Scientific research data sharing method based on blockchain architecture

Abstract

This invention provides a blockchain-based method for sharing scientific research data. This method leverages the decentralized nature of blockchain to break the data monopoly of traditional centralized systems, enabling the free flow of research data among multiple nodes and improving data sharing efficiency. Secondly, the application of encryption technology and hash functions ensures data security and accuracy during transmission, reducing the risk of data leakage. Furthermore, the application of smart contracts and data version control systems enables automated data management and tracking, improving data compliance and quality. Finally, the establishment of a data indexing and retrieval system allows researchers to quickly find the datasets they need, promoting the sharing and collaboration of scientific research data. In conclusion, this blockchain-based method for sharing scientific research data has significant advantages and broad application prospects.

Description

Technical Field

[0001] This invention specifically relates to a method for sharing scientific research data based on a blockchain architecture. Background Technology

[0002] With the deepening of scientific research and the arrival of the big data era, the importance of scientific research data has become increasingly prominent. As the foundational data for technological development and scientific research, scientific data has become the most important new strategic resource. Data is not only a crucial link in knowledge creation but also a significant manifestation of research results. Therefore, the management, sharing, and compliance checks of scientific research data have become important issues in the current scientific research field.

[0003] In recent years, research institutions and academic journals both domestically and internationally have paid increasing attention to data sharing of research findings. Openness, sharing, and reuse of research papers and scientific data have become an inevitable trend. However, in practice, the management and sharing of research data face numerous challenges, such as data credibility, security, transparency, and compliance. These issues not only affect the quality and utilization value of research data but also hinder the progress and development of scientific research.

[0004] Therefore, a scientific research data sharing method based on blockchain architecture is proposed to solve the above problems. Summary of the Invention

[0005] The purpose of this invention is to address the shortcomings of existing technologies by providing a scientific research data sharing method based on a blockchain architecture, which can effectively solve the aforementioned problems.

[0006] To achieve the above requirements, the technical solution adopted by the present invention is: to provide a scientific research data sharing method based on a blockchain architecture, which includes the following steps:

[0007] S1: The steps to initialize the blockchain network; the network consists of multiple nodes, each of which stores and verifies data. During initialization, the basic parameters of the network are set, including the consensus mechanism and encryption algorithm.

[0008] S2: Steps for creating research data blocks; each research dataset will be encapsulated into a block, which contains basic information about the dataset, including the dataset name, description, creation time, and hash value of the dataset to ensure data integrity and immutability. The hash value maps the input data to a fixed-length 256-bit output using the SHA-256 hash function, with the formula: H(m) = SHA-256(m), where m is the input dataset;

[0009] S3: Steps to define data access permissions; Before uploading research data to the blockchain, define data access permissions through smart contracts, which specify the rules and conditions for data access.

[0010] S4: Steps for uploading and verifying data; Data access permissions are defined, data is uploaded to nodes in the blockchain network, and after uploading, other nodes will verify the data to ensure its integrity and authenticity. The verification process is completed by comparing whether the hash value of the uploaded data is consistent with the hash value stored in the block.

[0011] S5: Steps for confirming consensus mechanism; Blockchain networks use consensus mechanisms to ensure that all nodes recognize the data. They use PoW and PoS consensus mechanisms. In PoW, nodes compete for the right to record transactions by solving complex mathematical problems, while in PoS, nodes obtain the right to record transactions based on the number of tokens they hold. Once a node successfully adds its data block to the blockchain, other nodes will confirm the validity of the data.

[0012] S6: Steps for data indexing and retrieval; Establish a data indexing system that indexes and retrieves data based on attributes such as dataset name, keywords, and creation time, allowing users to quickly find relevant datasets by entering keywords;

[0013] S7: Steps for data sharing and collaboration; datasets are uploaded to the blockchain, and access permissions are defined, allowing other researchers to access these datasets according to their permissions;

[0014] S8: Steps for implementing data version control; Establish a data version control system to track changes to the dataset. Each time the dataset is updated, a new block is generated and added to the blockchain to track the historical versions and changes of the dataset.

[0015] S9: Steps to ensure data security and privacy; ensuring the security and accuracy of data during transmission, while the decentralized nature of blockchain means that data no longer depends on a single server or institution, thereby reducing the risk of data being tampered with or stolen;

[0016] S10: Steps for conducting data audits and compliance checks; Regularly conduct data audits and compliance checks, which are automatically executed through smart contracts. Smart contracts periodically check whether the dataset meets specific standards and regulations. If any non-compliance is found, the smart contract will trigger an alarm or take other appropriate measures.

[0017] The advantages of this blockchain-based scientific research data sharing method are as follows:

[0018] (1) Improved accuracy of data auditing: By calculating the first and second derivatives of the data, the instantaneous rate of change and acceleration of the data can be assessed more accurately, thereby discovering abnormal or non-compliant behaviors in the data. By calculating the integral value of the data, the cumulative effect of the data over the entire time range can be assessed, further revealing the hidden characteristics and trends of the data.

[0019] (2) Enhanced data sharing security: This method takes into account the security and privacy protection of data. In particular, when dealing with complex data, it ensures the security and privacy of data during the sharing process through reasonable encryption and anonymization.

[0020] (3) Enhanced data compliance assessment capabilities: By introducing compliance standards within the complex domain, such as the modulus and argument ranges of complex derivatives and complex integrals, data compliance can be assessed more comprehensively. This method also combines numerical methods and complex number operations, making compliance checks more accurate and efficient.

[0021] (4) Promotes the opening and sharing of scientific research data: This method provides strong technical support for the opening and sharing of scientific research data, and helps to promote the standardization, normalization and sharing of scientific research data. By improving the quality and credibility of data, it enhances the utilization value and influence of scientific research data, and promotes the progress and development of scientific research. Attached Figure Description

[0022] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, use the same reference numerals to denote the same or similar parts. The illustrative embodiments of this application and their descriptions are used to explain this application and do not constitute an undue limitation of this application. In the drawings:

[0023] Figure 1 A schematic diagram of a blockchain-based scientific research data sharing method according to an embodiment of this application is shown. Detailed Implementation

[0024] 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 specific embodiments.

[0025] In the following description, references to "an embodiment," "an embodiment," "an example," "example," etc., indicate that the described embodiment or example may include a particular feature, structure, characteristic, property, element, or limitation, but not every embodiment or example necessarily includes that particular feature, structure, characteristic, property, element, or limitation. Furthermore, the repeated use of the phrase "an embodiment according to this application," while possibly referring to the same embodiment, does not necessarily refer to the same embodiment.

[0026] For simplicity, certain technical features known to those skilled in the art are omitted in the following description.

[0027] According to one embodiment of this application, a method for sharing scientific research data based on a blockchain architecture is provided, such as... Figure 1 As shown, it includes the following steps:

[0028] Step 1: Initialize the blockchain network

[0029] First, a blockchain network needs to be initialized, consisting of multiple nodes, each capable of storing and verifying data. These nodes can be research institutions, universities, data centers, etc. During initialization, basic network parameters need to be set, such as the consensus mechanism and encryption algorithm. This step is fundamental to building a blockchain data sharing platform, ensuring the network's stability and security.

[0030] Step 2: Create research data blocks

[0031] Each research dataset will be encapsulated into a block containing basic information about the dataset, such as its name, description, and creation time. Additionally, it must include the dataset's hash value to ensure data integrity and immutability. The hash value is calculated using a complex hash function that maps the input data to a fixed-length output (typically 256 bits). For example, the SHA-256 hash function can be used, with the formula: H(m) = SHA-256(m), where m is the input dataset.

[0032] Step 3: Define data access permissions

[0033] Before uploading research data to the blockchain, access permissions need to be defined. This can be achieved through smart contracts, which are automatically executed contracts on the blockchain that specify the rules and conditions for data access. For example, it can be set so that only specific research institutions or researchers can access certain datasets.

[0034] Step 4: Data Upload and Verification

[0035] Once data access permissions are defined, data can be uploaded to a node in the blockchain network. After uploading, other nodes will verify the data to ensure its integrity and authenticity. The verification process is accomplished by comparing the hash value of the uploaded data with the hash value stored in the block.

[0036] Step 5: Consensus Mechanism Confirmation

[0037] Blockchain networks use consensus mechanisms to ensure that all nodes agree on the data. For example, consensus mechanisms such as Proof-of-Work (PoW) or Proof-of-Stake (PoS) can be used. In PoW, nodes compete for the right to record transactions by solving complex mathematical problems, while in PoS, nodes gain the right to record transactions based on the number of tokens they hold. Once a node successfully adds its data block to the blockchain, other nodes will confirm the validity of that data.

[0038] Step Six: Data Indexing and Retrieval

[0039] To facilitate researchers' quick access to desired datasets, a data indexing system needs to be established. This system can index and retrieve datasets based on attributes such as name, keywords, and creation date. This allows researchers to quickly find relevant datasets by entering keywords.

[0040] Step Seven: Data Sharing and Collaboration

[0041] Once datasets are uploaded to the blockchain and access permissions are defined, other researchers can access them according to their permissions. This promotes the sharing and collaboration of scientific data, enabling researchers from different research institutions to jointly analyze and utilize these datasets.

[0042] Step 8: Data Version Control

[0043] In scientific research, datasets may be continuously updated and improved. Therefore, a data version control system is needed to track changes to the dataset. Each time the dataset is updated, a new block is generated and added to the blockchain. This makes it easy to track the historical versions and changes of the dataset.

[0044] Step Nine: Data Security and Privacy Protection

[0045] Blockchain technology offers robust data encryption and privacy protection. Encryption ensures the security and accuracy of data during transmission. Furthermore, the decentralized nature of blockchain eliminates reliance on a single server or institution, reducing the risk of data tampering or theft.

[0046] Step 10: Data Audit and Compliance Check

[0047] To ensure the compliance and quality of research data, regular data audits and compliance checks are necessary. This can be automated through smart contracts, which periodically check whether datasets meet specific standards and regulations. If any non-compliance is detected, the smart contract will automatically trigger an alert or take other appropriate measures.

[0048] According to one embodiment of this application, the specific details of this blockchain-based scientific research data sharing method are as follows:

[0049] Step 1: Initialize the blockchain network

[0050] Specific implementation:

[0051] Choose a suitable blockchain platform and a blockchain framework suitable for sharing scientific research data.

[0052] Configure network parameters, including the number of nodes, consensus mechanism (such as proof-of-work, proof-of-stake, etc.), and encryption algorithm.

[0053] Deploy a blockchain network to ensure that all nodes can communicate and synchronize data normally.

[0054] Step 2: Create research data blocks

[0055] Specific implementation:

[0056] Preprocessing of research data, including data cleaning and format conversion, is necessary to ensure data consistency and readability.

[0057] Calculate the hash value of the data using a hash function such as SHA-256, mapping the input data to a fixed-length output. The formula is: H(m) = SHA-256(m), where m is the input dataset.

[0058] The basic information of the dataset (such as name, description, creation time) and hash value are encapsulated into a block.

[0059] Add timestamps and unique identifiers to blocks to ensure the timeliness and traceability of data.

[0060] Step 3: Define data access permissions

[0061] Specific implementation:

[0062] Use smart contract technology to write rules and conditions for data access permissions.

[0063] Define permissions for the dataset, such as visitor identity, access time, and access method.

[0064] Deploying smart contracts onto the blockchain ensures that all nodes can recognize and verify access permissions.

[0065] Step 4: Data Upload and Verification

[0066] Specific implementation:

[0067] The packaged scientific research data block is uploaded to a node in the blockchain network.

[0068] Other nodes verify the uploaded data blocks by comparing their hash values ​​with those stored in the blocks.

[0069] If the verification passes, the data block is added to the blockchain, and the node's local ledger is updated.

[0070] Step 5: Consensus Mechanism Confirmation

[0071] Specific implementation:

[0072] Depending on the chosen consensus mechanism (such as proof-of-work, proof-of-stake, etc.), nodes begin competing for the right to record transactions.

[0073] In Proof-of-Work, nodes compete for the right to record transactions by solving complex mathematical problems; in Proof-of-Stake, nodes gain the right to record transactions based on the number of tokens they hold.

[0074] Once a node successfully adds its data block to the blockchain, other nodes will confirm the validity of the data and update their own local ledgers.

[0075] Step Six: Data Indexing and Retrieval

[0076] Specific implementation:

[0077] Establish a data indexing system to index datasets based on attributes such as name, keywords, and creation time.

[0078] Use search engines or database technology to achieve fast data retrieval and querying.

[0079] It provides a user-friendly interface and interactive methods, making it easy for researchers to use data indexing and retrieval functions.

[0080] Step Seven: Data Sharing and Collaboration

[0081] Specific implementation:

[0082] Based on the access permissions defined in the smart contract, other researchers are allowed to access and download research datasets.

[0083] It provides data sharing interfaces and APIs to facilitate researchers in integrating data into their research projects.

[0084] Encourage collaboration and communication among researchers to jointly analyze and utilize research datasets.

[0085] Step 8: Data Version Control

[0086] Specific implementation:

[0087] Establish a version control system for each research dataset to record the historical versions and changes of the dataset.

[0088] Each time the dataset is updated, a new block is generated and added to the blockchain. The new block contains the updated data and its hash value.

[0089] It provides version comparison and rollback functions, making it easy for researchers to view historical versions of the dataset and make necessary modifications.

[0090] Step Nine: Data Security and Privacy Protection

[0091] Specific implementation:

[0092] Encryption techniques (such as symmetric encryption, asymmetric encryption, etc.) are used to encrypt scientific research data.

[0093] Security protocols (such as HTTPS, TLS, etc.) are used during data transmission to ensure the confidentiality and integrity of the data.

[0094] Sensitive data is anonymized to protect personal privacy and trade secrets.

[0095] Regularly back up and restore your data to prevent data loss or corruption.

[0096] Step S10 specifically includes:

[0097] S101: Define compliance standards that, in addition to considering the first derivative of data change, i.e. rate, also consider its second derivative, i.e. acceleration, as well as the integral value of the data over the entire time range, and introduce the complex domain to handle potentially periodic or oscillating data.

[0098] S102: Data preprocessing to ensure that the data is continuous and differentiable, and to consider using complex representation to handle periodic or oscillating data;

[0099] S103: Calculate the first and second derivatives of the data.

[0100] First derivative formula: This represents the instantaneous rate of change of data D with respect to time t;

[0101] Second derivative formula: The instantaneous rate of change of data, i.e., acceleration;

[0102] S104: Calculate the integral value of the data, integration formula. This represents the cumulative effect of data D over the time range [t0, t1].

[0103] S105: Introduce complex numbers for compliance assessment. If the data is periodic or oscillatory, use complex number representation to better describe its characteristics; define compliance criteria in the complex domain, including the modulus and argument range of complex derivatives and complex integrals.

[0104] S106: Apply numerical methods and complex number operations, using numerical methods to approximate the calculation of derivatives; for complex data, use the rules of complex number operations to calculate derivatives and integrals;

[0105] S107: Compliance Check;

[0106] Check whether the first derivative v(t) satisfies |v(t)|≤C1, where C1 is the set upper limit of the speed;

[0107] Check whether the second derivative a(t) satisfies |a(t)|≤C2, where C2 is the set upper limit of acceleration;

[0108] Check the score Does it meet a specific range or condition?

[0109] For complex data, check whether the modulus and argument of the complex derivative and complex integral meet the set range;

[0110] S108: Recording and Reporting: Record the results of compliance checks, including the evaluation results of first derivatives, second derivatives, integral values, and complex properties.

[0111] The embodiments described above are merely examples of several implementations of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these all fall within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the claims.

Claims

1. A method for sharing scientific research data based on a blockchain architecture, characterized in that, Includes the following steps: S1: The steps to initialize the blockchain network; the network consists of multiple nodes, each of which stores and verifies data. During initialization, the basic parameters of the network are set, including the consensus mechanism and encryption algorithm. S2: Steps for creating research data blocks; each research dataset will be encapsulated into a block, which contains basic information about the dataset, including the dataset name, description, creation time, and hash value of the dataset to ensure data integrity and immutability. The hash value maps the input data to a fixed-length 256-bit output using the SHA-256 hash function, with the formula: H(m) = SHA-256(m), where m is the input dataset; S3: Steps for defining data access permissions; Before uploading scientific research data to the blockchain, data access permissions are defined and implemented through smart contracts, which stipulate the rules and conditions for data access. S4: Steps for uploading and verifying data; Data access permissions are defined, and data is uploaded to nodes in the blockchain network. After the data is uploaded, other nodes will verify it to ensure its integrity and authenticity. The verification process is completed by comparing whether the hash value of the uploaded data is consistent with the hash value stored in the block. S5: Steps for confirming consensus mechanism; Blockchain networks use consensus mechanisms to ensure that all nodes recognize the data. They use PoW and PoS consensus mechanisms. In PoW, nodes compete for the right to record transactions by solving complex mathematical problems, while in PoS, nodes obtain the right to record transactions based on the number of tokens they hold. Once a node successfully adds its data block to the blockchain, other nodes will confirm the validity of the data. S6: Steps for data indexing and retrieval; Establish a data indexing system that indexes and retrieves data based on the dataset's name, keywords, and creation time attributes, allowing users to quickly find relevant datasets by entering keywords; S7: Steps for data sharing and collaboration; The datasets are uploaded to the blockchain, and access permissions are defined, allowing other researchers to access these datasets based on their permissions. S8: Steps for implementing data version control; Establish a data version control system to track changes to the dataset. Each time the dataset is updated, a new block is generated and added to the blockchain to track the historical versions and changes of the dataset. S9: Steps for data security and privacy protection; This ensures the security and accuracy of data during transmission, while the decentralized nature of blockchain means that data no longer depends on a single server or institution, thereby reducing the risk of data being tampered with or stolen. S10: Steps for conducting data audits and compliance checks; Regular data audits and compliance checks are performed automatically via smart contracts. The smart contracts periodically check whether the dataset meets the set standards and regulations. If any non-compliance is found, the smart contracts will trigger an alarm or take other measures. Step S10 specifically includes: S101: Define compliance standards that, in addition to considering the first derivative of data change, i.e. rate, also consider its second derivative, i.e. acceleration, as well as the integral value of the data over the entire time range, and introduce the complex domain to handle existing periodic or oscillating data. S102: Data preprocessing to ensure that the data is continuous and differentiable, and to consider using complex representation to handle periodic or oscillating data; S103: Calculate the first and second derivatives of the data. First derivative formula: , representing the instantaneous rate of change of data D with respect to time t; Second derivative formula: , which represents the instantaneous rate of change of the data, i.e., acceleration; S104: Calculate the integral value of the data, integration formula. This indicates that data D is within a certain time range. The cumulative effect within; S105: Introduce complex numbers for compliance assessment. If the data is periodic or oscillatory, use complex number representation to better describe its characteristics; define compliance criteria in the complex domain, including the modulus and argument range of complex derivatives and complex integrals. S106: Apply numerical methods and complex number operations, using numerical methods to approximate the calculation of derivatives; for complex data, use the rules of complex number operations to calculate derivatives and integrals; S107: Compliance Check; Check if the first derivative v(t) satisfies ,in It is the set upper limit of the rate; Check if the second derivative a(t) satisfies ,in It is the set upper limit of acceleration; Check the score Does it meet the set range or conditions? For complex data, check whether the modulus and argument of the complex derivative and complex integral meet the set range; S108: Recording and Reporting: Record the results of compliance checks, including the evaluation results of first derivatives, second derivatives, integral values, and complex properties.

2. The scientific research data sharing method based on blockchain architecture according to claim 1, characterized in that, Step S1 specifically includes: S11: Select a suitable blockchain platform as a blockchain framework suitable for sharing scientific research data; S12: Set network parameters, including the number of nodes and consensus mechanism. The consensus mechanism includes proof-of-work, proof-of-stake, and encryption algorithm. S13: Deploy a blockchain network to ensure that all nodes can communicate and synchronize data normally.

3. The scientific research data sharing method based on blockchain architecture according to claim 1, characterized in that, Step S2 specifically includes: S21: Preprocess scientific research data, including data cleaning and format conversion, to ensure data consistency and readability; S22: Calculate the hash value of the data, using the SHA-256 hash function to map the input data to a fixed-length output; S23: Encapsulate the basic information of the dataset, including name, description, creation time, and hash value, into a block; S24: Add timestamps and unique identifiers to blocks to ensure the timeliness and traceability of data.

4. The scientific research data sharing method based on blockchain architecture according to claim 1, characterized in that, Step S3 specifically includes: S31: Use smart contract technology to write rules and conditions for data access permissions; S32: Define the visitor's identity, access time, access method, and permissions for the dataset; S33: Deploy smart contracts to the blockchain to ensure that all nodes can recognize and verify access permissions; Step S4 specifically includes: S41: Upload the packaged scientific research data block to a node in the blockchain network; S42: Other nodes verify the uploaded data blocks by comparing their hash values ​​with the hash values ​​stored in the blocks. S43: If the verification passes, add the data block to the blockchain and update the node's local ledger.

5. The scientific research data sharing method based on blockchain architecture according to claim 1, characterized in that, Step S5 specifically includes: S51: Based on the chosen consensus mechanism, nodes begin competing for the right to record transactions; S52: In Proof-of-Work, nodes compete for the right to record transactions by solving complex mathematical problems; in Proof-of-Stake, nodes obtain the right to record transactions based on the number of tokens they hold. S53: Once a node successfully adds its data block to the blockchain, other nodes will confirm the validity of the data and update their own local ledgers; Step S6 specifically includes: S61: Establish a data indexing system to index datasets based on their name, keywords, and creation time attributes; S62: Use search engines or database technology to achieve fast data retrieval and query.

6. The scientific research data sharing method based on blockchain architecture according to claim 1, characterized in that, Step S7 specifically includes: S71: Based on the access permissions defined in the smart contract, other researchers are allowed to access and download research datasets; S72: Provides data sharing interfaces and APIs to facilitate researchers in integrating data into their research projects; Step S8 specifically includes: S81: Establish a version control system for each research dataset to record the historical versions and changes of the dataset; S82: Each time the dataset is updated, a new block is generated and added to the blockchain. The new block contains the updated data information and hash value. S83: Provides version comparison and rollback functions, making it convenient for researchers to view historical versions of datasets and make modifications; Step S9 specifically includes: S91: Use encryption technology to encrypt scientific research data; S92: Use security protocols during data transmission to ensure the confidentiality and integrity of the data; S93: Sensitive data must be anonymized to protect personal privacy and trade secrets; S94: Regularly back up and restore data to prevent data loss or corruption.

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