribute information; data use control information; data security information;

[0010] The target data body is transmitted to the data space, so as to generate a data body application corresponding to the target data body through the data body service in the data space, and the data body application is sent to the second data node so that the second data node controls the use of the data body application.

[0011] In a second aspect, an embodiment of the present application further provides a data processing device, the device comprising:

[0012] An acquisition unit, used to acquire original data sent by the first data node;

[0013] The first processing unit is used to package the original data to obtain a target data body; the target data body includes one or more of the following information: data attribute information; data use control information; data security information;

[0014] The second processing unit is used to transmit the target data body to the data space, so as to generate a data body application corresponding to the target data body through the data body service in the data space, and send the data body application to the second data node so that the second data node can control the use of the data body application.

[0015] In a third aspect, an embodiment of the present application further provides a data processing device, comprising: a processor and a memory for storing a computer program that can be run on the processor;

[0016] Wherein, when the processor is used to run the computer program, it executes the steps of the data processing method described in the embodiment of the present application.

[0017] In a fourth aspect, an embodiment of the present application further provides a storage medium on which a computer program is stored, and when the computer program is executed by a processor, the steps of the data processing method described in the embodiment of the present application are implemented.

[0018] In a fifth aspect, an embodiment of the present application further provides a computer program product, including a computer program, which, when executed by a processor, implements the steps of the data processing method described in the embodiment of the present application.

[0019] The data processing method, device, equipment, storage medium and computer program product provided in the embodiment of the present application obtain the original data sent by the first data node; the original data is packaged and processed to obtain the target data body; the target data body includes one or more of the following information: data attribute information; data use control information; data security information; the target data body is transmitted to the data space, so as to generate a data body application corresponding to the target data body through the data body service in the data space, and the data body application is sent to the second data node, so that the second data node can use the data body application for control. The method of the embodiment of the present application is adopted, and the original data sent by the first data node is packaged and processed to obtain a target data body that can realize the data bootstrapping function (including data self-protection, self-security, and self-control). No additional components such as connectors are required to circulate data, that is, the target data body is transmitted to the data space, and after the data enters the data space, the data body service in the data space is used to generate a data body application, that is, a data space application, and the data space application is sent to the second data node for use control. It can be seen that the data service transaction function can be realized without a connector, which reduces the difficulty and cost of data space application development and gives full play to the use value of data. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 A schematic diagram of a network architecture for data flow in related technologies;

[0021] Figure 2 A schematic diagram of the interaction between technical components of the IDS solution in the related art;

[0022] Figure 3 A schematic diagram of the structure of a connector in the related art;

[0023] Figure 4 The data processing method of the present invention is shown in FIG. Figure 1 ;

[0024] Figure 5 A schematic diagram of the structure of the target data body in an embodiment of the present application;

[0025] Figure 6 A schematic diagram of the data format of the target data body in an embodiment of the present application;

[0026] Figure 7 The data processing method of the present invention is shown in FIG. Figure 2 ;

[0027] Figure 8 A schematic diagram of the structure of the data body service of an embodiment of the present application;

[0028] Fig. 9A schematic diagram of the architecture of a data body service in a data space of an embodiment of the present application;

[0029] Fig.10 A schematic diagram of the architecture of a data processing device according to an embodiment of the present application;

[0030] Fig.11 A schematic diagram of the data flow process of an embodiment of the present application;

[0031] Fig.12 A schematic diagram of the structure of a data processing device according to an embodiment of the present application;

[0032] Fig.13 Schematic diagram of the hardware structure of the data processing device according to the embodiment of the present application. DETAILED DESCRIPTION

[0033] The present application will be further described in detail below with reference to the accompanying drawings and embodiments.

[0034] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which this application belongs. The terms used herein in the specification of this application are only for the purpose of describing specific embodiments and are not intended to limit this application.

[0035] At present, the National Data Bureau has jointly issued the "Three-Year Action Plan for "Data Elements ×" (2024-2026)" with 16 departments. The purpose is to make "sleeping" data "alive", combine the basic conditions and data endowments of different industries, explore and release typical application scenarios of data elements, and use scenarios as the driving force to promote the supply and circulation of data elements, accelerate the process of data elementization, so as to better realize the value of data and build a digital economy with data as the key element.

[0036] From the perspective of circulation and utilization, it is necessary to establish a data infrastructure. In traditional trading markets, data flows and usage methods are often controlled through exclusive possession of items. The cost of copying plaintext data is close to zero. Once a transaction is reached, the data holder (that is, the data supplier, which can be understood as the seller's node) not only loses control of the data, but also bears the security risks of data transactions, which leads to data holders being "unwilling to circulate" and "daring not to circulate". Therefore, to promote data circulation, it is necessary to accelerate the construction of data infrastructure to establish a trusted circulation system, and use technologies such as secure multi-party computing (MPC) and blockchain to enable data suppliers to effectively control the purpose, method, and flow of data use, and realize the "available but invisible" and "controllable and measurable" functions of data circulation, ensure data security, prevent leakage risks, and realize data management and control.

[0037] From the perspective of security governance, new challenges are posed to data governance methods, and it is necessary to explore security governance models that adapt to the characteristics of data. The digital economy, with data as the key element, is highly innovative, widely covered, and highly permeable. While expanding and extending the connotation of traditional productivity, it also challenges the traditional regulatory model. On the one hand, the process of large-scale data circulation is also a process of multi-source and multi-party data integration. Once leaked or abused, it may lead to data leakage problems such as personal privacy and commercial secrets, affecting privacy protection and industrial development, and may even bring challenges to national security; on the other hand, the digital economy has the characteristics of cross-border integration, which challenges the traditional industry-specific supervision and territorial supervision models. Therefore, how to achieve good economic benefits at an appropriate security cost, and how to achieve high-quality development and utilization and high-level security benign interaction, how to improve regulatory effectiveness, and build a digital governance system that takes into account vitality and order, requires joint exploration by all parties.

[0038] The Digital Internet is an information service system of China Mobile based on "connection + computing power + capability". It is aimed at the data element circulation market and builds the next-generation intensive and efficient data circulation infrastructure across industries, regions, fields and entities. It provides a low-cost, high-efficiency and reliable circulation environment for on-site centralized transactions and off-site decentralized transactions, meets common needs in terms of connection, computing power, security, compliance, etc., and supports the efficient and healthy development of the national data element circulation market.

[0039] Figure 1 A schematic diagram of the network architecture for data flow in related technologies, such as Figure 1As shown in the figure, the data service node (DSN) is deployed on the data provider to realize core functions such as data source docking, DSSN private network access, and data security computing. Different forms of products can be provided according to customer needs. Among them, the DSN product forms include standard version (such as software form) and enhanced version (such as hardware form, with high performance and security requirements). DSN connects the provided data to the DSSN private network (DSSN private network is a data sharing virtual private network built based on existing network facilities to ensure the security of data transmission and service quality), and transmits the data to the data sharing platform (DSP) through the IF-2DSN management interface. The data sharing platform is used to provide services such as data access, task scheduling, reliable transmission, and secure computing, and transmits the data to the industry application platform (such as data circulation transaction platform / business platform, etc.) through the IF-1 circulation service interface to generate corresponding data applications, and transmits the data application to the data sharing platform through the IF-1 circulation service interface, and transmits the data application to the data sharing platform through the IF-2 data requirement node (DRN). The DSSN management interface sends data applications to DRN for use control. DRN is deployed on the data demand side to achieve core functions such as business system docking, DSSN private network access, visual development, and data security computing. It can provide different forms of products according to customer needs. DRN product forms include standard version (such as software form, standard deployment) and lightweight version (such as software form, lightweight deployment). It should be noted that DSN and DRN can communicate with each other through the IF-3DSN / DRN interconnection interface.

[0040] Data space is the core solution to achieve secure and reliable data circulation. It is a data element circulation space that connects multiple data providers and data demanders. Under the premise of ensuring the safety and compliance of data use, it provides "data logistics" services for the circulation of data commodities, such as providing information release, transaction negotiation, data trading, data clearing, audit supervision, data pricing, billing and settlement services for data and data products. Based on the principles of on-demand access, computing network foundation, secure sharing, open cooperation, and manageable and controllable, the data network constructs a trusted integrated computing service network to achieve five major goals: data access nearby, wide coverage of the circulation network, trusted data delivery, secure manageable and controllable, and full compliance and certification.

[0041] The current mainstream data space solutions are established with reference to the IDS standard, where IDS can be Huawei's cloud exchange data space (EDS, Exchange Data Space), Tsinghua's Qingyan data space, etc.

[0042] IDS is a virtual architecture proposed by the Fraunhofer Society in Germany that is based on a standard communication interface and enables secure data sharing. The solution was originally called Industrial Data Space, and its purpose is to resolve the conflict between data protection and data sharing in increasingly complex data services and new digital business models. Later, it was extended to corporate entities across industries and even across geographical boundaries, so it was renamed the International Data Space, and the corresponding International Data Space Association (IDSA) was established. So far, IDS has been used in Europe and Japan, and its main applications are in the industrial field, mobile travel, energy, etc.

[0043] In 2020, the Ministry of Industry and Information Technology issued the "Guiding Opinions on the Development of Industrial Big Data", which put forward the key tasks of building industrial data space, and in 2021, it issued the "Three-Year Action Plan for the Innovation and Development of Industrial Internet (2021-2023)", which once again proposed to explore the establishment of industrial data space and promote data openness and sharing. In January 2022, the white paper "Trusted Industrial Data Space System Architecture 1.0" was released at the Trusted Industrial Data Space Ecosystem Conference held by the China Academy of Information and Communications Technology, proposing the preliminary architecture and standard system of trusted industrial data space. In September 2022, Shuxin Technology, based on in-depth research on the IDSA reference architecture and combining domestic characteristics and needs, released the Domain Data Space (DDS). This is the first commercial data space product in China that is based on data sovereignty control and cross-domain, distribution, use, and connection of data. In the same year, Huawei launched its cloud service product-Cloud EDS. Cloud EDS conducts key design of data space based on the framework of "trusted, controllable, and certifiable" to create a full-stack capability for controllable data exchange. In 2023, Qingyan Technology released a new generation of data space solution SAFER (Security-Access control-Fairness-Efficiency-Regulation), which is developed based on IDS. Currently, Qingyan Technology is upgrading SAFER to support functions such as privacy computing.

[0044] Figure 2The following is a schematic diagram of the interaction between technical components of the IDS solution in the relevant technology. From the architectural perspective, IDS is actually a distributed network space connected by IDS connectors (which can be referred to as connectors) or other core components (metadata brokers, clearing houses, app stores, and vocabulary hubs) and different participants. The functions of the above core components are explained below.

[0045] The connector is the core component of IDS, which mainly provides data integration, data usage control, computing and consumption capabilities. Through the connector, data can be circulated and controlled between different domains. The core of the connector is the data usage policy engine. Figure 3 Schematic diagram of the structure of the connector in the related technology, such as Figure 3 As shown, the connector includes the following functional points: Policy Administration Point (PAP), Policy Enforcement Point (PEP), Policy Information Point (PIP), Policy Execution Point (PXP), Policy Management Point (PMP) and Policy Decision Point (PDP).

[0046] The metadata proxy is the endpoint that connectors use to register, publish, maintain and query self-descriptions. An IDS connector that provides services or data can send its self-description to the metadata proxy so that every participant can find it in the data space. The IDS metadata proxy can be understood as a phone book. In a data space, there can be multiple IDS metadata proxies, allowing the metadata proxy functionality to be distributed.

[0047] The clearing center performs clearing, billing, and auditing of usage control-related information based on all system log services.

[0048] The App Store is a secure platform for distributing applications. It supports application registration, publishing, maintenance, and query operations, as well as connector operations that provision applications to application users. Third-party applications can use the services of the connector trusted environment to implement business logic, which can be downloaded from the IDS App Store and deployed, executed, and managed on the connector.

[0049] Vocabulary Center, which provides developers of domain-specific vocabularies with tools and functionality to create, improve and publish terminology.

[0050] However, in the relevant technology, each data transaction flow process requires a connector to be provided on the side of the nodes participating in the process (including data providers and data demanders) in order to enter the IDS, so as to control the use of the data. That is, additional components need to be set up for data circulation, and the data governance and data production links such as data conversion, analysis, and calculation after circulation need to be based on the connector technology architecture. After the development of data governance and other functions is completed, it is necessary to package them into data space applications and distribute them to the connector through the application store before they can be used. The development of data space applications is difficult and costly, and it is difficult to maximize the use value of data.

[0051] Based on this, an embodiment of the present application proposes a data processing method. In various embodiments of the present application, by packaging the original data sent by the first data node, a target data body that can realize data bootstrapping functions (including data self-protection, self-security, and self-control) is obtained. Data circulation can be carried out without setting up additional components such as connectors, that is, the target data body is transmitted to the data space, and after the data enters the data space, the data body service in the data space is used to generate a data body application, namely a data space application, and the data space application is sent to the second data node for use control. It can be seen that the data service transaction function can be realized without a connector, which reduces the difficulty and cost of data space application development and gives full play to the use value of the data.

[0052] The present application embodiment provides a data processing method, which is applied to a data processing device. Figure 4 The data processing method of the present invention is shown in FIG. Figure 1 ;like Figure 4 As shown, the data processing method includes:

[0053] Step 401: Acquire original data sent by a first data node.

[0054] In the embodiment of the present application, the first data node represents a data provider, which can be understood as a party that provides data and ensures that the provided data is accurate, complete, and timely.

[0055] Here, the original data provided by the first data node is a data ontology, specifically including original data information such as unstructured data, structured data, semi-structured data, etc. Exemplarily, the unstructured data may include but is not limited to files, pictures, videos, etc.

[0056] Step 402: Packaging the original data to obtain a target data body.

[0057] In an embodiment of the present application, the target data body includes one or more of the following information: data attribute information; data usage control information; data security information.

[0058] In response to the problem that each data transaction flow process in the related technology requires a connector to be provided on the node side participating in the process in order to enter the IDS, so that the use of the data can be controlled, that is, additional components need to be set up for data circulation, the embodiment of the present application packages the original data to form a data body (corresponding to the aforementioned data attribute information), data use control (such as data access control), data security and other information (corresponding to the aforementioned target data body). In other words, the embodiment of the present application uses the data body to achieve data self-bootstrapping, including data self-protection, self-security, self-control and other functions. There is no need to set up additional components such as connectors to circulate data, that is, to transfer the target data body to the data space.

[0059] Figure 5 is a schematic diagram of the structure of the target data body in the embodiment of the present application, such as Figure 5 As shown, based on the packaging of the original data, the target data body can be obtained, wherein the target data body includes one or more of the following information: data attribute information; data usage control information; data security information. It should be noted that the data attribute information includes the unique identifier (ID, Identity) of the data, the data type, the data timestamp, the data location information, the data owner and other information, wherein the data type may include but is not limited to: file, table, row, column, cell and other types. The data usage control information includes the data usage method (including data user information), data access control information (including data classification, grading and other related information), control strategy, strategy execution and other information. The data security information includes security authentication, encryption obfuscation method, label and other information.

[0060] Figure 6 Schematic diagram of the data format of the target data body in the embodiment of the present application, such as Figure 6 As shown, the data format of the target data body may include but is not limited to: version number, serial number, data size, encryption method, security authentication, usage method, policy control, policy execution, data body ID, data type, data location, timestamp, data owner, etc. Specifically, after obtaining the original data sent by the first data node, the data processing device obtains the target data body in the above data format by serializing and encoding the original data, for example, located at Figure 5 The outermost target data body.

[0061] Based on this, in one embodiment, the packaging of the original data to obtain the target data body includes: serializing the original data to obtain serialization result data; and encoding the serialization result data to obtain the target data body.

[0062] Here, serializing the original data is actually the process of converting the original data into a storable or transmittable format, where the storable or transmittable format usually refers to a string format or a binary format. The purpose of data serialization is to enable its complex data structure to be transmitted over the network or stored on a disk (for example, to persist a complex data structure in a database or file system) while maintaining its original structure and data.

[0063] Here, after the data processing device serializes the original data and obtains the serialized result data, it performs an encoding process on the serialized result data. Encoding the serialized result data is actually a process of converting the serialized result data into a specific format of the data body to facilitate storage, transmission or further data processing, wherein further data processing includes data compression processing to reduce the volume of data, save storage space and transmission bandwidth; further data processing also includes data encryption processing to protect the security and privacy of data and prevent unauthorized access; further data processing also includes verifying the integrity and source of data through digital signature technology, and may also include detecting errors in data transmission or storage by adding checks and / or using cyclic redundancy checks (CRC) and other methods.

[0064] In actual application, the data processing device may determine the serialization format used to serialize the original data according to the usage scenario of the original data.

[0065] Based on this, in one embodiment, serializing the original data to obtain serialization result data includes: determining a serialization format based on a usage scenario of the original data; and serializing the original data based on the determined serialization format to obtain the serialization result data.

[0066] In the embodiments of the present application, the use scenarios of the original data may include but are not limited to: point-to-point transactions of the original data, point-to-multipoint transactions, etc. Here, the serialization format may include but is not limited to: lightweight data exchange format (JSON, Java Script Object Notation), Extensible Markup Language (XML, Extensible Markup Language), YAML format (a highly readable format used to express data serialization) and binary format, etc.

[0067] Step 403: The target data body is transmitted to the data space to generate a data body application corresponding to the target data body through the data body service in the data space, and the data body application is sent to the second data node so that the second data node can control the use of the data body application.

[0068] In the embodiment of the present application, the second data node represents the data consumer, that is, the data demander, which can be understood as the party using the data.

[0069] In one embodiment, the transmitting the target data body to the data space includes:

[0070] The target data body is transmitted to the data space via a digital network.

[0071] In actual application, the data processing device can divide the data body service into three types according to the usage scenario of the original data: data body adaptation service, data body processing service, and data body control service. Among them, the data body adaptation service is used for the adaptation and internal management of the data body service and the external system, including data serialization and deserialization, data encoding and decoding, data body service registration, data body service version management, etc.

[0072] Based on this, in one embodiment, the data body service includes a data body adaptation service; after the target data body is transmitted to the data space, the method further includes:

[0073] Decoding the target data body through the data body adaptation service to obtain decoded data;

[0074] The decoded data is deserialized through the data body adaptation service to obtain the original data, and the original data is distributedly stored.

[0075] Here, the process of decoding the target data body is the inverse process of encoding, that is, the encoded target data body is decoded through the data body adaptation service to obtain decoded data, that is, the decoded data is actually the data converted from the encoded target data body into its original data format.

[0076] Here, when transmitting data in the network, the original data needs to be serialized at the sending end before being sent. Correspondingly, the decoded data needs to be deserialized at the receiving end before being stored. It should be noted that deserialization is the reverse process of serialization, that is, the process of converting the decoded data of the serialized data body, such as the target data body, into the original data structure or object state. Among them, the deserialization operation enables data to be effectively exchanged between different systems, services or applications while ensuring the integrity and availability of the data.

[0077] In actual applications, in order to enable the data in the target data body to be used in circulation, storage, calculation, modeling and other scenarios, the data body processing service can read and parse the original data and related data usage policies in the target data body, and process the target data body according to the data usage policy to obtain the corresponding data processing results.

[0078] Based on this, in one embodiment, the data body service further includes a data body processing service; after the target data body is transmitted to the data space, the method further includes:

[0079] Performing data processing on the target data body through the data body processing service to obtain corresponding data processing results;

[0080] The data processing includes one of the following processing methods: data cleaning; data query; data conversion; data analysis; data mining.

[0081] Here, in actual application, in one embodiment, the data body service further includes a data body control service; the transmitting the target data body to the data space to generate a data body application corresponding to the target data body through the data body service in the data space includes:

[0082] The target data body is transmitted to the data space, so as to orchestrate the target data body service through the data body control service in the data space, so as to generate a data body application corresponding to the target data body.

[0083] Here, the service orchestration component is the core component in the data body control service, which is responsible for multiple key functions, can effectively manage the routing communication between data body services, and provide flexible traffic control and strong security guarantees. Therefore, the service orchestration component in the data body control service can be used to orchestrate the target data body service to generate a data body application corresponding to the target data body.

[0084] In actual application, in one embodiment, the target data body service is orchestrated to generate a data body application corresponding to the target data body, including:

[0085] Parsing the target data body to obtain data usage control information;

[0086] Based on the data usage control information, the target data volume service is orchestrated to generate a data volume application corresponding to the target data volume.

[0087] Here, since the target data body includes data usage control information, the data usage control information is obtained by parsing the target data body, and the control policy in the data usage control information is used to orchestrate the target data body service to generate a data body application corresponding to the target data body.

[0088] Here, the data body application can be understood as a data body product. After the data body application corresponding to the target data body is generated, the data body application can be put on the shelf in a product store (also called an application store (App Store)) and sold for users to use.

[0089] In actual application, in one embodiment, after the target data body service is orchestrated based on the data usage control information to generate a data body application corresponding to the target data body, the data body application is transmitted to the application layer of the system so that the data is settled through the clearing and billing module of the application layer.

[0090] It should be noted that the data body application can also be put on the product store for sale through the application layer, so that the data body application can be displayed through the user interface (UI, User Interface) module of the application layer, or the order management of the data can be performed through the order management module of the application layer, or the data can be audited and monitored through the audit monitoring module of the application layer.

[0091] In actual application, the data processing device divides the data body service into three types according to the usage scenario of the original data: data body adaptation service, data body processing service, and data body control service. In this way, a network composed of multiple data body services is formed in the data space. The above three service types correspond to the data body adaptation service layer, data body processing service layer, and data body control service layer in the network respectively.

[0092] In one embodiment, the method further comprises: constructing the data space;

[0093] The constructing of the data space includes: constructing the data space based on the target data body, the data body service and the data body application.

[0094] Here, the data space based on the Internet of Things is composed of target data bodies, data body services (including data body adaptation services, data body processing services, data body control services) and data body applications.

[0095] The present application also provides another data processing method, which is applied to a data processing device. Figure 7 The data processing method of the present invention is shown in FIG. Figure 2 ;like Figure 7As shown, the data processing method includes:

[0096] Step 701: Acquire original data sent by a first data node.

[0097] Step 702: Serialize the original data to obtain serialization result data.

[0098] In one embodiment, serializing the original data to obtain serialization result data includes: determining a serialization format based on a usage scenario of the original data; and serializing the original data based on the determined serialization format to obtain the serialization result data.

[0099] Step 703: Encode the serialization result data to obtain a target data body.

[0100] In an embodiment of the present application, the target data body includes one or more of the following information: data attribute information; data usage control information; data security information.

[0101] Step 704: The target data body is transmitted to the data space through the data network, and the target data body service is orchestrated through the data body control service in the data space to generate a data body application corresponding to the target data body.

[0102] In the embodiment of the present application, the target data body service is orchestrated to generate a data body application corresponding to the target data body, including:

[0103] The target data body is parsed to obtain data usage control information; and based on the data usage control information, the target data body service is orchestrated to generate a data body application corresponding to the target data body.

[0104] In one embodiment, the method further comprises: constructing the data space;

[0105] The constructing of the data space includes: constructing the data space based on the target data body, the data body service and the data body application.

[0106] In one embodiment, the data body service includes a data body adaptation service; after the target data body is transmitted to the data space, the method further includes:

[0107] Decoding the target data body through the data body adaptation service to obtain decoded data;

[0108] The decoded data is deserialized through the data body adaptation service to obtain the original data, and the original data is distributedly stored.

[0109] In one embodiment, the data body service further includes a data body processing service; after the target data body is transmitted to the data space, the method further includes:

[0110] Performing data processing on the target data body through the data body processing service to obtain corresponding data processing results;

[0111] The data processing includes one of the following processing methods: data cleaning; data query; data conversion; data analysis; data mining.

[0112] Step 705: Send the data body application to the second data node, so that the second data node performs use control on the data body application.

[0113] It should be noted that the specific processing process of the data processing device to complete the data processing has been described in detail above and will not be repeated here.

[0114] By adopting the technical solution of the embodiment of the present application, the original data sent by the first data node is packaged and processed to obtain a target data body that can realize data bootstrapping functions (including data self-protection, self-security, and self-control). Data circulation can be carried out without setting up additional components such as connectors, that is, the target data body is transmitted to the data space, and after the data enters the data space, the data body service in the data space is used to generate a data body application, namely a data space application, and the data space application is sent to the second data node for use control. It can be seen that the data service transaction function can be realized without a connector, which reduces the difficulty and cost of data space application development and gives full play to the use value of the data.

[0115] The present application is described below in conjunction with application examples.

[0116] The data circulation scheme in the related art has the following problems:

[0117] 1. In the current data space solution, every data transaction flow process requires a connector to be provided on the node side participating in the data transaction flow (such as data providers and data consumers) in order to enter the data space such as IDS, so as to control the use of data.

[0118] 2. After the circulation of data, data governance and data production links such as conversion, analysis, and calculation need to be completed based on the connector technology architecture. After the data governance and other functions are developed, they need to be packaged into data space applications and distributed to the connector through the application store before they can be used. It can be seen that the development of data space applications is difficult, the degree of reusability is low, the cost is high, and it is difficult to maximize the use value of data.

[0119] 3. Currently, connectors that include data usage control solutions must rely on external environments, such as trusted execution environments (TEEs), trusted containers, and other security environments for protection, and cannot achieve the bootstrapping functions of data security and data usage control.

[0120] 4. The current data space solution uses connectors as the underlying layer, and is mostly used in point-to-point transactions. It cannot solve the availability issues in data circulation functions such as "available but invisible" and "controllable and measurable".

[0121] In response to the above problems, this application packages the original data to form a data body (corresponding to the aforementioned target data body) with basic data attributes (corresponding to the aforementioned data attribute information), data usage control, data security and other information.

[0122] Among them, raw data refers to the data body, which may include unstructured data (such as files, pictures, videos, etc.), structured data, semi-structured data (such as parquet) and other raw data information. The basic attributes of data include the unique ID of the data, data type (such as files, tables, rows, columns, cells, etc.), data timestamp, data location information, data owner and other information. Data usage control information includes data usage methods, data access control information (such as data classification, grading and other related information), control strategies, strategy execution and other information. Data security information includes security authentication, encryption and obfuscation methods, labels and other information.

[0123] Figure 8 This is a schematic diagram of the structure of the data body service of the embodiment of the present application, such as Figure 8 As shown, the internal structure of the data body service includes the following modules: Application Programming Interface (API) service, storage engine, computing engine, and service agent.

[0124] In order to enable the data in the data body to be used in scenarios such as circulation, storage, calculation, and modeling, the data body service can read and parse the data body and related data usage policies, use the storage engine inside the data body service for data storage according to the data usage policy, and use the calculation engine inside the data body service for data analysis and calculation. It can realize the interconnection, security management, and policy execution of the data body service through the service agent, and can provide data access service functions to the outside world through API services and other forms.

[0125] According to the usage scenario of the original data, data body services can be divided into three types, namely data body adaptation service, data body processing service, and data body control service. The following describes these three types of data body services respectively.

[0126] Data body adaptation service: This service is used for the adaptation of data body services and external systems and internal management, including data serialization and deserialization, data encoding and decoding, data body service registration, data body service version management, etc.

[0127] Here, data serialization and deserialization are two key concepts in data body adaptation services, which are used in data storage, transmission and communication processes, including:

[0128] Network communication: When transmitting data in the network, the original data needs to be serialized before being sent at the sending end, and the data needs to be deserialized at the receiving end.

[0129] Data storage: When data is persistently stored in a database or file system, it is usually necessary to serialize and deserialize the data before storage.

[0130] Distributed systems: In distributed systems, when remote calls are made between data services, request and response data need to be serialized.

[0131] Data serialization is the process of converting raw data or its object state into a storable or transmittable format (usually a string or binary format). The purpose of data serialization is to enable complex data structures to be transmitted over the network or stored on disk while maintaining their original structure and data. Depending on the usage scenario, serialization formats include JSON, XML, YAML, binary format, etc.

[0132] Data deserialization is the reverse process of data serialization, that is, the process of converting the serialized data body into the original data structure or object state. Data deserialization enables data to be effectively exchanged between different systems, services or applications while ensuring data integrity and availability.

[0133] Data encoding and decoding is the process of encoding and decoding data, including:

[0134] Encoding: The process of converting data into a specific format for storage, transmission or further processing. Further processing includes data compression to reduce the size of data and save storage space and transmission bandwidth; data encryption to protect data security and privacy and prevent unauthorized access; verifying the integrity and source of data through digital signature technology; detecting errors in data transmission or storage by adding checksums and / or using methods such as CRC, etc.

[0135] Decoding: The reverse process of encoding, that is, the process of converting the encoded data body into its original data format.

[0136] Data body processing service: This service is used to read the original data and data usage policies in the data body, and process the data according to the data usage policies, such as data cleaning, data query, data conversion, data analysis and data mining.

[0137] (1) Data cleaning: Correct or delete erroneous data records through data cleaning techniques, such as removing duplicates, correcting format errors, and filling missing values; implement data verification rules to ensure the accuracy and completeness of new data.

[0138] (2) Data query: The key function of efficiently retrieving, filtering, sorting, and analyzing information from data bodies or data stores, usually including building conditional queries, applying logical operators, performing grouping and aggregation operations, merging multiple data sources, deduplication, paging, full-text search, regular expression matching, time series and spatial data query, data pivoting, and result caching.

[0139] (3) Data transformation: Data integration and merging of data from different sources. Data transformation redefines the organization of data elements through data mapping to adapt to a specific data model or system.

[0140] (4) Data analysis: including calculation of mean, median, mode, variance, standard deviation, etc. to describe the basic characteristics of the data; inferential statistics, such as hypothesis testing and confidence intervals, to infer population characteristics from sample data; correlation and regression analysis to determine the relationship between variables; time series analysis to process and predict trends and patterns in time series data; and data visualization to present data through charts and graphs to make the analysis results easier to understand and interpret.

[0141] (5) Data mining: It is the process of extracting (mining) valuable information or knowledge from large amounts of data through algorithms and statistical models. This information or knowledge can be used to predict future trends, identify patterns, establish associations, and make decisions.

[0142] Data body control service, mainly including service orchestration component, service policy control component, service configuration component, authentication component, and service monitoring component; among them,

[0143] The service orchestration component is the core component of the data body control service. It is responsible for a variety of key functions, can effectively manage the routing communication between data body services, and provide flexible traffic control and strong security. It mainly includes the following functional modules:

[0144] Service registration: When a service instance is started, it registers its network location (such as IP address and port number) and metadata (such as service version, function description, etc.) with the service registration center.

[0145] Service discovery: This module integrates with the underlying service discovery mechanism of K8s (such as Kubernetes) to monitor the registration and deregistration of services and ensure that traffic can be routed to the correct target.

[0146] Routing management: Dynamically discover service instances and incorporate them into routing decisions, define the flow path of requests in the service network, including entry points, exit points, and intermediate service jumps, and manage and optimize the network topology between services.

[0147] Traffic management: Supports complex traffic management functions, including traffic splitting, A / B testing, canary deployment, traffic mirroring, and fault injection.

[0148] Load balancing: Performs load balancing between service instances and dynamically updates load balancing rules based on configured policies to achieve balanced distribution of requests.

[0149] Dependency management: Tracking dependencies between services so that services can be properly managed and coordinated when they are updated or redeployed.

[0150] Version management: Supports multi-version registration of services, allowing clients to select specific versions of services based on their needs, and manages smooth updates and version rolling of services to reduce service interruptions.

[0151] Security: Responsible for managing the Transport Layer Security (TLS) certificate of the data service proxy, achieving two-way authentication and encrypted communication between services, and ensuring communication security.

[0152] Service policy control component: manages the internal policies of data bodies and the security policies of data body services, including access control and authentication policies, usage policies, etc. It mainly includes the following functional modules:

[0153] Policy control: Responsible for implementing the access control policy of data services, ensuring that the communication between services complies with the established security policy, and checking the data usage control policy.

[0154] Policy management: used to manage usage restriction-related policies, covering the entire policy lifecycle, including policy instantiation, deployment, and update. In addition to the configuration of data service, it also includes the configuration-related functions of data usage control policies, that is, the definition of usage policy rules: who can access the data, what the data can be used for, data usage restrictions, and other 21 data usage policies.

[0155] Policy execution: Perform some additional actions based on the decision rules, such as sending an email after the data is used, writing to a specific log system, etc.

[0156] Policy information: provides missing information for relevant decisions and can also be used to obtain contextual information about the relevant behaviors of the interception system, such as data flow information, geographic location of the requesting device, etc.

[0157] Policy decision: According to the policy specified by policy management, call policy information to obtain relevant information, perform policy evaluation on events and trigger policies to perform additional operations.

[0158] Policy auditing: Collects policy log data, authorization data, and monitoring data between services to provide observability for the system and synchronizes them to the upper-level clearing and auditing center.

[0159] The service configuration component is responsible for verifying, collecting, processing and distributing the configuration of data services. It is used to simplify the management of system configuration, improve the reliability and flexibility of configuration, reduce configuration errors and inconsistencies, and improve system stability and maintainability. It mainly includes the following functional modules:

[0160] Configuration templates: Responsible for generating configurations using templates. These templates can be customized to suit different deployment requirements.

[0161] Configuration processing: Responsible for processing configurations, including validation, parsing, conversion, and standardization.

[0162] Configuration distribution: Responsible for distributing the processed configuration to other components, such as service discovery and orchestration components and service monitoring components.

[0163] Configuration monitoring: responsible for monitoring configuration changes and updating configuration information in real time.

[0164] Authentication component: responsible for managing the keys and certificates of data and data services, ensuring the communication security of data and data services; responsible for verifying the identity of data and data services, and authorizing them to access specific resources or perform specific operations, mainly including the following functional modules:

[0165] Certificate issuance management: Automatically issue TLS certificates for all services and data in the service network, and be responsible for the lifecycle management of the TLS certificates.

[0166] Authentication: Generate identity credentials for each service in the service network, ensure the verifiability and security of inter-service communication, and provide authentication services.

[0167] Security configuration distribution: Distribute security configuration and certificates to the agents of the data body services to ensure that they can communicate securely with other services.

[0168] Auditing and monitoring: Supports auditing and monitoring of security configurations to help operation and maintenance personnel understand the security status of the service network.

[0169] The service monitoring component includes monitoring data collection and synchronization. It is specifically used to collect log data, authorization data, monitoring data, and dialing data between services, provide observable data for the system, and synchronize it to the upper-level clearing and audit center.

[0170] Fig. 9 This is a schematic diagram of the architecture of the data body service in the data space of the embodiment of the present application, such as Fig. 9 As shown, a network consisting of multiple data body services is formed in the data space. The data body services can be divided into three types, namely, data body adaptation service, data body processing service, and data body control service; among them, the data body adaptation service is used for data serialization and deserialization, data encoding and decoding, etc. The data body control service mainly includes service orchestration components, service policy control components, service configuration components, authentication components, and service monitoring components. The service orchestration components include but are not limited to the following functional modules: service registration, service discovery, routing management, and traffic management; the service policy control components include but are not limited to the following functional modules: policy decision, policy information, policy management, and policy execution; the service configuration components include but are not limited to the following functional modules: configuration templates, configuration processing, configuration distribution, and configuration monitoring; the authentication components include but are not limited to the following functional modules: auditing and monitoring, identity authentication, certificate issuance management, and security configuration distribution. It should be noted that the description of the above functional modules can refer to the above understanding and will not be repeated here.

[0171] Fig.10 Schematic diagram of the architecture of the data processing device according to the embodiment of the present application. Fig.10 As shown, the data processing device includes from bottom to top: equipment and operating environment layer, cloud service infrastructure layer, data body adaptation service layer, data body processing service layer, data body control service layer, and application layer, wherein the equipment set in the equipment and operating environment layer can be a physical machine, a virtual machine, etc., and the operating environment can be a secure environment such as TEE, a trusted container, etc.; the cloud service infrastructure layer includes a variety of cloud service infrastructures, such as infrastructure for microservice management, container management, task scheduling, resource scheduling, data storage, and stream computing engine; the data body adaptation service layer includes but is not limited to the following functional modules: data serialization and deserialization, data encoding and decoding; the data body processing service layer includes but is not limited to the following functional modules: data cleaning, data query, data conversion, data aggregation, data statistics, and data mining; the data body control service layer includes but is not limited to the following functional modules: service orchestration, policy control, service configuration, authentication, and service monitoring; the application layer includes but is not limited to the following functional modules: product store, order management, clearing and billing, audit monitoring, and UI display.

[0172] Here, through the orchestration of the data body service layer, any data usage needs can be simply realized, and settlement can be performed through the clearing and billing module of the application layer. At the same time, the orchestrated data body service can be formed into a data body product (corresponding to the aforementioned data body application), and the data body product can be put on the product store for sale.

[0173] Based on the architecture of the above-mentioned data processing device, a data space based on the Internet of Things is formed by data bodies, data body services, and data body applications. Fig.11 Schematic diagram of the data flow process of the embodiment of the present application, such as Fig.11 As shown, first, the original data is serialized, encoded, and processed to form a data body (corresponding to the aforementioned target data body). The data body adaptation service transmits the data body to the data space through the data network, and deserializes the data body for distributed storage, or the data body processing service can clean, query, convert, count, and process the data body. These data body services are arranged by the control layer service (corresponding to the data body control service) to form a data body application for user use. Among them, the data body application can be displayed in the UI through the data screen. The data body application can be a business intelligence (BI, Business Intelligence) application. After the data body application is generated, the data body application is sent to the client to perform data governance such as data conversion, analysis, and calculation.

[0174] Compared with the methods of the related art, the solution of the present application has the following beneficial effects:

[0175] (1) Using data bodies can achieve data self-bootstrapping, including data security, data usage control, access control, etc., and data can be circulated without the need for additional components.

[0176] (2) The use of data body services realizes the functions of data entering the data space and becoming data services, data service orchestration and use, and data service transactions, so as to solve the problem of flexible data use, low cost, and give full play to the use value of data.

[0177] In order to implement the data processing method of the embodiment of the present application, the embodiment of the present application also provides a data processing device, Fig.12 Schematic diagram of the structure of the data processing device according to the embodiment of the present application. Fig.12 As shown, the data processing device includes:

[0178] An acquiring unit 121 is configured to acquire original data sent by the first data node;

[0179] The first processing unit 122 is used to package the original data to obtain a target data body; the target data body includes one or more of the following information: data attribute information; data use control information; data security information;

[0180] The second processing unit 123 is used to transmit the target data body to the data space, so as to generate a data body application corresponding to the target data body through the data body service in the data space, and send the data body application to the second data node so that the second data node can control the use of the data body application.

[0181] In one embodiment, the first processing unit 122 includes a serialization subunit and an encoding subunit; wherein,

[0182] The serialization subunit is used to serialize the original data to obtain serialization result data;

[0183] The encoding subunit is used to encode the serialization result data to obtain the target data body.

[0184] In one embodiment, the serialization subunit is specifically used for:

[0185] Determine a serialization format based on a usage scenario of the original data;

[0186] The original data is serialized based on the determined serialization format to obtain the serialization result data.

[0187] In one embodiment, the second processing unit 123 is specifically configured to:

[0188] The target data body is transmitted to the data space via a digital network.

[0189] In one embodiment, the data body service includes a data body adaptation service; the device further includes: a decoding unit, a deserialization unit and a storage unit; wherein,

[0190] The decoding unit is configured to decode the target data body through the data body adaptation service to obtain decoded data after the second processing unit 123 transmits the target data body to the data space;

[0191] The deserialization unit is used to deserialize the decoded data through the data body adaptation service to obtain the original data;

[0192] The storage unit is used to perform distributed storage on the original data.

[0193] In one embodiment, the data body service further includes a data body processing service; the device further includes: a third processing unit; wherein,

[0194] The third processing unit is configured to perform data processing on the target data body through the data body processing service to obtain a corresponding data processing result after the second processing unit 123 transmits the target data body to the data space;

[0195] The data processing includes one of the following processing methods: data cleaning; data query; data conversion; data analysis; data mining.

[0196] In one embodiment, the data body service further includes a data body control service; the second processing unit 123 is specifically configured to:

[0197] The target data body is transmitted to the data space, so as to orchestrate the target data body service through the data body control service in the data space, so as to generate a data body application corresponding to the target data body.

[0198] In another embodiment, the second processing unit 123 is further specifically configured to:

[0199] Parsing the target data body to obtain data usage control information;

[0200] Based on the data usage control information, the target data volume service is orchestrated to generate a data volume application corresponding to the target data volume.

[0201] In one embodiment, the device further comprises: a construction unit; wherein,

[0202] The construction unit is used to construct the data space;

[0203] The building block is specifically used for:

[0204] The data space is constructed based on the target data body, the data body service and the data body application.

[0205] In actual application, the acquisition unit 121 may be implemented by a communication interface in a data processing device; the first processing unit 122 and the second processing unit 123 may be implemented by a processor in the data processing device.

[0206] It should be noted that: when the data processing device provided in the above embodiment performs data processing, only the division of the above program modules is used as an example. In actual applications, the above processing can be assigned to different program modules as needed, that is, the internal structure of the device is divided into different program modules to complete all or part of the processing described above. In addition, the data processing device provided in the above embodiment and the data processing method embodiment belong to the same concept, and the specific implementation process is detailed in the data processing method embodiment, which will not be repeated here.

[0207] Based on the hardware implementation of the above program modules, and in order to implement the data processing method of the embodiment of the present application, the embodiment of the present application also provides a data processing device, Fig.13 Schematic diagram of the hardware structure of the data processing device of the embodiment of the present application. Fig.13 As shown, the data processing device 130 includes:

[0208] Communication interface 131, capable of exchanging information with other devices;

[0209] The processor 132 is connected to the communication interface 131 to implement information interaction with other devices and is used to execute the above-mentioned data processing method when running a computer program, and the computer program is stored in the memory 133.

[0210] Specifically, the communication interface 131 is used to obtain the original data sent by the first data node;

[0211] The processor 132 is used to package the original data to obtain a target data body; the target data body includes one or more of the following information: data attribute information; data usage control information; data security information; the target data body is transmitted to the data space to generate a data body application corresponding to the target data body through the data body service in the data space, and the data body application is sent to the second data node so that the second data node can control the use of the data body application.

[0212] In one embodiment, the processor 132 is specifically configured to:

[0213] Serializing the original data to obtain serialized result data;

[0214] The serialization result data is encoded to obtain the target data body.

[0215] In one embodiment, the processor 132 is specifically configured to:

[0216] Determine a serialization format based on a usage scenario of the original data;

[0217] The original data is serialized based on the determined serialization format to obtain the serialization result data.

[0218] In one embodiment, the processor 132 is specifically configured to:

[0219] The target data body is transmitted to the data space via a digital network.

[0220] In one embodiment, the data body service includes a data body adaptation service; the processor 132 is further configured to decode the target data body through the data body adaptation service to obtain decoded data after the target data body is transmitted to the data space;

[0221] The decoded data is deserialized through the data body adaptation service to obtain the original data, and the original data is distributedly stored.

[0222] In one embodiment, the data body service further includes a data body processing service; the processor 132 is further configured to perform data processing on the target data body through the data body processing service after the target data body is transmitted to the data space, to obtain a corresponding data processing result;

[0223] The data processing includes one of the following processing methods: data cleaning; data query; data conversion; data analysis; data mining.

[0224] In one embodiment, the data body service further includes a data body control service; the processor 132 is specifically configured to:

[0225] The target data body is transmitted to the data space, so as to orchestrate the target data body service through the data body control service in the data space, so as to generate a data body application corresponding to the target data body.

[0226] In one embodiment, the processor 132 is specifically configured to:

[0227] Parsing the target data body to obtain data usage control information;

[0228] Based on the data usage control information, the target data volume service is orchestrated to generate a data volume application corresponding to the target data volume.

[0229] In one embodiment, the processor 132 is further configured to construct the data space;

[0230] The processor 132 is specifically configured to:

[0231] The data space is constructed based on the target data body, the data body service and the data body application.

[0232] It should be noted that the specific processing process of the communication interface 131 and the processor 132 can be understood by referring to the above data processing method.

[0233] Of course, in actual application, the various components in the data processing device 130 are coupled together through the bus system 134. It is understandable that the bus system 134 is used to realize the connection and communication between these components. In addition to the data bus, the bus system 134 also includes a power bus, a control bus, and a status signal bus. However, for the sake of clarity, Fig.13 Various buses are labeled as bus system 134 .

[0234] The memory 133 in the embodiment of the present application is used to store various types of data to support the operation of the data processing device 130. Examples of such data include: any computer program used to operate on the data processing device 130.

[0235] The data processing method disclosed in the above embodiment of the present application can be applied to the processor 132, or implemented by the processor 132. The processor 132 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above data processing method can be completed by the hardware integrated logic circuit or software instructions in the processor 132. The above-mentioned processor 132 may be a general-purpose processor, a digital signal processor (DSP, Digital Signal Processor), or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. The processor 132 can implement or execute the various data processing methods, steps and logic block diagrams disclosed in the embodiments of the present application. A general-purpose processor may be a microprocessor or any conventional processor, etc. In combination with the steps of the data processing method disclosed in the embodiment of the present application, it can be directly embodied as a hardware decoding processor to execute, or it can be executed by a combination of hardware and software modules in the decoding processor. The software module can be located in a storage medium, which is located in the memory 133, and the processor 132 reads the information in the memory 133 and completes the steps of the aforementioned data processing method in combination with its hardware.

[0236] In an exemplary embodiment, the data processing device 130 can be implemented by one or more application specific integrated circuits (ASIC), DSP, programmable logic device (PLD), complex programmable logic device (CPLD), field programmable gate array (FPGA), general processor, controller, microcontroller (MCU), microprocessor, or other electronic components to execute the aforementioned data processing method.

[0237] It can be understood that the memory 133 of the embodiment of the present application can be a volatile memory or a non-volatile memory, and can also include both volatile and non-volatile memories. Among them, the non-volatile memory can be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), a magnetic random access memory (FRAM), a flash memory, a magnetic surface memory, an optical disc, or a compact disc read-only memory (CD-ROM); the magnetic surface memory can be a disk memory or a tape memory. The volatile memory can be a random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of RAM are available, such as static random access memory (SRAM), synchronous static random access memory (SSRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDRSDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM, SyncLink Dynamic Random Access Memory), and direct RAMbus random access memory (DRRAM, Direct Rambus Random Access Memory).The memory 133 described in the embodiments of the present application is intended to include but is not limited to these and any other suitable types of memories.

[0238] In an exemplary embodiment, the present application also provides a storage medium, namely a computer storage medium, specifically a computer-readable storage medium, for example, a memory 133 storing a computer program, and the computer program can be executed by a processor 132 in a data processing device 130 to complete the steps of the data processing method described in the above embodiment of the present application. The computer-readable storage medium can be a memory such as FRAM, ROM, PROM, EPROM, EEPROM, Flash Memory, magnetic surface storage, optical disk, or CD-ROM.

[0239] In an exemplary embodiment, the present application also provides a computer program product, including a computer program, which can be executed by the processor 132 in the data processing device 130 to complete the steps of the data processing method described in the above-mentioned embodiment of the present application.

[0240] It should be noted that: "first", "second", "third", etc. are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence.

[0241] In addition, the technical solutions described in the embodiments of the present application can be combined arbitrarily without conflict.

[0242] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A data processing method, characterized in that: The method comprises: Obtaining original data sent by the first data node; The original data is packaged to obtain a target data body; the target data body includes one or more of the following information: data attribute information; data use control information; data security information; The target data body is transmitted to the data space, so as to generate a data body application corresponding to the target data body through the data body service in the data space, and the data body application is sent to the second data node so that the second data node controls the use of the data body application.

2. The method according to claim 1, characterized in that The packaging process of the original data to obtain the target data body includes: Serializing the original data to obtain serialized result data; The serialization result data is encoded to obtain the target data body.

3. The method according to claim 2, characterized in that The serializing the original data to obtain serialization result data includes: Determine a serialization format based on a usage scenario of the original data; The original data is serialized based on the determined serialization format to obtain the serialization result data.

4. The method according to any one of claims 1 to 3, characterized in that: The step of transmitting the target data body to the data space comprises: The target data body is transmitted to the data space via a digital network.

5. The method according to claim 1, characterized in that The data body service includes a data body adaptation service; after the target data body is transmitted to the data space, the method further includes: Decoding the target data body through the data body adaptation service to obtain decoded data; The decoded data is deserialized through the data body adaptation service to obtain the original data, and the original data is distributedly stored.

6. The method according to claim 1, characterized in that The data body service also includes a data body processing service; after the target data body is transmitted to the data space, the method further includes: Performing data processing on the target data body through the data body processing service to obtain corresponding data processing results; The data processing includes one of the following processing methods: data cleaning; data query; data conversion; data analysis; data mining.

7. The method according to claim 1, characterized in that The data body service also includes a data body control service; The step of transmitting the target data body to the data space so as to generate a data body application corresponding to the target data body through a data body service in the data space includes: The target data body is transmitted to the data space, so as to orchestrate the target data body service through the data body control service in the data space, so as to generate a data body application corresponding to the target data body.

8. The method according to claim 7, characterized in that The orchestration of the target data body service to generate a data body application corresponding to the target data body includes: Parsing the target data body to obtain data usage control information; Based on the data usage control information, the target data volume service is orchestrated to generate a data volume application corresponding to the target data volume.

9. The method according to claim 1, characterized in that: The method further comprises: constructing the data space; The constructing the data space includes: The data space is constructed based on the target data body, the data body service and the data body application.

10. A data processing device, characterized in that: The device comprises: An acquisition unit, used to acquire original data sent by the first data node; The first processing unit is used to package the original data to obtain a target data body; the target data body includes one or more of the following information: data attribute information; data use control information; data security information; The second processing unit is used to transmit the target data body to the data space, so as to generate a data body application corresponding to the target data body through the data body service in the data space, and send the data body application to the second data node so that the second data node can control the use of the data body application.

11. A data processing device, characterized in that: include: a processor and a memory for storing a computer program capable of running on said processor; Wherein, when the processor is used to run the computer program, it executes the steps of the method described in any one of claims 1 to 9.

12. A storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 9 are implemented.

13. A computer program product, comprising a computer program, characterized in that The computer program implements the steps of the method according to any one of claims 1 to 9 when executed by a processor.

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