Blockchain-based storage data generation method, device and computer equipment

Abstract

The application relates to a blockchain-based evidence storage data generation method, device and computer equipment. The method comprises the following steps: obtaining a target business document, and determining a target on-chain format conversion template corresponding to the target business document; determining a respective business field type corresponding to each business field, and determining a respective mapping mode corresponding to each business field according to a mapping relationship in the target on-chain format conversion template and each business field type; respectively mapping each business field according to the respective mapping mode corresponding to each business field, to obtain at least one evidence storage field; and obtaining target evidence storage data with a standard on-chain format according to the at least one evidence storage field. The method can improve the accuracy of generating evidence storage data.

Description

Technical Field

[0001] This application relates to the field of blockchain technology, and in particular to a blockchain-based method, apparatus, and computer device for generating evidence-based data. Background Technology

[0002] With the development of blockchain technology, business systems of different enterprises can use business documents as evidence and upload them to the blockchain, which is known as blockchain-based evidence storage. Once stored, these business documents cannot be tampered with, are easy to share with all parties, and can serve as electronic evidence in case of disputes, achieving end-to-end trustworthiness.

[0003] Currently, integrating business systems with blockchain systems requires using SDKs or APIs supported by the underlying blockchain framework. Business systems then need to redevelop different heterogeneous business documents to meet the requirements for smart contracts and blockchain interaction and integration. However, existing blockchain underlying systems are quite large and complex, and business systems and blockchain systems often use different development languages, development standards, and data storage methods, making system development very difficult.

[0004] Therefore, for business documents with significant structural differences, the problem that this application needs to solve is how to accurately obtain evidence data with a standard on-chain format while reducing the development process of the business system, thereby ensuring the data integration between the business system and the blockchain system. Summary of the Invention

[0005] Therefore, it is necessary to provide a method, apparatus, computer equipment, computer-readable storage medium, and computer program product for generating evidence data that can improve the accuracy of data uploading to the blockchain, in response to the above-mentioned technical problems.

[0006] Firstly, this application provides a method for generating evidence-based data using blockchain. The method includes:

[0007] Obtain the target business document and determine the target on-chain format conversion template corresponding to the target business document; the target business document includes multiple business fields; the target on-chain format conversion template includes the mapping relationship between business field types and evidence storage field types;

[0008] Determine the business field type corresponding to each of the business fields, and determine the mapping method corresponding to each of the business fields based on each business field type and the mapping relationship;

[0009] Based on the mapping method corresponding to each of the business fields, each of the business fields is mapped to obtain at least one evidence storage field;

[0010] Based on the at least one evidence storage field, target evidence storage data with a standard on-chain format is obtained; the target evidence storage data is used to be uploaded to the blockchain.

[0011] In one embodiment, before obtaining the target business document, the method further includes: displaying a business association interface; the business association interface includes multiple business documents and multiple on-chain format conversion templates; in response to an association operation on the multiple business documents and multiple on-chain format conversion templates, obtaining the business association relationship between the business documents and the on-chain format conversion templates; determining the target on-chain format conversion template corresponding to the target business document includes: if the target business document is obtained, determining the target on-chain format conversion template corresponding to the target business document based on the business association relationship.

[0012] In one embodiment, the target on-chain format conversion template includes on-chain conditions; the on-chain conditions include multiple sub-conditions; each sub-condition has a logical relationship with the others; after determining the target on-chain format conversion template corresponding to the target business document, the method further includes: determining the field value corresponding to each business field, and determining the target field value corresponding to each sub-condition; filtering the target field value corresponding to each sub-condition according to each sub-condition to obtain multiple filtering results; associating the multiple filtering results according to the logical relationship between each sub-condition to obtain an association result; when the association result is true, the target business document is used as the filtered target business document.

[0013] In one embodiment, the logical association relationship includes at least one of logical AND and logical OR; the filtering result includes any one of true or false; the step of associating multiple filtering results according to the logical association relationship between each of the sub-conditions to obtain an association result includes: determining the current sub-condition and the adjacent sub-conditions adjacent to the current sub-condition; associating the filtering result corresponding to the current sub-condition and the filtering result corresponding to the adjacent sub-condition according to the logical association relationship between the current sub-condition and the adjacent sub-condition to obtain an association result; taking the adjacent sub-condition as the new current sub-condition, taking the association result as the filtering result of the new current sub-condition, and returning to the step of determining the adjacent sub-conditions adjacent to the current sub-condition to continue until all filtering results are associated.

[0014] In one embodiment, determining the mapping method corresponding to each business field based on each business field type and the mapping relationship includes: for each of the multiple business fields, determining the evidence storage field type corresponding to the current business field based on the mapping relationship and the business field type of the current business field; and determining the mapping method corresponding to the current business field based on the evidence storage field type.

[0015] In one embodiment, determining the evidence storage field type corresponding to the current business field based on the mapping relationship and the business field type of the current business field includes: when the business field type is at least one of string type, numeric type, basic data type, and entry type, determining the evidence storage field type corresponding to the current business field as a normal type based on the mapping relationship; when the business field type is at least one of multi-select type, attachment field, and special type, determining the evidence storage field type corresponding to the current business field as a specified type based on the mapping relationship.

[0016] In one embodiment, determining the mapping method corresponding to the current business field based on the evidence storage field type includes: when the evidence storage field type is a normal type, determining the mapping method corresponding to the current business field as an automatic conversion method; mapping each business field according to its respective mapping method to obtain at least one evidence storage field includes: mapping the current business field according to the automatic conversion method to obtain a current evidence storage field corresponding to the evidence storage field type.

[0017] In one embodiment, determining the mapping method corresponding to the current business field based on the evidence storage field type includes: when the evidence storage field type is a specified type, determining the mapping method corresponding to the current business field as a value conversion method; mapping each business field according to its respective mapping method to obtain at least one evidence storage field includes: mapping each business field according to the value conversion method to obtain at least one evidence storage field.

[0018] In one embodiment, the value conversion method includes either concatenation processing or sequence processing; the step of mapping each of the business fields according to the value conversion method to obtain at least one evidence storage field includes: determining a plurality of first business fields whose mapping method is the value conversion method; when the value conversion method is concatenation processing, adding a separator between each of the first business fields and concatenating the first business fields with the separator added to obtain an evidence storage field; when the value conversion method is sequence processing, serializing each of the first business fields according to a preset standard data format to obtain an evidence storage field.

[0019] In one embodiment, determining the mapping method corresponding to the current business field based on the evidence field type includes: when the evidence field type is a specified type and has a manual configuration identifier, determining the mapping method corresponding to the current business field as a hash processing method; mapping each business field according to its respective mapping method to obtain at least one evidence field includes: in response to a selection operation for the plurality of business fields, determining the selected plurality of second business fields; serializing each second business field according to a preset standard data format to obtain a business string; determining the hash value corresponding to the business string, and using the hash value as an evidence field.

[0020] In one embodiment, the target on-chain format conversion template includes a data permission identifier; obtaining target evidence data with a standard on-chain format based on the at least one evidence field includes: synthesizing each of the evidence fields to obtain candidate evidence data, and determining an identity identifier corresponding to the target business document based on the data permission identifier; when a target digital identity matching the identity identifier is found in a preset database, the candidate evidence data is used as evidence data with a standard on-chain format; the above method further includes: associating the target digital identity with the target evidence data, and uploading the target evidence data to the blockchain through the target digital identity.

[0021] In one embodiment, the method further includes: when receiving an on-chain task, determining the on-chain method in the on-chain task; when the on-chain method is a timed batch method, determining all target business documents generated within a preset on-chain time period; determining the target evidence storage data corresponding to each target business document, and on-chaining each target evidence storage data to the blockchain by calling a preset interface.

[0022] In one embodiment, the above method further includes: when the on-chain method is an event-triggered method, listening to multiple business events; the business events include at least one of business document approval, business document push-down, and business document closure; when a target business event is detected, determining the target business document corresponding to the target business event; determining the target evidence data corresponding to the target business document, and on-chaining the target evidence data to the blockchain by calling a preset interface.

[0023] Secondly, this application also provides a blockchain-based device for generating evidence storage data. The device includes:

[0024] The business document acquisition module is used to acquire the target business document and determine the target on-chain format conversion template corresponding to the target business document; the target business document includes multiple business fields; the target on-chain format conversion template includes the mapping relationship between business field types and evidence storage field types;

[0025] The mapping method determination module is used to determine the business field type corresponding to each of the business fields, and to determine the mapping method corresponding to each of the business fields based on each business field type and the mapping relationship;

[0026] The evidence storage data determination module is used to map each of the business fields according to the mapping method corresponding to each of the business fields to obtain at least one evidence storage field; and to obtain target evidence storage data with a standard on-chain format according to the at least one evidence storage field; the target evidence storage data is used to be uploaded to the blockchain.

[0027] Thirdly, this application also provides a computer device. The computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to perform the following steps:

[0028] Obtain the target business document and determine the target on-chain format conversion template corresponding to the target business document; the target business document includes multiple business fields; the target on-chain format conversion template includes the mapping relationship between business field types and evidence storage field types;

[0029] Determine the business field type corresponding to each of the business fields, and determine the mapping method corresponding to each of the business fields based on each business field type and the mapping relationship;

[0030] Based on the mapping method corresponding to each of the business fields, each of the business fields is mapped to obtain at least one evidence storage field;

[0031] Based on the at least one evidence storage field, target evidence storage data with a standard on-chain format is obtained; the target evidence storage data is used to be uploaded to the blockchain.

[0032] Fourthly, this application also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program, which, when executed by a processor, performs the following steps:

[0033] Obtain the target business document and determine the target on-chain format conversion template corresponding to the target business document; the target business document includes multiple business fields; the target on-chain format conversion template includes the mapping relationship between business field types and evidence storage field types;

[0034] Determine the business field type corresponding to each of the business fields, and determine the mapping method corresponding to each of the business fields based on each business field type and the mapping relationship;

[0035] Based on the mapping method corresponding to each of the business fields, each of the business fields is mapped to obtain at least one evidence storage field;

[0036] Based on the at least one evidence storage field, target evidence storage data with a standard on-chain format is obtained; the target evidence storage data is used to be uploaded to the blockchain.

[0037] Fifthly, this application also provides a computer program product. The computer program product includes a computer program that, when executed by a processor, performs the following steps:

[0038] Obtain the target business document and determine the target on-chain format conversion template corresponding to the target business document; the target business document includes multiple business fields; the target on-chain format conversion template includes the mapping relationship between business field types and evidence storage field types;

[0039] Determine the business field type corresponding to each of the business fields, and determine the mapping method corresponding to each of the business fields based on each business field type and the mapping relationship;

[0040] Based on the mapping method corresponding to each of the business fields, each of the business fields is mapped to obtain at least one evidence storage field;

[0041] Based on the at least one evidence storage field, target evidence storage data with a standard on-chain format is obtained; the target evidence storage data is used to be uploaded to the blockchain.

[0042] The aforementioned blockchain-based method, apparatus, computer equipment, storage medium, and computer program product for generating evidence storage data acquires the target business document and determines the target on-chain format conversion template corresponding to the target business document. It then determines the business field type for each business field and, based on the mapping relationship between each business field type and the target on-chain format conversion template, determines the mapping method for each business field. By mapping each business field according to its corresponding mapping method, at least one evidence storage field is obtained. Thus, target evidence storage data with a standard on-chain format can be obtained based on at least one evidence storage field. Since this application flexibly maps business fields of different business field types based on different mapping methods after determining the target on-chain format conversion template, it can accurately obtain target evidence storage data with a standard on-chain format. Furthermore, since it eliminates the need for redeveloping heterogeneous business documents, it uses a low-code approach to map the target business document and upload the mapped target evidence storage data to the blockchain, reducing the difficulty of blockchain evidence storage for different business documents.

[0043] Furthermore, since the low-code approach enables rapid reuse, this application can achieve enterprise-level standardized management of the mapping process when a large number of business documents need to be uploaded to the blockchain, and can also achieve large-scale control over the process of uploading business documents to the blockchain, thereby quickly realizing data integration between the business system and the blockchain system. Attached Figure Description

[0044] Figure 1 This is an application environment diagram of a blockchain-based evidence data generation method in one embodiment;

[0045] Figure 2 This is a flowchart illustrating a blockchain-based method for generating evidence storage data in one embodiment.

[0046] Figure 3 This is a schematic diagram illustrating the mapping relationship in one embodiment;

[0047] Figure 4 This is a schematic diagram illustrating the content of a subcondition in one embodiment;

[0048] Figure 5 This is a schematic diagram illustrating the mapping relationship in another embodiment;

[0049] Figure 6 This is a flowchart illustrating the execution of an on-chain task in one embodiment;

[0050] Figure 7 This is a flowchart illustrating the execution of an on-chain task in another embodiment;

[0051] Figure 8This is a structural block diagram of a blockchain-based evidence storage data generation device in one embodiment;

[0052] Figure 9 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0053] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0054] The blockchain-based evidence data generation method provided in this application can be applied to, for example... Figure 1 In the application environment shown, terminal 102 can communicate with server 104 via a network. Both terminal 102 and server 104 can be used independently to execute the blockchain-based evidence data generation method provided in this embodiment, or they can work together to execute the same method. Taking the collaborative execution of the blockchain-based evidence data generation method by terminal 102 and server 104 as an example, terminal 102 sends the target business document to server 104. Server 104 determines the target on-chain format conversion template corresponding to the target business document and determines the business field type corresponding to each business field; based on the mapping relationship between each business field type and the target on-chain format conversion template, it determines the mapping method corresponding to each business field. Server 104 also maps each business field according to its corresponding mapping method to obtain at least one evidence field, and based on at least one evidence field, obtains target evidence data with a standard on-chain format, and returns the target evidence data to terminal 102. The terminal 102 can be, but is not limited to, various personal computers, laptops, smartphones, tablets, and portable wearable devices, and the server 104 can be implemented using a standalone server or a server cluster consisting of multiple servers.

[0055] In one embodiment, such as Figure 2 As shown, a blockchain-based method for generating evidence storage data is provided. The method is illustrated using a computer device as an example, which can provide... Figure 1 The terminal or server in the process includes the following steps:

[0056] Step 202: Obtain the target business document and determine the target on-chain format conversion template corresponding to the target business document.

[0057] The target business document includes multiple business fields; the target on-chain format conversion template includes the mapping relationship between business field types and evidence storage field types. The target on-chain format conversion template can also be called an evidence storage entity. An evidence storage entity is a template with a standard on-chain format implemented through a blockchain smart contract. It generally includes evidence storage codes and evidence storage fields. Different participants can upload data to the blockchain based on the evidence storage entity, enabling data sharing on the blockchain.

[0058] Once the stored entity uploads its data to the blockchain, the blockchain's consensus mechanism, encryption algorithms, digital signatures, and other technologies provide features such as immutability of the data, traceability of the process, and transparent and controllable permissions.

[0059] Specifically, the target business documents typically originate from the business systems of different companies, and their data formats are not the same and do not conform to the standard on-chain format in blockchain. Upon obtaining the target business documents, the computer equipment acquires the pre-set business relationship and determines the target on-chain format conversion template corresponding to the target business documents based on the business relationship.

[0060] In one embodiment, before obtaining the target business document, the method further includes: displaying a business association interface; the business association interface includes multiple business documents and multiple on-chain format conversion templates; in response to the association operation on the multiple business documents and multiple on-chain format conversion templates, obtaining the business association relationship between the business documents and the on-chain format conversion templates.

[0061] Specifically, the computer device can display a business association interface, which includes a list of business documents and a list of on-chain format conversion templates. In response to the user's selection operation on the business documents and on-chain format conversion templates, the selected business documents and on-chain format conversion templates are determined, and in response to the association operation between the selected business documents and on-chain format conversion templates, the business association relationship is obtained.

[0062] In one embodiment, when the on-chain format conversion template does not meet the user's needs, the computer device can respond to the user's new creation operation and create an on-chain format conversion template that meets the user's needs.

[0063] In one embodiment, the computer device can store business relationships in the form of basic data. Typically, the basic data is a relatively stable data set, and there is comprehensive lifecycle management for the basic data. This ensures that in subsequent on-chain tasks or other business tasks, business documents can be quickly referenced based on business relationships.

[0064] In one embodiment, the computer device also provides an encoding rule module, which can generate a system code corresponding to the business relationship according to the user's pre-defined encoding rules. For example, the system code is in the form of "date + random code". At this time, the computer device responds to the user's editing operation and obtains the target name corresponding to the system code. When the computer device responds to the user's trigger operation on the target name, it can display the target business document and the target on-chain format conversion template.

[0065] Step 204: Determine the business field type corresponding to each business field, and determine the mapping method corresponding to each business field based on the business field type and mapping relationship.

[0066] The business field types include at least one of the following: string type, numeric type, basic data type, journal entry type, multi-select type, attachment type, and special type, and are not limited to the listed types. Objects in the target business document correspond to business fields of the basic data type; arrays in the target business document correspond to business fields of the journal entry type; multi-select types indicate types where multiple business fields must be converted simultaneously before being uploaded to the blockchain; if the target business document is a file, it corresponds to business fields of the attachment type; special types indicate types where business fields must be manually configured before being uploaded to the blockchain.

[0067] In one embodiment, the mapping method corresponding to each business field is determined according to each business field type and mapping relationship, including: for each of the multiple business fields, the evidence storage field type corresponding to the current business field is determined according to the mapping relationship and the business field type of the current business field; and the mapping method corresponding to the current business field is determined according to the evidence storage field type.

[0068] Specifically, the mapping relationship is obtained through pre-configuration of computer equipment. Through the mapping relationship, the data field types of different business fields can determine the data field type of the corresponding data field to be generated. Then, the computer equipment determines the mapping method of different business fields to the corresponding data field to be generated based on the data field type.

[0069] Furthermore, when the business field type is at least one of string type, numeric type, basic data type and entry type, the evidence storage field type corresponding to the current business field is determined to be a normal type according to the mapping relationship; when the business field type is at least one of multi-select type, attachment type and special type, the evidence storage field type corresponding to the current business field is determined to be a specified type according to the mapping relationship.

[0070] Common types include simpler types such as string, numeric, and array types. Specified types are user-defined types, such as string types.

[0071] Specifically, such as Figure 3 As shown, Figure 3 This diagram illustrates the mapping relationship between business field types and evidence storage field types. When the business field type is a string, the computer device determines that the corresponding evidence storage field type is a string; when the business field type is a numeric type, the computer device determines that the corresponding evidence storage field type is a numeric; when the business field type is a basic data type, the computer device determines that the corresponding evidence storage field type is either a string or a numeric; when the business field type is an entry type, the computer device determines that the corresponding evidence storage field type is an array type, where array types include simple arrays and composite arrays, and composite arrays are Object arrays, such as "objects" in JSON.

[0072] In one embodiment, the computer device determines the mapping method corresponding to the business field based on the business field type of the business field.

[0073] In this embodiment, by mapping relationships and business field types of business fields, the types of evidence storage fields that are easy to store on the blockchain can be determined. This improves the flexibility of mapping different business field types to different evidence storage field types and ensures the rapid generation of subsequent target evidence storage data, thereby simplifying the process of standardized management of large-scale data.

[0074] Step 206: Map each business field according to its corresponding mapping method to obtain at least one evidence storage field.

[0075] The mapping methods include automatic conversion, value conversion, and hash processing.

[0076] Specifically, if the evidence storage field type corresponding to the business field is a common type, and the business field type includes at least one of string, numeric, basic data, and entry types, then the mapping method is determined to be automatic conversion. Automatic conversion is typically a one-to-one conversion, meaning one business field is mapped to one evidence storage field. If the evidence storage field type corresponding to the business field is a specified type, and the business field type includes multiple-selection or attachment types, then the mapping method is determined to be value conversion. Value conversion is typically a many-to-one conversion, meaning multiple business fields are mapped to one evidence storage field. If the evidence storage field type corresponding to the business field is a specified type, and the business field type is a special selection type, then the mapping method is determined to be hash processing.

[0077] In one embodiment, the evidence fields included in the evidence storage data can generally be divided into two main parts: direct evidence fields and indirect evidence fields. Direct evidence fields refer to fields directly defined or commonly used by the business system, which can be directly filled in or entered after simple processing when the business system uploads data to the blockchain. Examples include order type, quantity, amount, and business status. Indirect evidence fields refer to fields that require interaction between the business document and the blockchain system to be calculated. Examples include digital identities related to on-chain calls and fields associated with data permission identifiers. Therefore, computer devices need to convert personnel information and organizational information from the business system into digital identities representing blockchain private keys and certificates through blockchain services before they can be uploaded to the blockchain or queried. This process is called setting data permission identifiers in the on-chain conversion template, which is also a kind of "data ownership" setting.

[0078] Step 208: Obtain target evidence data with a standard on-chain format based on at least one evidence field; the target evidence data is used to upload to the blockchain.

[0079] Specifically, by integrating each field of the evidence storage, the computer device can obtain the target evidence storage data, which can then be considered as an evidence storage entity with a standard on-chain format. When multiple target evidence storage data from different business systems are obtained, the computer device can perform data integration. Data integration refers to the process of combining data to obtain a unified and more valuable view. Data integration helps enterprises make faster and better decisions. For blockchain, data integration is a process of integrating target evidence storage data and performing large-scale processing before putting the data on the blockchain.

[0080] In one embodiment, obtaining target evidence data with a standard on-chain format based on at least one evidence field includes: synthesizing each evidence field to obtain candidate evidence data, and determining the identity identifier corresponding to the target business document based on the data permission identifier; when a target digital identity matching the identity identifier is found in a preset database, the candidate evidence data is used as the target evidence data with a standard on-chain format.

[0081] The target on-chain format conversion template also includes data permission identifiers; data permission identifiers include organizational permission identifiers or personnel permission identifiers; target business documents usually carry organizational information or personnel information.

[0082] Specifically, when the computer device determines that the data permission identifier is an organizational permission identifier, it determines the identity identifier corresponding to the target business document as the organizational information carried in the target business document; when the computer device determines that the data permission identifier is a personnel permission identifier, it determines the identity identifier corresponding to the target business document as the personnel information carried in the target business document, for example, the personnel information is the applicant or approver of the target business document. The computer device searches from a preset database based on the identity identifier. If a matching target digital identity is found, it indicates that the candidate evidence data can be used as target evidence data with a standard on-chain format.

[0083] In one embodiment, a computer device associates a target digital identity with target evidence data and uploads the target evidence data to the blockchain via the target digital identity.

[0084] In one embodiment, the computer device also includes a blockchain digital identity system that associates a digital identity address with a blockchain certificate and private key. The computer device also stores multiple digital identities in a pre-defined database.

[0085] In one embodiment, the computer device can reasonably separate blockchain-related development tools from business system-related development tools and better manage the entire on-chain process, enabling the computer system to be quickly reused. Simultaneously, it can encapsulate the underlying complexity of the blockchain and technical details unrelated to the business system itself, allowing for low-code integration of heterogeneous business documents and heterogeneous system blockchain notarization without modifying existing business systems.

[0086] In the aforementioned blockchain-based evidence storage data generation method, the target business document is obtained, and the target on-chain format conversion template corresponding to the target business document is determined. Then, the business field type corresponding to each business field is determined. Based on the mapping relationship between each business field type and the target on-chain format conversion template, the mapping method corresponding to each business field can be determined. Thus, each business field is mapped according to its corresponding mapping method to obtain at least one evidence storage field. In this way, target evidence storage data with a standard on-chain format can be obtained based on at least one evidence storage field. Since this application flexibly maps business fields of different business field types based on different mapping methods after determining the target on-chain format conversion template, it can accurately obtain target evidence storage data with a standard on-chain format. At the same time, since it eliminates the need to redevelop heterogeneous business documents, it only uses a low-code approach to map the target business document and upload the mapped target evidence storage data to the blockchain, reducing the difficulty of blockchain evidence storage for different business documents.

[0087] In one embodiment, after determining the target on-chain format conversion template corresponding to the target business document, the method further includes: determining the field value corresponding to each business field and determining the target field value corresponding to each sub-condition; filtering the target field value corresponding to each sub-condition according to each sub-condition to obtain multiple filtering results; associating the multiple filtering results according to the logical relationship between each sub-condition to obtain an association result; and when the association result is true, using the target business document as the filtered target business document.

[0088] The target on-chain format conversion template includes on-chain conditions; the on-chain conditions include multiple sub-conditions; each sub-condition has a logical relationship with the others; each sub-condition and the logical relationship are pre-set.

[0089] Specifically, the computer equipment determines the field value corresponding to each business field. For example, when the business field is document status, the corresponding field value is "Status A"; when the business field is contract amount, the corresponding field value is 1000; and when the business field is applicant, the corresponding field value is "Zhang San". The computer equipment parses each sub-condition, determines the content corresponding to each sub-condition, and determines the target field value corresponding to the content of each sub-condition. For example... Figure 4 As shown, Figure 4 This is a schematic diagram of the content of a sub-condition. For example, the content of the first sub-condition includes the document status, so the field value corresponding to the document status is used as the target field value.

[0090] The computer device filters the target field values ​​corresponding to each sub-condition, resulting in multiple filtering results. For example, if the first sub-condition includes comparison methods of "equal to" and a comparison value of "C", then the first sub-condition is "Document status equal to C". Since the target field value for "Document status" is "A", the filtering result is false, indicating that the business field corresponding to the target field value has not passed the filtering. As another example, if the second sub-condition includes comparison methods of "equal to" and a comparison value of 1000, then the second sub-condition is "Contract amount equal to 1000". Since the target field value for "Contract amount" is 1000, the filtering result is true, indicating that the business field corresponding to the target field value has passed the filtering. The computer device then correlates these filtering results based on the logical relationships between the sub-conditions, obtaining a correlation result. This correlation result is used as the Boolean value returned by the target business document, which can be either true or false. When the correlation result is true, the computer device considers the target business document as a filtered and passed document.

[0091] In one embodiment, the on-chain conditions in the target on-chain format conversion template are encapsulated in a technical module, which can be flexibly invoked by the user after configuring different sub-conditions.

[0092] In one embodiment, multiple filtering results are associated based on the logical relationship between each sub-condition to obtain an association result, including: determining the current sub-condition and its adjacent sub-conditions; associating the filtering result corresponding to the current sub-condition with the filtering result corresponding to the adjacent sub-condition based on the logical relationship between the current sub-condition and the adjacent sub-conditions to obtain an association result; using the adjacent sub-condition as the new current sub-condition, using the association result as the filtering result of the new current sub-condition, and returning to the step of determining the adjacent sub-conditions of the current sub-condition to continue until all filtering results are associated.

[0093] The logical relationships include at least one of logical AND and logical OR; the filtering results include either true or false.

[0094] Specifically, the computer device can use the first sub-condition as the current sub-condition and the second sub-condition as the adjacent sub-condition. If the logical relationship between the current sub-condition and the adjacent sub-condition is logical OR, then the filtering result corresponding to the current sub-condition and the filtering result corresponding to the adjacent sub-condition are logically correlated. For example, referring to the example above, the filtering result "false" of the first sub-condition is logically ORed with the filtering result "true" of the second sub-condition, resulting in a correlation result of "true". The computer device continues to use the correlation result as the filtering result of the new current sub-condition and the third sub-condition as the new adjacent sub-condition. If the logical relationship between the new current sub-condition and the new adjacent sub-condition is logical AND, then the correlation result "true" is logically ANDed with the filtering result of the third sub-condition, until all filtering results are correlated.

[0095] In this embodiment, different sub-conditions are provided to filter target business documents, accurately obtaining the filtering results. Multiple filtering results are then linked based on the logical relationships between each sub-condition. This reduces the risk of incorrect data upload to the blockchain due to erroneous filtering of target business documents. Furthermore, users can flexibly configure sub-conditions, enabling large-scale control over the upload of large volumes of evidence data to the blockchain without modifying existing business systems, thus improving the efficiency of data upload.

[0096] In one embodiment, determining the mapping method corresponding to the current business field based on the type of the evidence storage field includes: when the type of the evidence storage field is a normal type, determining that the mapping method corresponding to the current business field is an automatic conversion method; mapping each business field according to its respective mapping method to obtain at least one evidence storage field includes: mapping the current business field according to the automatic conversion method to obtain the current evidence storage field corresponding to the type of the evidence storage field.

[0097] Specifically, since common data types are typically simpler structures such as string, numeric, and array types, computing devices can employ a simple automatic conversion method. The corresponding business field types are also usually simple. This automatic conversion is implemented through a user-preset script file, and the resulting evidence-stored fields are in plaintext format. Therefore, in this embodiment, the automatic conversion method allows for mapping simpler business fields, quickly obtaining evidence-stored fields corresponding to their types. This provides a flexible field mapping method and improves the efficiency of subsequent target evidence-stored data generation.

[0098] In one embodiment, determining the mapping method corresponding to the current business field based on the type of the evidence storage field includes: when the type of the evidence storage field is a specified type, determining the mapping method corresponding to the current business field as a value conversion method; mapping each business field according to its respective mapping method to obtain at least one evidence storage field includes: mapping each business field according to the value conversion method to obtain at least one evidence storage field.

[0099] Specifically, since the data storage field type is a specified type, the business field type can be at least one of multiple-choice, attachment, and special types. When the business field type is a multiple-choice type, the computer device can map multiple business fields corresponding to the multiple-choice type according to the value conversion method to obtain a single data storage field. When the business field type is an attachment type, i.e., it cannot be automatically converted, the computer device can map the business fields corresponding to the attachment type according to the value conversion method to obtain a single data storage field. For example... Figure 5 As shown, Figure 5 This is a schematic diagram illustrating the mapping relationship.

[0100] Furthermore, based on the value conversion method, each business field is mapped to obtain at least one evidence storage field, including: multiple first business fields whose mapping method is determined to be value conversion; when the value conversion method is concatenation processing, a separator is added between each first business field, and the multiple first business fields with added separators are concatenated to obtain an evidence storage field; when the value conversion method is sequence processing, each first business field is serialized according to a preset standard data format to obtain an evidence storage field.

[0101] The value conversion method includes either concatenation or sequence processing. The evidence storage field obtained through concatenation and sequence processing is in plaintext form.

[0102] Specifically, when the business field type is multi-select, the representation requires the simultaneous conversion of multiple business fields. Therefore, the computer device needs to determine the corresponding multiple first business fields when the mapping method is value conversion. When the value conversion method is concatenation, a separator is added between each first business field before concatenation to obtain a single evidence field, which is a string. When the value conversion method is sequence processing, the computer device serializes each first business field according to a preset standard data format, such as JSON data format, to obtain a single evidence field, which is a JSON string.

[0103] In one embodiment, after performing sequence processing on multiple first business fields to obtain a single evidence storage field, the computer device can determine the hash value corresponding to the evidence storage field through hash processing, use the hash value as the target evidence storage field, and upload the data to the blockchain using the hash value. This can be viewed as a one-way hash encryption process. For example, if a user wants to ensure that the contracting parties in the system have not changed, but does not want to upload the data to the blockchain in plaintext, they can select the two fields "Contract Party A" and "Contract Party B" and map them to a single evidence storage field.

[0104] In this embodiment, while mapping business fields with relatively simple field types, multi-selection business fields can also be mapped through value-dynamic conversion, realizing multi-threaded synchronous processing, improving the accuracy of determining the evidence storage fields, and the efficiency of generating subsequent target evidence storage data.

[0105] In one embodiment, determining the mapping method corresponding to the current business field based on the type of the evidence storage field includes: when the evidence storage field type is a specified type and has a manual configuration identifier, determining the mapping method corresponding to the current business field as a hash processing method; mapping each business field according to its respective mapping method to obtain at least one evidence storage field, including: in response to a selection operation for multiple business fields, determining multiple selected second business fields; serializing each second business field according to a preset standard data format to obtain a business string; determining the hash value corresponding to the business string, and using the hash value as an evidence storage field.

[0106] Specifically, when the evidence storage field type is a specified type and has a manual configuration identifier, it indicates that the current business field is a manually configured field, and the corresponding mapping method is hash processing. When the computer device responds to the user's selection operation of multiple business fields, it can determine the selected multiple second business fields. It is easy to understand that the user can also select only one business field for hash processing. The specific implementation process of mapping the second business field using hash processing can be referred to the specific implementation process of mapping the first business field using hash processing, and will not be repeated here.

[0107] In this embodiment, by providing a method for users to manually configure, flexible conversion of evidence storage fields can be achieved, which also facilitates flexible management of target business documents by users.

[0108] In one embodiment, such as Figure 6 As shown, Figure 6 This is a flowchart illustrating the process of performing an on-chain task. Implementing an on-chain task also includes the following steps:

[0109] Step 602: When an on-chain task is received, determine the on-chain method in the on-chain task.

[0110] Among them, the on-chain methods include timed batch method and event-triggered method. The timed batch method can be an asynchronous on-chain method, while the event-triggered method is a synchronous on-chain method.

[0111] Specifically, once the computer device has established the business relationships, it can receive the user-preset on-chain task and then quickly implement and manage the entire data on-chain process according to the on-chain task. The on-chain task can be viewed as a document in the business system referencing at least one business relationship. When the on-chain task is initiated, it can extract or filter the target business documents corresponding to these referenced business relationships, map the business documents that meet the on-chain conditions to target evidence storage data, and ultimately invoke the on-chain evidence storage service through the target digital identity, handling any exceptions during the invocation process.

[0112] Step 604: When the on-chain method is timed batch mode, determine all target business documents generated within the preset on-chain time period.

[0113] Specifically, such as Figure 7 As shown, Figure 7 This is a flowchart illustrating the execution of a blockchain task. The computer device retrieves source data from the business system. When the blockchain upload method is scheduled batch upload, the source data consists of all target business documents added or modified within a preset upload time period. The preset upload time period can be daily, hourly, etc. Based on the blockchain upload task, the computer device takes a data snapshot of all target business documents and uploads all snapshotted target business documents through... Figure 7 The business association template is defined in the document for blockchain uploading. This business association template definition is also known as the target uploading format conversion template.

[0114] Step 606: Determine the target evidence data corresponding to each target business document, and upload each target evidence data to the blockchain by calling the preset interface.

[0115] Specifically, refer to Figure 7As shown, for each target business document, the computer device filters the document according to the on-chain conditions in its corresponding target on-chain format conversion template. The filtered documents are then mapped to specific fields, and the data format is converted to obtain the corresponding target evidence data. The computer device determines the identity of the target business document based on the data permission identifier, also known as data ownership. When a target digital identity matching the identity identifier is found in the pre-set database, the pre-set interface of the on-chain service is invoked to upload the target evidence data containing the target digital identity to the blockchain.

[0116] In one embodiment, reference Figure 7 As shown, when the interface call succeeds, the computer device records the corresponding target evidence data in the evidence storage log. If the interface call fails due to network errors or other reasons, the interface will be called multiple times according to the preset number of calls, and the error log will be recorded to facilitate maintenance and troubleshooting. Furthermore, if multiple interface calls fail, the process can be switched to manual execution for re-uploading to the blockchain.

[0117] In one embodiment, when the on-chain method is event-triggered, multiple business events are monitored; when a target business event is detected, the target business document corresponding to the target business event is determined; the target evidence data corresponding to the target business document is determined, and the target evidence data is uploaded to the blockchain by calling a preset interface.

[0118] Business events include at least one of the following: business document approval, business document pushdown, and business document closure; typically, business events need to be pre-configured by the user. Business document pushdown refers to the process of pushing down a document to generate a new document, such as a purchase order generating a purchase contract, or a purchase contract generating a purchase payable invoice; business document closure generally refers to the business process of closing a document, such as closing a contract after its execution.

[0119] Specifically, the computer system also includes a message broker. When a user performs business operations and generates a corresponding business event, the message broker distributes and broadcasts the business event. When the computer device detects a target business event, it determines the target business document corresponding to the target business event and continues to execute the on-chain task on the target business document. The specific implementation of determining the target evidence data corresponding to the target business document can be found in step 606, which will not be repeated in this embodiment. It is easy to understand that, unlike the timed batch method, the on-chain task corresponding to the event-triggered method typically contains only one target business document.

[0120] In this embodiment, by adopting a target on-chain format conversion template, the process of filtering business documents from the business system and automatically matching and integrating them with the data format of the blockchain system is realized. Through methods such as custom configuration of on-chain conditions, synchronization of multiple on-chain task threads, and asynchronous handling of error events, high-concurrency and high-reliability task management of evidence storage data is achieved. Thus, data integration between the business system and the blockchain system is realized in a low-code manner without modifying the business system or requiring business developers to understand the complexity of the underlying blockchain technology.

[0121] It should be understood that although the steps in the flowcharts of the above embodiments are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the above embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0122] Based on the same inventive concept, this application also provides a blockchain-based evidence data generation device for implementing the blockchain-based evidence data generation method described above. The solution provided by this device is similar to the implementation described in the above method. Therefore, the specific limitations of one or more blockchain-based evidence data generation device embodiments provided below can be found in the limitations of the blockchain-based evidence data generation method described above, and will not be repeated here.

[0123] In one embodiment, such as Figure 8 As shown, a blockchain-based evidence storage data generation device 800 is provided, comprising: a business document acquisition module 802, a mapping method determination module 804, and an evidence storage data determination module 806, wherein:

[0124] The business document acquisition module 802 is used to acquire the target business document and determine the target on-chain format conversion template corresponding to the target business document; the target business document includes multiple business fields; the target on-chain format conversion template includes the mapping relationship between the business field types and the evidence storage field types;

[0125] The mapping method determination module 804 is used to determine the business field type corresponding to each business field, and to determine the mapping method corresponding to each business field based on the business field type and mapping relationship.

[0126] The evidence storage data determination module 806 is used to map each business field according to the mapping method corresponding to each business field to obtain at least one evidence storage field; based on at least one evidence storage field, it obtains target evidence storage data with a standard on-chain format; the target evidence storage data is used to upload to the blockchain.

[0127] In one embodiment, the blockchain-based evidence generation device 800 further includes a business association module 808 for displaying a business association interface; the business association interface includes multiple business documents and multiple on-chain format conversion templates; in response to association operations on the multiple business documents and multiple on-chain format conversion templates, the business association relationship between the business documents and the on-chain format conversion templates is obtained; determining the target on-chain format conversion template corresponding to the target business document includes: when the target business document is obtained, determining the target on-chain format conversion template corresponding to the target business document based on the business association relationship.

[0128] In one embodiment, the blockchain-based evidence storage data generation device 800 includes an on-chain filtering module 810, which is used to determine the field values ​​corresponding to each business field and the target field values ​​corresponding to each sub-condition; to filter the target field values ​​corresponding to each sub-condition according to each sub-condition to obtain multiple filtering results; to associate the multiple filtering results according to the logical relationship between each sub-condition to obtain an association result; and when the association result is true, the target business document is used as the target business document that has passed the filtering.

[0129] In one embodiment, the on-chain filtering module 810 is further configured to determine the current sub-condition and its adjacent sub-conditions; based on the logical association between the current sub-condition and its adjacent sub-conditions, associate the filtering result corresponding to the current sub-condition with the filtering result corresponding to the adjacent sub-condition to obtain an association result; use the adjacent sub-condition as the new current sub-condition, use the association result as the new current sub-condition's filtering result, and return to the step of determining the adjacent sub-conditions of the current sub-condition to continue until all filtering results are associated.

[0130] In one embodiment, the mapping method determination module 804 is used to determine the evidence storage field type corresponding to the current business field for each business field based on the mapping relationship and the business field type of the current business field; and to determine the mapping method corresponding to the current business field based on the evidence storage field type.

[0131] In one embodiment, the mapping method determination module 804 includes a field type determination module 8041, which is used to determine, according to the mapping relationship, that the evidence storage field type corresponding to the current business field is a normal type when the business field type is at least one of string type, numeric type, basic data type and entry type; and to determine, according to the mapping relationship, that the evidence storage field type corresponding to the current business field is a specified type when the business field type is at least one of multi-select type, attachment type and special type.

[0132] In one embodiment, the mapping method determination module 804 further includes an automatic conversion module 8042, which is used to determine that the mapping method corresponding to the current business field is the automatic conversion method when the evidence storage field type is a normal type; and to map each business field according to the mapping method corresponding to each business field to obtain at least one evidence storage field, including: mapping the current business field according to the automatic conversion method to obtain the current evidence storage field corresponding to the evidence storage field type.

[0133] In one embodiment, the mapping method determination module 804 further includes a value conversion module 8043, which is used to determine that the mapping method corresponding to the current business field is a value conversion method when the evidence storage field type is a specified type; and to map each business field according to the mapping method corresponding to each business field to obtain at least one evidence storage field, including: mapping each business field according to the value conversion method to obtain at least one evidence storage field.

[0134] In one embodiment, the value conversion module 8043 is further configured to determine multiple first business fields whose mapping method is value conversion method; when the value conversion method is concatenation processing, a separator is added between each first business field, and each first business field with the added separator is concatenated to obtain a storage field; when the value conversion method is sequence processing, each first business field is serialized according to a preset standard data format to obtain a storage field.

[0135] In one embodiment, the mapping method determination module 804 further includes a hash processing module 8044, used to determine that the mapping method corresponding to the current business field is a hash processing method when the evidence storage field type is a specified type and has a manual configuration identifier; and to map each business field according to its respective mapping method to obtain at least one evidence storage field, including: in response to a selection operation for multiple business fields, determining multiple selected second business fields; serializing each second business field according to a preset standard data format to obtain a business string; determining the hash value corresponding to the business string, and using the hash value as an evidence storage field.

[0136] In one embodiment, the evidence storage data determination module 806 is further configured to integrate each evidence storage field to obtain candidate evidence storage data, and determine the identity identifier corresponding to the target business document based on the data permission identifier; when a target digital identity matching the identity identifier is found in the preset database, the candidate evidence storage data is used as evidence storage data with a standard on-chain format; the above method also includes: associating the target digital identity with the target evidence storage data, and on-chaining the target evidence storage data to the blockchain through the target digital identity.

[0137] In one embodiment, the blockchain-based evidence storage data generation device 800 further includes a task determination module 812, which is used to determine the on-chain method in the on-chain task when an on-chain task is received; when the on-chain method is a timed batch method, determine all target business documents generated within a preset on-chain time period; determine the target evidence storage data corresponding to each target business document, and upload each target evidence storage data to the blockchain by calling a preset interface.

[0138] In one embodiment, the task determination module 812 is further configured to listen to multiple business events when the on-chain method is event-triggered; the business events include at least one of business document approval, business document push-down, and business document closure; when a target business event is detected, the target business document corresponding to the target business event is determined; the target evidence data corresponding to the target business document is determined, and the target evidence data is on-chained to the blockchain by calling a preset interface.

[0139] The modules in the aforementioned blockchain-based evidence generation device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the corresponding operations of each module.

[0140] In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 9As shown, the computer device includes a processor, memory, input / output interfaces (I / O), a communication interface, a display unit, and input devices. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface, display unit, and input devices are also connected to the system bus via the I / O interfaces. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides the environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The I / O interfaces are used for exchanging information between the processor and external devices. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, NFC (Near Field Communication), or other technologies. When the computer program is executed by the processor, it implements a blockchain-based method for generating evidence-based data. The display unit of the computer device is used to form a visually visible image. It can be a display screen, a projection device, or a virtual reality imaging device. The display screen can be an LCD screen or an e-ink screen. The input device of the computer device can be a touch layer covering the display screen, or buttons, trackballs, or touchpads set on the casing of the computer device, or external keyboards, touchpads, or mice, etc.

[0141] Those skilled in the art will understand that Figure 9 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0142] In one embodiment, a computer device is also provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above method embodiments.

[0143] In one embodiment, a computer-readable storage medium is provided storing a computer program that, when executed by a processor, implements the steps in the above method embodiments.

[0144] In one embodiment, a computer program product or computer program is provided, the computer program product or computer program including computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and executes the computer instructions, causing the computer device to perform the steps in the above method embodiments.

[0145] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0146] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0147] The above embodiments are merely illustrative of several implementation methods of this application, and their descriptions are relatively specific and detailed. However, they should not be construed as limiting the scope of this application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method for generating evidence-based data based on blockchain, characterized in that, The method includes: The process involves acquiring a target business document and determining the target on-chain format conversion template corresponding to the target business document based on pre-set business relationships. The target business document includes multiple business fields. The target on-chain format conversion template includes a mapping relationship between business field types and evidence storage field types, data permission identifiers, and on-chain conditions. The on-chain conditions include multiple sub-conditions, each of which has a logical relationship with the others. The target on-chain format conversion template is a template with a standard on-chain format implemented through a blockchain smart contract. Determine the business field type corresponding to each of the business fields, and determine the evidence storage field type corresponding to each of the business fields based on each business field type and the mapping relationship; wherein, the evidence storage field type includes ordinary type and specified type; Based on the type of the evidence storage field, determine the mapping method for each of the business fields to be mapped to the corresponding evidence storage field to be generated, including: if the type of the evidence storage field is the specified type, and the business field type of the business field is a special type, determine that the mapping method for the business field to be mapped to the corresponding evidence storage field to be generated is a hash processing method; wherein, the mapping method includes an automatic conversion method, a value conversion method, and the hash processing method; Based on the mapping method corresponding to each of the business fields, each of the business fields is mapped to obtain at least one evidence storage field; Based on the at least one evidence storage field, target evidence storage data with a standard on-chain format is obtained; the target evidence storage data is used to be uploaded to the blockchain.

2. The method according to claim 1, characterized in that, Prior to obtaining the target business document, the method further includes: The interface displays business associations; the business association interface includes multiple business documents and multiple on-chain format conversion templates. In response to association operations involving multiple business documents and multiple on-chain format conversion templates, the business association relationship between the business documents and the on-chain format conversion templates is obtained; The step of determining the target on-chain format conversion template corresponding to the target business document includes: Once the target business document is obtained, the target on-chain format conversion template corresponding to the target business document is determined based on the business association relationship.

3. The method according to claim 1, characterized in that, After determining the target on-chain format conversion template corresponding to the target business document, the method further includes: Determine the field value corresponding to each of the business fields, and determine the target field value corresponding to each of the sub-conditions; Based on each of the sub-conditions, the target field values ​​corresponding to each sub-condition are filtered to obtain multiple filtering results; Based on the logical relationships between each of the sub-conditions, multiple filtering results are associated to obtain associated results; When the association result is true, the target business document is selected as the target business document that passes the screening.

4. The method according to claim 3, characterized in that, The logical relationship includes at least one of logical AND and logical OR; the filtering result includes either true or false. The step of associating multiple filtering results based on the logical relationship between each of the sub-conditions to obtain the association result includes: Determine the current sub-condition and its adjacent neighboring sub-conditions; Based on the logical relationship between the current sub-condition and the adjacent sub-condition, the filtering results corresponding to the current sub-condition and the filtering results corresponding to the adjacent sub-condition are associated to obtain the association result; The adjacent sub-conditions are used as the new current sub-conditions, and the association results are used as the filtering results of the new current sub-conditions. The process then returns to the step of determining the adjacent sub-conditions of the current sub-conditions and continues until all filtering results are associated.

5. The method according to claim 1, characterized in that, The step of determining the mapping method corresponding to each business field based on each business field type and the mapping relationship includes: For each of the multiple business fields, the type of evidence storage field corresponding to the current business field is determined according to the mapping relationship and the business field type of the current business field; Based on the type of the evidence storage field, determine the mapping method corresponding to the current business field.

6. The method according to claim 5, characterized in that, The step of determining the evidence storage field type corresponding to the current business field based on the mapping relationship and the business field type of the current business field includes: When the business field type is at least one of string type, numeric type, basic data type and entry type, the evidence storage field type corresponding to the current business field is determined to be ordinary type according to the mapping relationship; When the business field type is at least one of multiple selection type, attachment field and special type, the evidence storage field type corresponding to the current business field is determined to be the specified type according to the mapping relationship.

7. The method according to claim 5, characterized in that, The step of determining the mapping method corresponding to the current business field based on the evidence storage field type includes: When the type of the evidence storage field is a normal type, the mapping method corresponding to the current business field is determined to be the automatic conversion method; Based on the mapping method corresponding to each of the business fields, each business field is mapped to obtain at least one evidence storage field, including: Based on the automatic conversion method, the current business field is mapped to obtain the current evidence storage field corresponding to the evidence storage field type.

8. The method according to claim 5, characterized in that, The step of determining the mapping method corresponding to the current business field based on the evidence storage field type includes: When the type of the evidence storage field is a specified type, the mapping method corresponding to the current business field is determined to be the value conversion method; Based on the mapping method corresponding to each of the business fields, each business field is mapped to obtain at least one evidence storage field, including: Based on the value conversion method, each of the business fields is mapped to obtain at least one evidence storage field.

9. The method according to claim 8, characterized in that, The value conversion method includes either concatenation processing or sequence processing; the mapping of each business field according to the value conversion method to obtain at least one evidence storage field includes: Multiple first business fields whose mapping method is the value conversion method are determined; When the value conversion method is concatenation processing, a separator is added between each of the first business fields, and the first business fields with the added separator are concatenated to obtain a certificate field; When the value conversion method is serialization, each of the first business fields is serialized according to a preset standard data format to obtain a certificate field.

10. The method according to claim 5, characterized in that, The step of determining the mapping method corresponding to the current business field based on the evidence storage field type includes: When the evidence storage field type is a specified type and has a manual configuration identifier, the mapping method corresponding to the current business field is determined to be a hash processing method; Based on the mapping method corresponding to each of the business fields, each business field is mapped to obtain at least one evidence storage field, including: In response to the selection operation for the plurality of business fields, the plurality of selected second business fields are determined; According to the preset standard data format, each of the second business fields is serialized to obtain a business string; Determine the hash value corresponding to the business string, and use the hash value as a certificate field.

11. The method according to claim 1, characterized in that, The step of obtaining target evidence data with a standard on-chain format based on the at least one evidence field includes: By combining each of the evidence storage fields, candidate evidence storage data is obtained, and based on the data permission identifier, the identity identifier corresponding to the target business document is determined; When a target digital identity matching the identity identifier is found in the preset database, the candidate evidence data is used as evidence data with a standard on-chain format. The method further includes: The target digital identity is associated with the target evidence data, and the target evidence data is uploaded to the blockchain through the target digital identity.

12. The method according to claim 1, characterized in that, The method further includes: When an on-chain task is received, the on-chain method in the on-chain task is determined; When the on-chain method is a timed batch method, all target business documents generated within the preset on-chain time period are determined; The target evidence data corresponding to each target business document is determined, and each target evidence data is uploaded to the blockchain by calling a preset interface.

13. The method according to claim 12, characterized in that, The method further includes: When the on-chain method is event-triggered, multiple business events are monitored; the business events include at least one of business document approval, business document push-down, and business document closure. When a target business event is detected, the target business document corresponding to the target business event is determined; The target evidence data corresponding to the target business document is determined, and the target evidence data is uploaded to the blockchain by calling a preset interface.

14. A blockchain-based evidence storage data generation device, characterized in that, The device includes: The business document acquisition module is used to acquire target business documents and determine the target on-chain format conversion template corresponding to the target business document based on pre-set business association relationships. The target business document includes multiple business fields. The target on-chain format conversion template includes a mapping relationship between business field types and evidence storage field types, data permission identifiers, and on-chain conditions. The on-chain conditions include multiple sub-conditions, and each sub-condition has a logical association relationship. The target on-chain format conversion template is a template with a standard on-chain format implemented through a blockchain smart contract. The mapping method determination module is used to determine the business field type corresponding to each of the business fields, and to determine the evidence storage field type corresponding to each of the business fields based on each business field type and the mapping relationship; wherein, the evidence storage field type includes ordinary type and specified type; and to determine the mapping method for mapping each business field to the corresponding evidence storage field to be generated based on the evidence storage field type, including: if the evidence storage field type is the specified type and the business field type of the business field is a special type, the mapping method for mapping the business field to the corresponding evidence storage field to be generated is determined to be a hash processing method; wherein, the mapping method includes automatic conversion method, value conversion method and hash processing method; The evidence storage data determination module is used to map each of the business fields according to the mapping method corresponding to each of the business fields to obtain at least one evidence storage field; and to obtain target evidence storage data with a standard on-chain format according to the at least one evidence storage field; the target evidence storage data is used to be uploaded to the blockchain.

15. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 13.

16. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 13.

17. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 13.

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