A transaction-based big data rights sharing method and system

Abstract

The present invention discloses a transaction-based big data rights sharing method and system, which fully explores the value of data through price transactions, realizes the separation of data usage rights, income rights and ownership rights, and then realizes the sharing of data rights throughout the entire network, and provides a non-tamperable and anti-repudiation mechanism for the core data in the system. The method includes: S1 calculates the cost of data use based on data consumption needs; S2 distributes data rights and interests income; S3 establishes a non-tamperable and anti-repudiation mechanism for all consumption and income records in the platform. Under the premise of protecting big data privacy, the present invention can eliminate data islands while avoiding the occurrence of data price discrimination.

Description

Technical Field

[0001] The present invention relates to the separation of ownership, income rights and usage rights of big data, as well as rights and interests sharing, and in particular to a transaction-based big data rights and interests sharing method and system. Background Art

[0002] In the current mainstream network big data usage process, due to the particularity of big data and the credibility of users, the value of big data cannot be truly brought into play for the purpose of protecting big data, making big data sharing a false proposition. The present invention distinguishes the ownership, income rights and usage rights of big data and designs a billing method for the latter two, thereby realizing the separation of these three rights and interests on the basis of protecting the privacy of big data, thereby truly realizing the sharing of big data usage rights. Summary of the invention

[0003] The purpose of the present invention is to overcome the defects of existing big data that either all of them are shared without reservation or desensitized data level sharing is provided through complicated encryption modes, and to provide a transaction method for charging separately for usage rights and income rights, so as to realize the sharing of big data usage rights while protecting the privacy and ownership of big data, and objectively and truly bring into play the value of big data.

[0004] To achieve the above purpose, the present invention proposes the following technical solution: a transaction-based big data rights sharing method, comprising:

[0005] S1 is oriented to data consumption needs and calculates the cost of data usage;

[0006] S2 distributes data equity benefits;

[0007] S3 establishes an unalterable and anti-repudiation mechanism for all consumption and revenue records on the platform.

[0008] Preferably, the data consumption demand is described by a data demand description item DReqD_Onto, and the calculation of the data usage cost includes at least the following steps:

[0009] S1-1: The system constructs the consumption item data rights composition table ConsmDEityDetal based on the data demand description items and the data rights DEityD_Onto as the unit, and then generates the data demand description items based on the demand description ontology DReqD_Onto;

[0010] S1-2: Calculate the data usage cost DPayment according to the data demand description item;

[0011] Preferably, DReqD_Onto includes at least:

[0012] DReqD_Onto := <DEityPurcReqD_Onto, DAppReqD_Onto, DReqD_ID, Requester Digital Signature, Platform Digital Signature>

[0013] DEityPurcReqD_Onto := <BDD_Onto, Expected Purchase Completion Time, Requester's Pre - quote, Requester's Account ID, Contact Phone Number, Email, Order Placement Time>

[0014] DAppReqD_Onto := <BDD_Onto, Comparison Index, Description of Comparison Method, Function ID or Analysis Requirement, Expected Completion Time of Analysis Function, Requester's Pre - quote, Requester's Account ID, Contact Phone Number, Email>

[0015] BDD_Onto := <Data Category, Subordinate City, Start Date and Month of Data, End Date and Month of Data, Data Volume, Data Entries, Expected Start Time of Data Validity, Expected End Time of Data Validity, Subordinate Province, Latest Update Time, ConsmDEityDetal>

[0016] Among them, DReqD_ID is the data requirement ID, which is a string and unique within the system; the data category table is the natural description of the classification to which the matter described by the data belongs; the comparison index is a certain field of the big data record, and the comparison method is the analysis method that can be carried out for the comparison index, such as growth rate, year - on - year, month - on - month, etc.; the analysis requirement is a natural language description, and the function ID is the ID of the analysis function provided by the platform; BDD_ID is a string and unique within the system, identifying BDD_Onto, and ConsmDEityDetal is the consumption item data rights and interests composition table.

[0017] Preferably, ConsmDEityDetal at least includes:

[0018] ConsmDEityDetal := <List of Data Composition Items, Consumption Item Data Rights and Interests Composition Table Record ID, Platform Digital Signature>

[0019] <List of Data Composition Items> := <[Data Composition Item 1, Data Composition Item 2, Data Composition Item i , …, Data Composition Item n >,

[0020] <Data Composition Item i > := <Data Rights and Interests ID i , Corresponding Data Volume Proportion>,

[0021] Among them, the data volume proportion refers to the proportion of the data volume corresponding to the current data rights and interests ID in the total data volume of all data in the list of data composition items.

[0022] Preferably, the data rights and interests DEityD_Onto at least include:

[0023] DEityD_Onto := <BDD_ID, the platform account ID that owns the BDD_ID, data rights and interests ID, total purchase price of the rights and interests, average purchase price per single piece of data, referrer, number of uses, usage frequency, return on investment, current total earnings, unit of current total earnings, rights and interests purchase time, remaining duration of rights and interests, remaining days, platform digital signature>;

[0024] BDD_ID := <data category, affiliated city, start year and month of data, end year and month of data, data volume, affiliated province, affiliated organization, publisher ID, data brief introduction, latest update time, Data, Data_checksum, checksum_func>;

[0025] Data is a list of data entity records, and Data_checksum is the data checksum value obtained after processing Data based on the data checksum function checksum_func and signed by the platform digital signature;

[0026] The data rights and interests ID is a string, unique within the system;

[0027] Preferably, the data usage cost at least includes:

[0028]

[0029] Among them, DPayment user_id is the fee that the platform account user_id should pay to the platform, including the price of the used data and the price of the used data analysis function; is the billing coefficient function of the data level, with the input being the data component ditem i , and the output being the price floating coefficient corresponding to ditem i ; |ditem i | represents the number of data records of the smallest atomic unit in the data component ditem i ; ρ is the single-piece data usage price calculation function, and the output is the price required to repeatedly view a single data record of the smallest atomic unit within a fixed period; dequity i is the data rights and interests ID; λ is the price function of a single data analysis and result presentation function, with the input being the function ID and the output being the price of the function; func_id is the ID of the currently used data analysis function.

[0030] Preferably, the steps for distributing the data rights and interests earnings at least include the following:

[0031] S2-1: The system generates a data consumption record DConsmD_Onto based on the user's payment;

[0032] S2-2: For a single data right, calculate the data right revenue Prf and generate a data right revenue log DEityPrft_Onto;

[0033] S2-3: Based on S2-2, the system updates the newly added data right revenue to the revenue balance of the platform account ID to which each data right ID involved belongs;

[0034] Preferably, DConsmD_Onto includes at least:

[0035] DConsmD_Onto := <DEityPurcD_Onto, DReqD_ID, data consumption record ID, requester digital signature, platform digital signature>,

[0036] DEityPurcD_Onto := <platform account ID of the order placer, TotalFee, payment time, payment account, payment method, payer digital signature>,

[0037] The data consumption record ID is composed of a string, automatically generated by the system, and unique within the system; TotalFee is the payment amount; DConsmD_Onto indicates the fact that the user has consumed data.

[0038] Preferably, the data right revenue log DEityPrft_Onto includes at least:

[0039] DEityPrft_Onto := <user_id, corresponding data consumption record ID, data right ID used, dataM_Per, platform data right revenue this time, account ID to which the data right ID belongs, Pft, platform digital signature>,

[0040] Pft := (DPayment user_id - λ(func_id)) * dataM_Per,

[0041] where user_id is the account ID of the user, Pft is the revenue of the account ID to which the data right ID belongs this time, dataM_Per is the data volume ratio corresponding to the data right ID, λ is the price function of the single data analysis and result presentation function, the input is the function ID, and the output is the price of the function; func_id is the data analysis function ID currently used, and DPayment user_id is the fee that the platform account user_id should pay to the platform.

[0042] Preferably, the establishment of an unalterable and non-repudiation mechanism for all consumption and revenue records in the platform at least includes:

[0043] S3-1: Both the platform and its users hold asymmetric encryption certificates, which are used to sign their operation records on the platform;

[0044] S3-2: All data consumption and data equity income records on the platform belong to their respective platform account IDs, and are based on the SHA256-like hash function φ as the hash algorithm. For each record, they are organized into two chains in chronological order. The head of the chain is a string chHead with a length of 256, which is the root hash value of the latest data equity income chain. The end of the chain is an initial genesis string. The chain is composed of blocks connected head to tail;

[0045] S3-3: Each block has only one record. The block structure is DEity_Blk, which includes at least:

[0046] DEity_Blk:=<(chHead,Record,seed,chTail)>,

[0047] Record:=DConsmD_Onto|DEityPrft_Onto,

[0048] chHead:=φ(Record,seed,Tail),

[0049] Among them, seed is a random number generation function;

[0050] The chain points to the next block by storing the next block header chHead in the block tail chTail;

[0051] S3-4: Generate corresponding blockchains for each user account’s user consumption order log, data rights, data rights income log, and system core data;

[0052] S3-5: Each user account saves the data rights and interests chain of itself and another account, and the system saves the blockchain of all data. The data of each user account in the system has at least three redundant backups in the system, and the total number of backups of each user account data in the system is odd;

[0053] S3-6: The system provides a blockchain accounting function, and each user uses the accounting function to verify and record the data received from other accounts;

[0054] S3-7: All functions provided by the system cannot be changed by user accounts.

[0055] Preferably, each user uses an accounting function to verify and account the data received from other accounts, which at least includes:

[0056] T8-1: User A receives block data U_BDataList of other accounts sent by the system;

[0057] T8-2: User A verifies the correctness of the digital signature in U_BDataList. If it is correct, it jumps to the next step. Otherwise, it sends an Error_Ini_BData message to the system.

[0058] T8-3: User A parses subBMData from U_BDataList = (bChainName i ,blockData i , merkletr_root i ) tuple, block blockData i Go to the local blockchain bChainName i In the process, based on the new blockchain, the local Merkle tree is updated to obtain the root node of the updated Merkle tree;

[0059] T8-4: User A compares the Merkle Tree root node merkletr_root of root and subBMData i Are they equal? ​​If they are equal, the process ends. If they are not equal, ErrChck_BData information is sent to the system.

[0060] T8-5: The system parses the received ErrChck_BData to get the corresponding blockchain account user_id, packages all the latest blockchains and corresponding Merkle Tree data under the user_id account in the system, and sends them to the sender in ErrChck_BData. ecb ;

[0061] T8-6: The system parses the received Error_Ini_BData to obtain the U_BDataList, and then performs a i ,blockData i , merkletr_root i) tuple, reconstruct U_BDataList, get the new block data new_U_BDataList, if new_U_BDataList is different from U_BDataList, send new_U_BDataList to the sender of Error_Ini_BData, otherwise, parse the corresponding blockchain account user_id from U_BDataList, pack all the latest blockchains and corresponding Merkle Tree data under the user_id account in the system, and send them to the sender of Error_Ini_BData sender eib ;

[0062] in,

[0063] U_BDataList:=<[user_id,(bChainName1,blockData1,merkletr_root1),…,(bChainName i ,blockData i ,merkletr_root i ),…]>

[0064] Error_Ini_BData:=<('ErrorIniBData',U_BDataList,sender eib )>;

[0065] ErrChck_BData:=<('ErrChckBData',U_BDataList,sender ecb )>;

[0066] user_id is the platform account corresponding to the current block data U_BDataList, bChainName i is the blockchain name, blockData i For blocks, merkletr_root i bChainName i Add new block blockData i After that, the corresponding Merkle tree is updated with a new root node; sender eib The sender of the message Error_Ini_BData; sender ecb The sender of the ErrChck_BData message.

[0067] The present invention also proposes a transaction-based big data rights and interests sharing system, which at least includes: a data usage cost calculation unit DUC_CM, a data rights and interests benefit distribution unit DEP_DM, and a data record blockchain generation unit DBC_GM; DUC_CM completes data consumption needs and calculates data usage costs, DEP_DM distributes data rights and interests benefits, and DBC_GM establishes an unalterable and anti-repudiation mechanism for all consumption and income records in the platform.

[0068] Preferably, the data usage cost calculation unit DUC_CM at least includes a data composition analysis module DCA_CM, a data consumption demand generation module DCR_GM and a data usage cost calculation module DUP_CM;

[0069] The DCA_CM generates a consumption item data rights composition table ConsmDEityDetal based on the consumption request submitted by the user and in units of data rights;

[0070] The DCR_GM generates a data requirement description item having the same structure as DReqD_Onto based on the consumption request submitted by the user and ConsmDEityDetal;

[0071] The DUP_CM is based on the data requirement description item and the following function, according to the following about DPayment user_id The formula is used to calculate the price that user user_id should pay for this data consumption:

[0072]

[0073] Preferably, the data equity benefit distribution unit at least includes a data consumption log generation module DCL_GM, a data equity benefit calculation module DEP_CM, a data equity benefit log generation module DEPL_GM and a data equity update module DEU_GM;

[0074] The DCL_GM generates a data consumption record, the structure of which is DConsmD_Onto described in S2-1;

[0075] The DEP_CM extracts relevant values ​​based on the data consumption records generated by DCL_GM and calculates the data equity income according to the following function:

[0076] Pft:=(DPayment user_id -λ(func_id))*dataM_Per;

[0077] DEPL_GM generates a data equity income log with structure like DEityPrft_Onto based on DConsmD_Onto and Pft;

[0078] Based on DEityPrft_Onto, DEU_GM finds the user_id to which the data equity ID belongs, and updates Pft to the income balance of user_id.

[0079] Preferably, the data record blockchain generation unit DBC_GM at least includes a key certificate generation module Crypto_GM, a block generation module B_GM, a blockchain Merkle Tree maintenance module BNMerkleTr_MM, and a blockchain accounting module BA_GM;

[0080] Crypto_GM is responsible for creating a unique PKI key pair for the entire network based on the basic information submitted by the user.

[0081] B_GM creates the initial genesis block based on the initial genesis string, and generates corresponding blockchains for user consumption order logs, data rights, data rights income logs, and system core data based on the DEity_Blk structure.

[0082] DEity_Blk:=<(chHead,Record,seed,chTail)>,

[0083] Record:=DConsmD_Onto|DEityPrft_Onto,

[0084] chHead:=φ(Record,seed,Tail),

[0085] Among them, seed is a random number generation function;

[0086] The chain points to the next block by storing the next block header chHead in the block tail chTail;

[0087] BNMerkleTr_MM generates a traditional Merkle tree for each blockchain based on the Merkle Tree algorithm, with the root node serving as the basis for tamper-proofing.

[0088] BA_GM is used to maintain the blockchain data of the system on different user ends.

[0089] Preferably, the blockchain accounting module BA_GM at least includes: a verification module Ck_CM, and an error handling module ErrDeal_CM;

[0090] Ck_CM is responsible for verifying the data received from other accounts. If the received data does not match the verification result, the data will be discarded and reported to the system. Otherwise, the received data will be entered into the blockchain of the corresponding account.

[0091] ErrDeal_CM is responsible for reviewing the data that failed the verification and sending the reviewed data.

[0092] The present invention distinguishes the ownership, usage rights, and income rights of big data, separates the three through transactions and billing methods, and realizes independent ownership of the three, so that the usage rights of big data can be shared while keeping the ownership of big data completely belonging to the real owner, and based on the billing method of different rights and interests, the deserved interests of the big data owner and the purchaser of the income rights are protected. At the same time, through the independent billing method of data analysis functions, the interests of data analysis designers are protected, and the privacy of big data is protected.

[0093] The big data rights and interests sharing method of the present invention can be used to guide the establishment of a big data rights and interests sharing system, wherein the non-tamperability and non-repudiation mechanism can serve as the basis for the value of big data, thereby forming a distributed network of the big data rights and interests sharing system, further enhancing the value, benefits, and contribution of big data to society. BRIEF DESCRIPTION OF THE DRAWINGS

[0094] Figure 1 This is the transaction-based big data rights sharing process of the present invention;

[0095] Figure 2 It is a structural block diagram of the transaction-based big data rights and interests system of the present invention;

[0096] Figure 3 Data usage cost calculation unit;

[0097] Figure 4 Data equity income distribution unit;

[0098] Figure 5 Data equity income distribution unit;

[0099] Figure 6 is an operation flow chart of an embodiment of the present invention; DETAILED DESCRIPTION

[0100] The technical solutions of the embodiments of the present invention will be clearly and completely described below in combination with the present invention. Figure 3 It is a flow chart of an embodiment of the present invention.

[0101] A transaction-based big data rights and interests sharing method and system disclosed in an embodiment of the present invention mainly provides a transaction-based big data rights and interests sharing method; the method is mainly composed of a big data description ontology, a data rights and interests description ontology, a data rights and interests benefit description ontology, a data demand description ontology, a data consumption description ontology, a data access rights verification method, a system role, a data billing method, a data rights and interests benefit billing method, a data rights and interests benefit distribution method, and an unalterable and anti-repudiation mechanism.

[0102] Scenario assumptions:

[0103] The system contains structured data X_BData about industry X, and provides data analysis functions for X_BData [DAFunc1, DAFunc2, DAFunc3, ..., DAFunc i , …], where DAFunc i It is the data analysis function ID; the platform account ID "UserA" has both the roles of data rights holder and data consumer, and owns data rights. The corresponding data rights IDs are "DEity_A1" and "DEity_A2", the platform account ID "UserB" has the role of data consumer, and the platform account ID "UserC" has the role of data rights holder and owns data rights. The corresponding data rights IDs are "DEity_C1", "DEity_C2" and "DEity_C3", the corresponding big data are BDD_Ins1, BDD_Ins2, BDD_Ins3, and the corresponding big data description ontology is BDD_Onto1, BDD_Onto2, BDD_Onto3; the data rights income chains of UserA and UserC accounts are DEity_Chain_A and DEity_Chain_C respectively, and the corresponding chain heads are chHead_A1 and chHead_C1 respectively.

[0104] In step S1001, the consumption request submitted by UserB is to use DAFunc2. The system generates a data requirement description item DEityPurcReqD_Instance according to DAFunc2, where:

[0105] DEityPurcReqD_Instance=<DAppReqD_Instance> ,

[0106] DAppReqD_Instance = <, comparison index, description of comparison method, DAFunc2, expected completion time of analysis function, demander's pre-quotation, demand initiator's account ID, contact number, email address, demand initiator's digital signature, platform digital signature>;

[0107] In step S1002, the system checks the access rights of UserB to BDD_Instance according to DAppReqD_Instance, and generates the consumption item data rights composition table ConsmDEityDetal.

[0108] ConsmDEityDetal = <data component list, platform digital signature>,

[0109] List of data components: = [BData_A1, BData_C2, BData_C3],

[0110] BData_A1 = <BDD_Ins1, X1, UserA, DEity_A1>,

[0111] BData_C2 = <BDD_Ins2, X2, UserC, DEity_C1>,

[0112] BData_C3 = <BDD_Ins3, X3, UserC, DEity_C3>,

[0113] <Set of consumption item data right IDs> = {DEity_A1, DEity_C1, DEity_C3},

[0114] Among them, X1, X2, and X3 are the percentage ratios of the data BDD_Ins1, BDD_Ins2, and BDD_Ins3 in the total amount of data BDD_Instance in the list of data components, respectively.

[0115] In step S1003, the system checks the data rights owned by UserB and finds that UserB does not have any of the data rights in the set of consumption item data right IDs involved in the analysis function DAFunc2. Therefore, according to the data charging method, the fee that UserB should pay for using the analysis function DAFunc2 this time is:

[0116] DPayment UserB = φ(BDD_Instance) * |BDD_Instance| * Uni_price + λ(DAFunc2),

[0117] Among them, BDD_Instance is all the data involved in UserB's use of the analysis function DAFunc2 this time,

[0118] The system generates a user consumption order UConsmOrder based on this and pushes it to UserB,

[0119] UConsmOrder = <DAFunc2, function description, ConsmDEityDetal, UserB, DPayment UserB , UserB_Order_ID, UserB's order time, UserB's digital signature, platform digital signature>;

[0120] In step S1004, after UserB completes the payment, the system calculates the payable income of the data rights DEity_A1, DEity_C2, and DEity_C3 involved in UserB's payment, which are DEity_Prft deit_A1 ,DEity_Prft deit_C2 ,DEity_Prft deit_C3 :

[0121] DEity_Prft deit_A1 =(1-ρ)*(DPayment UserB -λ(DAFunc2))*X1

[0122] DEity_Prft deit_C2 =(1-ρ)*(DPayment UserC -λ(DAFunc2))*X2

[0123] DEity_Prft deit_C2 =(1-ρ)*(DPayment UserC -λ(DAFunc2))*X3

[0124] In step S1005, the system distributes the data rights and interests income according to the data rights and interests income billing result and generates a data rights and interests income description item:

[0125] DEity_PrftDtl deit_A1

[0126] = <UserB,UserB_Order_ID,BDD_Onto1,X1,DPayment UserB ,0,DEity_A1,UserA,DEity_Prft deit_A1 ,UserB order time,UserB digital signature,Platform digital signature>,

[0127] DEity_PrftDtl deit_C2

[0128] = <UserB,UserB_Order_ID,BDD_Onto2,X2,DPayment UserB ,0,DEity_C2,UserC,DEity_Prft deit_C2 ,UserB order time,UserB digital signature,Platform digital signature>,

[0129] DEity_PrftDtl deit_C2

[0130] = <UserB,UserB_Order_ID,BDD_Onto3,X3,DPayment UserB ,0,DEity_C3,UserC,DEity_Prft deit_C3 ,UserB order time,UserB digital signature,Platform digital signature>,

[0131] The system then adds the earnings to UserA's earnings balance, and adds the earnings sum to UserC's earnings balance;

[0132] In step S1006, for step S1005, DEity_PrftDtl deit_A1 , and two DEity_PrftDtl deit_C2 , generate three blocks respectively, and update the chain heads of DEity_Chain_A and DEity_Chain_C to chHead_A and chHead_C respectively:

[0133] chHead_A=δ(DEity_PrftDtl deit_A1 ,seed,chHead_A1),

[0134] chHead_C=δ(DEity_PrftDtl deit_C2 ,seed,chHead_C2),

[0135] chHead_C2=δ(DEity_PrftDtl deit_C2 ,seed,chHead_C1).

[0136] The technical contents and technical features of the present invention have been disclosed as above. However, those skilled in the art may still make various substitutions and modifications based on the teachings and disclosures of the present invention without departing from the spirit of the present invention. Therefore, the protection scope of the present invention should not be limited to the contents disclosed in the embodiments, but should include various substitutions and modifications that do not depart from the present invention and are covered by the claims of this patent application.

Claims

1. A transaction-based big data rights sharing method, characterized in that: include: S1 is oriented to data consumption needs and calculates the cost of data usage; S2 distributes data equity benefits; S3 establishes an unalterable and anti-repudiation mechanism for all consumption and revenue records on the platform, including: S3-1 The platform and its users all hold asymmetric encryption certificates, which are used to sign their operation records on the platform; S3-2 All data consumption and data equity income records on the platform belong to their respective platform account IDs and are based on SHA256-like hash functions. As a hash algorithm, each record is organized into two chains in chronological order. The head of the chain is a string chHead with a length of 256, which is the root hash value of the latest data equity income chain. The end of the chain is an initial genesis string. The chain is composed of blocks connected head to tail. Each block of S3-3 has only one record. The block structure is DEity_Blk, which includes the block header chHead and the block tail chTail, and is charged by the data volume level billing coefficient function. Create, including at least: ， Among them, DConsmD_Onto is the data consumption record, DEityPrft_Onto is the data equity income log, seed is a random number generation function, Tail is the block header of the previous block, and the head and tail are connected to form a chain; S3-4 Generate corresponding blockchains for each user account’s user consumption order log, data rights, data rights income log, and system core data; S3-5 Each user account saves the data rights and interests chain of itself and another account, and the system saves the blockchain of all data. The data of each user account has at least three redundant backups in the system, and the total number of backups of the data of each user account in the system is odd; S3-6 The system provides a blockchain accounting function, and each user uses the accounting function to verify and record the data received from other accounts; All functions provided by the S3-7 system cannot be changed by user accounts.

2. The method according to claim 1, characterized in that The data consumption demand is described by a data demand description item DReqD_Onto, and the calculation of the data usage cost includes at least the following steps: S1-1: Taking data rights DEityD_Onto as the unit, construct the consumption item data rights composition table ConsmDEityDetal, and then generate the data requirement description item DReqD_Onto according to the requirement description ontology; S1-2: Calculate the data usage cost DPayment based on the data requirement description item user_id ; DPayment user_id := , Among them, DPayment user_id The fees that the platform account user_id should pay to the platform, including the price of the data used and the price of the data analysis function used; is the charging coefficient function at the data volume level, and the input is the data component , the output is Price fluctuation coefficient corresponding to the amount of data; | |Indicates data components The number of data records in the smallest atomic unit; Use a price calculation function for a single piece of data to output the price required to repeatedly browse a single piece of data record of the smallest atomic unit within a fixed period; Data rights ID; It is the price function of a single data analysis and result presentation function. The input is the function ID and the output is the price of the function. func_id is the ID of the data analysis function currently in use.

3. The method according to claim 1, characterized in that The distribution of data equity benefits includes at least the following steps: S2-1: The system generates a data consumption record DConsmD_Onto based on the user’s payment; S2-2: For a single data right, calculate the data right benefit Prf and generate the data right benefit log DEityPrft_Onto; S2-3: Based on S2-2, the system updates the newly added data equity income Pft to the income balance of the platform account ID to which each data equity ID involved belongs; , Among them, user_id is the user's account ID, Pft is the current income of the account ID to which the data equity ID belongs, and dataM_Per is the proportion of data volume corresponding to the data equity ID. It is the price function of a single data analysis and result presentation function. The input is the function ID and the output is the price of the function. func_id is the ID of the data analysis function currently used. DPayment user_id The fees that the platform account user_id should pay to the platform.

4. The method according to claim 1, wherein each user uses an accounting function to verify and account the data received from other accounts, comprising at least: T8-1: User A receives block data U_BDataList from other accounts sent by the system; T8-2: User A verifies the correctness of the digital signature in U_BDataList. If it is correct, it jumps to the next step. Otherwise, it sends an Error_Ini_BData message to the system. T8-3: User A parses the blockData to be recorded from U_BDataList i , write it to the local blockchain bChainName according to S3-3 i In the process, based on the new blockchain, the local Merkle tree is updated to obtain the root node of the updated Merkle tree; T8-4: User A compares root with the Merkle Tree root node merkletr_root in U_BDataList i Are they equal? ​​If they are equal, the process ends. If they are not equal, ErrChck_BData information is sent to the system. T8-5: The system parses the received ErrChck_BData to get the corresponding blockchain account user_id, packages all the latest blockchains and corresponding Merkle Tree data under the user_id account in the system, and sends them to the sender in ErrChck_BData. ecb ; T8-6: The system parses the received Error_Ini_BData to obtain U_BDataList, and reconstructs U_BDataList for all block tuples in U_BDataList to obtain new block data new_U_BDataList. If new_U_BDataList is different from U_BDataList, new_U_BDataList is sent to the sender of Error_Ini_BData. Otherwise, the corresponding blockchain account user_id is parsed from U_BDataList, and all the latest blockchains and corresponding Merkle Tree data under the user_id account in the system are packaged and sent to the sender of Error_Ini_BData. eib ; T8-7: sender ecb or sender eib Unpack the packaged data received from the system, take out the blockchain and Merkle Tree data, replace your own blockchain and Merkle Tree data, and complete the update.

5. A transaction-based big data rights sharing system, characterized in that: At least: The data usage cost calculation unit DUC_CM is used to complete the data consumption requirements and calculate the data usage cost; Data equity income distribution unit DEP_DM, used to distribute data equity income; The data record blockchain generation unit DBC_GM is used to establish an unalterable and non-repudiation mechanism for all consumption and income records in the platform; Wherein, the data record blockchain generation unit DBC_GM at least includes a key certificate generation module Crypto_GM, a block generation module B_GM, a blockchain Merkle Tree maintenance module BNMerkleTr_MM, and a blockchain accounting module BA_GM; Crypto_GM is responsible for creating a unique key pair PKI for the entire network based on the basic information submitted by the user. The block generation module B_GM creates the initial genesis block based on the initial genesis string, and generates corresponding blockchains for user consumption order logs, data rights, data rights income logs, and system core data based on the block structure DEity_Blk. , , in, , seed is a random number generation function, DConsmD_Onto is the data consumption record, DEityPrft_Onto is the data equity income log, is the billing coefficient function at the data volume level, and Tail is the block header of the previous block; The chain points to the next block by storing the next block header chHead in the block tail chTail; BNMerkleTr_MM generates a traditional Merkle tree for each blockchain based on the Merkle Tree algorithm, with the root node serving as the basis for tamper-proofing. BA_GM is used to maintain the blockchain data of the system on different user ends.

6. The system according to claim 5, characterized in that The data usage cost calculation unit at least includes a data composition analysis module DCA_CM, a data consumption demand generation module DCR_GM and a data usage cost calculation module DUP_CM; The DCA_CM generates a consumption item data rights composition table ConsmDEityDetal based on the consumption request submitted by the user and in units of data rights; The DCR_GM generates a data requirement description item having the same structure as the data requirement description item DReqD_Onto according to the consumption request and ConsmDEityDetal submitted by the user; The DUP_CM is based on the data requirement description item and the following function, according to the following about DPayment user_id The formula is used to calculate the price that user user_id should pay for this data consumption: DPayment user_id := ; Among them, DPayment user_id The fees that the platform account user_id should pay to the platform, including the price of the data used and the price of the data analysis functions used; is the charging coefficient function at the data volume level, and the input is the data component , the output is Price fluctuation coefficient corresponding to the amount of data; | |Indicates data components The number of data records in the smallest atomic unit; Use a price calculation function for a single piece of data to output the price required to repeatedly browse a single piece of data record of the smallest atomic unit within a fixed period; Data rights ID; It is the price function of a single data analysis and result presentation function. The input is the function ID and the output is the price of the function. func_id is the ID of the data analysis function currently in use.

7. The system according to claim 5, characterized in that The data rights and interests benefit distribution unit at least includes a data consumption log generation module DCL_GM, a data rights and interests benefit calculation module DEP_CM, a data rights and interests benefit log generation module DEPL_GM and a data rights and interests update module DEU_GM; The DCL_GM generates a data consumption record DConsmD_Onto; The DEP_CM extracts relevant values ​​based on the data consumption records generated by DCL_GM and calculates the data equity income according to the following function: ； Among them, Pft is the current income of the account ID to which the data equity ID belongs, DPayment user_id is the fee that the platform account user_id should pay to the platform, λ is the price function of a single data analysis and result presentation function, the input is the function ID, and the output is the price of the function; func_id is the data analysis function ID currently used, and dataM_ Per is the data volume percentage corresponding to the data equity ID; DEPL_GM generates a data equity income log with structure like DEityPrft_Onto based on DConsmD_Onto and Pft; DEU_GM finds the user_id to which the data equity ID belongs based on the data equity income log DEityPrft_Onto, and updates Pft to the income balance of user_id.

8. The system according to claim 5, characterized in that The blockchain accounting module BA_GM at least includes: a verification module Ck_CM and an error handling module ErrDeal_CM; Ck_CM is responsible for verifying the data received from other accounts. If the received data does not match the verification result, the data will be discarded and reported to the system. Otherwise, the received data will be entered into the blockchain of the corresponding account. ErrDeal_CM is responsible for reviewing the data that failed the verification and sending the reviewed data.

Images