Data asset ownership confirmation methods, systems, equipment and program products

Abstract

This invention discloses a method, system, device, and program product for confirming data asset ownership. The method includes: collecting multi-source heterogeneous data and performing data preprocessing to obtain standardized data; generating a fingerprint digest of the standardized data based on its data type; generating an ownership commitment structure based on the ownership information of the standardized data; writing the ownership commitment structure and fingerprint digest into a consortium blockchain to generate a confirmation and storage record; generating a fiscal asset entry data structure according to preset fiscal asset entry specifications; valuing the standardized data based on preset multi-dimensional asset valuation factors to obtain an asset valuation result; and finally, generating a data asset ownership certificate based on the confirmation and storage record, the fiscal asset entry data structure, and the asset valuation result. This invention achieves reliable ownership confirmation, complete traceability, structural compliance and verifiable verification, asset value re-verification, and executable fiscal asset entry, and is applicable to various data asset management and circulation scenarios.

Description

Technical Field

[0001] This invention relates to the field of blockchain technology, and in particular to a method, system, device, and program product for confirming data asset ownership. Background Technology

[0002] With the development of the digital economy, the volume of data generated by various institutions in their production, operation, and governance processes, including video, IoT sensor data, business logs, and reports, is growing rapidly. Therefore, the industry needs to promote the ownership, accounting, and value management of data as a production factor. However, existing technologies suffer from the following problems: 1. Disorganized multi-source data formats and a lack of unified and reliable preprocessing capabilities; 2. Lack of verifiable original data fingerprint digest chains, making it difficult to guarantee data integrity; 3. Generally simple ownership structures, making it impossible to prove the responsible party and the source of equipment; 4. Blockchain evidence storage cannot support the long-term on-chain storage of large-scale video / IoT data; 5. Lack of structural compliance verification and automated reporting technology for fiscal accounting; 6. Opaque data valuation models, making it impossible for financial institutions to verify; 7. Lack of cross-departmental collaborative ownership certificate verification standards.

[0003] Therefore, there is an urgent need to invent a method for confirming and managing data assets in order to solve the problems of chaotic multi-source data formats, difficulty in ensuring data security, and a single ownership structure in existing technologies. Summary of the Invention

[0004] In view of this, embodiments of the present invention provide a data asset ownership confirmation method, system, device, and program product, which at least partially solves the problems existing in the prior art.

[0005] Other features and advantages of the invention will become apparent from the following detailed description, or may be learned in part by practice of the invention.

[0006] To achieve the above objectives, the embodiments of the present invention provide the following technical solutions:

[0007] According to a first aspect of the present invention, a method for confirming ownership of data assets is provided, the method comprising:

[0008] Collect multi-source heterogeneous data;

[0009] The multi-source heterogeneous data is preprocessed to obtain standardized data;

[0010] Generate a fingerprint digest corresponding to the standardized data based on the data type of the standardized data;

[0011] Based on the ownership information of the standardized data, generate the ownership commitment structure corresponding to the standardized data;

[0012] Write the ownership commitment structure and the fingerprint digest into the consortium blockchain to generate ownership confirmation and storage records and transaction identifiers;

[0013] Generate the fiscal asset entry data structure according to the preset fiscal asset entry standards;

[0014] Based on preset multidimensional asset valuation factors, the standardized data is used to perform asset valuation to obtain asset valuation results.

[0015] Based on the aforementioned ownership confirmation and storage records, the aforementioned fiscal entry data structure, and the aforementioned asset valuation results, a data asset ownership confirmation certificate is generated.

[0016] Furthermore, it collects heterogeneous data from multiple sources, including:

[0017] Collect heterogeneous data from multiple sources, including industrial video systems, IoT terminals, industrial business systems, and document databases.

[0018] Furthermore, the data preprocessing includes format unification, time calibration, structured extraction, and noise filtering.

[0019] Further, based on the data type of the standardized data, a fingerprint digest corresponding to the standardized data is generated, including:

[0020] The standardized data structure includes video data, IoT time-series data, document data, and tabular data;

[0021] For video data, key frames of the video data are extracted according to a preset time interval, and the perceptual hash value of each key frame is calculated to obtain the fingerprint digest corresponding to the video data.

[0022] For IoT time-series data, a preset sliding window is used to segment the IoT time-series data, and a sequence hash is generated for the data in each sliding window to obtain the fingerprint digest corresponding to the IoT time-series data.

[0023] For the document data, a cryptographic hash algorithm is used to calculate the fingerprint digest corresponding to the document data;

[0024] For tabular data, a fingerprint digest corresponding to the tabular data is calculated based on a structured hash tree algorithm.

[0025] Furthermore, the ownership information includes the data production entity, data management entity, data acquisition device identifier, responsible person's signature, process step identifier, and timestamp sequence.

[0026] Furthermore, based on the pre-defined fiscal asset entry standards, a fiscal entry data structure is generated, including:

[0027] According to the preset fiscal asset entry specifications, a fiscal entry data structure is generated, which includes a reporting header, a data asset classification field, a data asset valuation field, a ownership subject field, and an XML / JSON message.

[0028] The data structure of the fiscal entry table is subject to compliance verification, which includes field type verification, mandatory field verification, logical consistency verification, derived field verification, and integrity verification.

[0029] Furthermore, based on preset multi-dimensional asset valuation factors, the standardized data is used to perform asset valuation, resulting in asset valuation results, including:

[0030] Based on preset multidimensional asset valuation factors, a multidimensional asset valuation model is constructed. The multidimensional asset valuation factors include quality, usability, scarcity, scalability, and compliance.

[0031] The standardized data is evaluated using the multi-dimensional asset valuation model to obtain asset valuation results.

[0032] According to a second aspect of the present invention, a data asset ownership confirmation system is provided, the system comprising:

[0033] The data acquisition module is used to collect heterogeneous data from multiple sources.

[0034] The preprocessing module is used to preprocess the multi-source heterogeneous data to obtain standardized data;

[0035] The fingerprint digest generation module is used to generate a fingerprint digest corresponding to the standardized data based on the data type of the standardized data.

[0036] The ownership commitment structure generation module is used to generate an ownership commitment structure corresponding to the standardized data based on the ownership information of the standardized data.

[0037] The consortium blockchain notarization module is used to write the ownership commitment structure and the fingerprint digest into the consortium blockchain to generate ownership notarization records and transaction identifiers;

[0038] The asset entry module is used to generate the fiscal asset entry data structure according to the preset fiscal asset entry specifications.

[0039] The asset valuation module is used to perform asset valuation on the standardized data based on preset multi-dimensional asset valuation factors to obtain asset valuation results.

[0040] The certificate generation module is used to generate a data asset ownership certificate based on the ownership confirmation and storage record, the fiscal entry data structure, and the asset valuation result.

[0041] According to a third aspect of the present invention, a data asset ownership confirmation device is provided, the device comprising: a processor and a memory;

[0042] The memory is used to store one or more program instructions;

[0043] The processor is configured to run one or more program instructions to perform the steps of a data asset ownership confirmation method as described in any of the preceding claims.

[0044] According to a fourth aspect of the present invention, a computer program product is provided, the computer program product including a computing program stored on a non-transitory computer-readable storage medium, the computer program including program instructions, which, when executed by a computer, cause the computer to implement the steps of a data asset ownership confirmation method as described in any of the preceding claims.

[0045] This invention provides a data asset ownership confirmation method, system, device, and program product. The method includes: collecting multi-source heterogeneous data and performing data preprocessing to obtain standardized data; generating a fingerprint digest of the standardized data based on its data type; generating an ownership commitment structure based on the ownership information of the standardized data; writing the ownership commitment structure and fingerprint digest into a consortium blockchain to generate an ownership confirmation and storage record; generating a fiscal asset entry data structure according to preset fiscal asset entry specifications; valuing the standardized data based on preset multi-dimensional asset valuation factors to obtain an asset valuation result; and finally, generating a data asset ownership confirmation certificate based on the ownership confirmation and storage record, the fiscal asset entry data structure, and the asset valuation result. This invention achieves reliable ownership confirmation, complete traceability, structural compliance and verifiable verification, asset value re-verification, and executable fiscal asset entry, and is applicable to various data asset management and circulation scenarios. Attached Figure Description

[0046] To more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are merely exemplary, and those skilled in the art can derive other embodiments based on the provided drawings without creative effort.

[0047] Figure 1 A flowchart illustrating a data asset ownership confirmation method provided in an embodiment of the present invention;

[0048] Figure 2 This is a schematic diagram of a data asset ownership confirmation system provided in an embodiment of the present invention. Detailed Implementation

[0049] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0050] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0051] Figure 1 A flowchart of a data asset ownership confirmation method according to an embodiment of the present invention is shown.

[0052] like Figure 1 As shown, the data asset ownership confirmation method according to the embodiments of the present invention may include steps S100, S200, S300, S400, S500, S600, S700 and S800.

[0053] In step S100, multi-source heterogeneous data is collected.

[0054] Specifically, the above steps include:

[0055] Collect heterogeneous data from multiple sources, including industrial video systems, IoT terminals, industrial business systems, and document databases.

[0056] The data structure of the aforementioned standardized data includes video data, IoT time-series data, document data, and tabular data.

[0057] Optionally, the aforementioned industrial video system is industrial video surveillance (RTSP / GB28181), the aforementioned IoT terminal is an IoT sensor (Modbus / MQTT / OPCUA), and the aforementioned document and spreadsheet data is Office / PDF / CSV.

[0058] Next, in step S200, the multi-source heterogeneous data is preprocessed to obtain standardized data.

[0059] Specifically, the above steps include:

[0060] The above data preprocessing includes format standardization, time calibration, structured extraction, and noise filtering.

[0061] The above-mentioned unified format processing includes: for video data, the preprocessed video data structure is "frame sequence + timestamp"; for IoT time series data, the preprocessed IoT time series data structure is a standardized time series structure; for document data, the preprocessed document data structure is "binary content + DOM structure"; and for table data, the preprocessed table data structure is a cell matrix structure.

[0062] To ensure consistency in subsequent weight confirmation, the above time calibration process employs NTP synchronization, local clock offset compensation, and automatic filling of missing time periods. By unifying the time axis, different data can be compared with each other.

[0063] The noise filtering process described above includes: for video data, discarding motion-blurred frames; for IoT time-series data, using Kalman filtering to eliminate sudden jumps; for document data, automatically correcting encoding anomalies; and for tabular data, repairing missing fields.

[0064] In step S300, a fingerprint digest corresponding to the standardized data is generated according to the data type of the standardized data.

[0065] Specifically, the above steps include:

[0066] For video data, keyframes are extracted at preset time intervals (T=2s). The pHsh and aHash of each keyframe are calculated, and the multi-frame digests are serialized and then subjected to SHA256 hashing to obtain the fingerprint digest corresponding to the video data. The video-aware digest generation method used in this embodiment of the invention has resistance to minor editing, does not depend on the video encoding format, and is exceptionally sensitive to content tampering.

[0067] For IoT time-series data, a preset sliding window is used to segment the IoT time-series data (adjacent windows overlap by 0%). A sequence hash is generated for the data in each sliding window, and the windows are sequentially connected to form a time-continuous digest chain to obtain the fingerprint digest corresponding to the IoT time-series data.

[0068] For document data, SHA256 or SM3 is calculated in binary form to obtain the fingerprint digest corresponding to the document data, thus achieving format independence.

[0069] For tabular data, a structured hash tree is generated based on the structured hash tree algorithm, with each cell as a leaf node, each row hash as an intermediate node, and the overall hash of the table as the root node. Any change in any cell will cause a change in the root hash, thus obtaining the fingerprint digest corresponding to the tabular data.

[0070] In step S400, an ownership commitment structure corresponding to the standardized data is generated based on the ownership information of the standardized data.

[0071] Specifically, the above steps include:

[0072] The aforementioned ownership information includes the data production entity (field ORG_ID), data management entity (field MGT_ID), data acquisition device identifier (field DEVICE_ID), responsible person's signature (field USER_SIGN), process step type identifier (field FLOW_STEP), timestamp sequence (field TS_SEQ), and fingerprint digest sequence reference (field HASH_SEQ).

[0073] The ownership commitment structure in this embodiment of the invention establishes an ownership chain from five dimensions: "data producer, manager, equipment, responsible person, and process link," which solves the industry problem that traditional technologies cannot prove "who generates and who is responsible."

[0074] In step S500, the ownership commitment structure and fingerprint digest are written into the consortium blockchain to generate ownership confirmation and storage records and transaction identifiers.

[0075] Specifically, the above steps include:

[0076] The ownership commitment structure and fingerprint digest are written into the consortium blockchain through a smart contract to generate ownership confirmation and storage records and transaction identifiers TxID. The smart contract supports write access control, verification access control, audit access control, block height recording, and rollback version management.

[0077] On-chain storage includes summary information and ownership structure, while off-chain storage includes encrypted raw data or metadata, to achieve privacy protection and scalability.

[0078] In step S600, a fiscal asset entry data structure is generated according to the preset fiscal asset entry specifications.

[0079] Specifically, the above steps include:

[0080] Based on the preset fiscal asset entry specifications, a fiscal entry data structure is generated, which includes a reporting header, a data asset classification field, a data asset valuation field, a ownership subject field, and an XML / JSON message.

[0081] The data structure of the fiscal records is subject to compliance verification, which includes field type verification, mandatory field verification, logical consistency verification, automatic derivation verification of derived items, and integrity verification.

[0082] The above field type validations include verifying that the amount must be a floating-point number and that the date format must be correct; the above mandatory field validations are used to verify the management entity, asset source, etc.; the above logical consistency validations verify that the amount equals the total of the details and that the category conforms to the rules; the automatic derivation validation of derived items is used to automatically classify asset categories by source, including the automatic calculation of fields such as asset category, asset source, management entity, and total amount; and the above completeness validations verify that the summary, valuation, ownership, and other elements are complete.

[0083] In step S700, asset valuation is performed on standardized data based on preset multidimensional asset valuation factors to obtain asset valuation results.

[0084] Specifically, the above steps include:

[0085] Based on preset multidimensional asset valuation factors, a multidimensional asset valuation model is constructed. The aforementioned multidimensional asset valuation factors include quality (Q), usability (U), scarcity (R), scalability (E), and compliance (C).

[0086] Using a multi-dimensional asset valuation model, standardized data is used to evaluate assets and obtain the asset valuation result Value. The calculation formula for the above asset valuation result is: Value = Base × (0.8 + 0.6 × (Q+U+R+E+C) / 500).

[0087] In step S800, a data asset ownership certificate is generated based on the ownership confirmation and storage records, the fiscal entry data structure, and the asset valuation results.

[0088] Specifically, the above steps include:

[0089] Based on the confirmation and storage records, the data structure of fiscal entries, and the asset valuation results, a data asset confirmation certificate and blockchain verification information that can be used for cross-institutional verification are generated.

[0090] The aforementioned asset ownership certificate includes a fingerprint summary, ownership commitment structure, blockchain TxID, block height, valuation result, and verification QR code.

[0091] The QR code is used to access the verification service. The fingerprint digest and ownership information are retrieved through the blockchain to verify the authenticity of the certificate.

[0092] In addition, the data asset ownership confirmation method provided in this embodiment of the invention also includes:

[0093] Generate a traceable audit chain for all rights confirmation, evidence storage, valuation, table entry, modification and verification actions.

[0094] When inconsistent data input is detected, the system rolls back to the previous trusted evidence storage state based on the version number recorded on the blockchain.

[0095] In addition, embodiments of the present invention also provide a data asset ownership confirmation system. Figure 2 This diagram illustrates the structure of a data asset ownership confirmation system according to an embodiment of the present invention. The system specifically includes:

[0096] The data acquisition module is used to collect heterogeneous data from multiple sources.

[0097] The preprocessing module is used to preprocess multi-source heterogeneous data to obtain standardized data;

[0098] The fingerprint digest generation module is used to generate fingerprint digests corresponding to standardized data based on the data type of the standardized data.

[0099] The ownership commitment structure generation module is used to generate ownership commitment structures corresponding to standardized data based on the ownership information of standardized data.

[0100] The consortium blockchain notarization module is used to write the ownership commitment structure and fingerprint digest into the consortium blockchain to generate ownership notarization records and transaction identifiers;

[0101] The asset entry module is used to generate the fiscal asset entry data structure according to the preset fiscal asset entry specifications.

[0102] The asset valuation module is used to perform asset valuation on standardized data based on preset multi-dimensional asset valuation factors, and obtain asset valuation results.

[0103] The certificate generation module is used to generate data asset ownership certificates based on ownership confirmation records, fiscal entry data structure, and asset valuation results.

[0104] In addition, this embodiment of the invention also provides a data asset ownership confirmation device, which includes: a processor and a memory; the memory is used to store one or more program instructions; the processor is used to run one or more program instructions to perform the steps of a data asset ownership confirmation method as described above.

[0105] In addition, embodiments of the present invention also provide a computer program product, which includes computer program instructions that, when executed by a processor, implement the steps of a data asset ownership confirmation method as described above.

[0106] The data asset ownership confirmation method, system, device, and program products provided in this invention have the following technical advantages compared with the prior art:

[0107] The embodiments of this invention form a trusted system integrating "fingerprint chain + ownership chain + blockchain", providing a fiscal entry verification engine rarely seen in existing technologies.

[0108] The embodiments of the present invention, by constructing a verifiable multidimensional valuation model, meet the requirements of financial auditing, support four-party collaborative verification, and enhance the circulation capability of data assets.

[0109] The embodiments of the present invention can automatically generate asset packages for financing and transactions, so as to ensure that the entire process is auditable and traceable.

[0110] This invention achieves tamper-proof and credible ownership confirmation without disclosing the original data, realizing credible ownership confirmation, complete traceability, structural compliance and verifiable verification, asset value re-verification, and fiscal entry execution for data assets. It provides a unified and credible data asset management capability for various institutions and is applicable to various scenarios such as state-owned asset management, enterprise data assetization, and financial data ownership confirmation, with significant innovation and industrial value.

[0111] In this embodiment of the invention, the processor can be an integrated circuit chip with signal processing capabilities. The processor can be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in this embodiment of the invention. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the methods disclosed in this embodiment of the invention can be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software modules can be located in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. The processor reads information from the storage medium and, in conjunction with its hardware, completes the steps of the above methods. The storage medium can be memory, for example, volatile memory or non-volatile memory, or may include both volatile and non-volatile memory. Non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. Volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of RAM are available, such as Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced Synchronous DRAM (ESDRAM), Synchlink DRAM (SLDRAM), and Direct Rambus RAM (DRRAM).The storage media described in the embodiments of this invention are intended to include, but are not limited to, these and any other suitable types of memory. Those skilled in the art will recognize that the functions described in the above examples can be implemented using a combination of hardware and software. When applied software, the corresponding functions can be stored in a computer-readable medium or transmitted as one or more instructions or code on a computer-readable medium. Computer-readable media include computer storage media and communication media, wherein communication media include any medium that facilitates the transmission of computer programs from one place to another. Storage media can be any available medium accessible to general-purpose or special-purpose computers. Although the invention has been described in detail above with general description and specific embodiments, modifications or improvements can be made to it, which will be apparent to those skilled in the art. Therefore, such modifications or improvements made without departing from the spirit of the invention are all within the scope of protection claimed by the invention.

[0112] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Any simple modifications, equivalent changes, or alterations made by those skilled in the art using the disclosed technical content shall fall within the protection scope of the present invention.

Claims

1. A method for confirming ownership of data assets, characterized in that, The method includes: Collect multi-source heterogeneous data; The multi-source heterogeneous data is preprocessed to obtain standardized data; Generate a fingerprint digest corresponding to the standardized data based on the data type of the standardized data; Based on the ownership information of the standardized data, generate the ownership commitment structure corresponding to the standardized data; Write the ownership commitment structure and the fingerprint digest into the consortium blockchain to generate ownership confirmation and storage records and transaction identifiers; Generate the fiscal asset entry data structure according to the preset fiscal asset entry standards; Based on preset multidimensional asset valuation factors, the standardized data is used to perform asset valuation to obtain asset valuation results. Based on the aforementioned ownership confirmation and storage records, the aforementioned fiscal entry data structure, and the aforementioned asset valuation results, a data asset ownership confirmation certificate is generated.

2. The data asset ownership confirmation method according to claim 1, characterized in that, Collect multi-source heterogeneous data, including: Collect heterogeneous data from multiple sources, including industrial video systems, IoT terminals, industrial business systems, and document databases.

3. The data asset ownership confirmation method according to claim 1, characterized in that, The data preprocessing includes format standardization, time calibration, structured extraction, and noise filtering.

4. The data asset ownership confirmation method according to claim 1, characterized in that, Based on the data type of the standardized data, a fingerprint digest corresponding to the standardized data is generated, including: The standardized data structure includes video data, IoT time-series data, document data, and tabular data; For video data, key frames of the video data are extracted according to a preset time interval, and the perceptual hash value of each key frame is calculated to obtain the fingerprint digest corresponding to the video data. For IoT time-series data, a preset sliding window is used to segment the IoT time-series data, and a sequence hash is generated for the data in each sliding window to obtain the fingerprint digest corresponding to the IoT time-series data. For the document data, a cryptographic hash algorithm is used to calculate the fingerprint digest corresponding to the document data; For tabular data, a fingerprint digest corresponding to the tabular data is calculated based on a structured hash tree algorithm.

5. A method for confirming data asset ownership according to claim 1, characterized in that, The ownership information includes the data production entity, data management entity, data collection device identifier, responsible person's signature, process step identifier, and timestamp sequence.

6. The data asset ownership confirmation method according to claim 1, characterized in that, Based on the pre-defined fiscal asset entry standards, a fiscal entry data structure is generated, including: According to the preset fiscal asset entry specifications, a fiscal entry data structure is generated, which includes a reporting header, a data asset classification field, a data asset valuation field, a ownership subject field, and an XML / JSON message. The data structure of the fiscal entry table is subject to compliance verification, which includes field type verification, mandatory field verification, logical consistency verification, derived field verification, and integrity verification.

7. A method for confirming data asset ownership according to claim 1, characterized in that, Based on preset multidimensional asset valuation factors, the standardized data is used to perform asset valuation, resulting in asset valuation results, including: Based on preset multidimensional asset valuation factors, a multidimensional asset valuation model is constructed. The multidimensional asset valuation factors include quality, usability, scarcity, scalability, and compliance. The standardized data is evaluated using the multi-dimensional asset valuation model to obtain asset valuation results.

8. A data asset ownership confirmation system, characterized in that, The system includes: The data acquisition module is used to collect heterogeneous data from multiple sources. The preprocessing module is used to preprocess the multi-source heterogeneous data to obtain standardized data; The fingerprint digest generation module is used to generate a fingerprint digest corresponding to the standardized data based on the data type of the standardized data. The ownership commitment structure generation module is used to generate an ownership commitment structure corresponding to the standardized data based on the ownership information of the standardized data. The consortium blockchain notarization module is used to write the ownership commitment structure and the fingerprint digest into the consortium blockchain to generate a notarization record and a transaction identifier. The asset entry module is used to generate the fiscal asset entry data structure according to the preset fiscal asset entry specifications. The asset valuation module is used to perform asset valuation on the standardized data based on preset multi-dimensional asset valuation factors to obtain asset valuation results. The certificate generation module is used to generate a data asset ownership certificate based on the ownership confirmation and storage record, the fiscal entry data structure, and the asset valuation result.

9. A data asset ownership confirmation device, characterized in that, The device includes: a processor and a memory; The memory is used to store one or more program instructions; The processor is configured to run one or more program instructions to perform the steps of a data asset ownership confirmation method as described in any one of claims 1 to 7.

10. A computer program product, characterized in that, The computer program product includes computer program instructions that, when executed by a processor, implement the steps of a data asset ownership confirmation method as described in any one of claims 1 to 7.

Images