WO2020250705A1 - Data price calculation device and data price calculation method - Google Patents

Abstract

Provided is a data price calculation device 100 for calculating a compensation to be provided to a prescribed provider by an acquirer acquiring from the provider a right pertaining to prescribed transaction data, said data price calculation device executing: a nonpublic transaction data estimation process for estimating the content of transaction data the content of which has not been acquired by the acquirer, on the basis of public data; a nonpublic transaction data importance calculation process for calculating the importance of the content of the transaction data, on the basis of the estimated content of the transaction data; and a nonpublic transaction data pricing process for calculating a compensation to be provided to the provider, on the basis of the calculated importance.

Description

Data price calculation device and data price calculation method

The present invention relates to a data price calculation device and a data price calculation method.

=== Import by reference ===
This application claims the priority of Japanese Patent Application No. 2019-107728 filed on June 10, 2019 and incorporates it into this application by reference to its contents.
In the trading of commodities, it is extremely important to properly set the price or consideration of the commodities. Regarding the technology related to product pricing, Patent Document 1 describes product information including the selling price of the product, store card information including information on the return rate of the point card of the store, and information on the return rate of the card used at the time of payment. Based on the payment card information including, the earned points obtained by purchasing the product are calculated, the cash converted value obtained by converting the earned points into the cash value is calculated, and the actual value obtained by subtracting the cash converted value from the selling price is calculated. It is stated that the selling price is calculated.

Japanese Unexamined Patent Publication No. 2014-1995777

Patent Document 1 describes the points obtained when purchasing a product and the mechanism for calculating the real price of the product including the points. In this way, by providing the user with the points calculated according to the transaction content, it is possible to bring benefits to the user. Such a mechanism is generally used by a business operator such as a store or a point service to obtain a license for transaction data from a user. However, there are the following problems from the viewpoint that the product to be traded is data and the points are for obtaining a license for the transaction data.

First, for businesses licensed for data, the calculation of points should be determined from the perspective of the value of the transaction data, that is, from the analysis of the transaction data (for example, analysis of big data). .. In this respect, the commodity price on which Patent Document 1 is calculated does not satisfy such a requirement because it is basically irrelevant to the value of transaction data.

Secondly, points for transaction data cannot generally be calculated without knowing the contents of the transaction data in advance. In other words, a third party (data purchaser, etc.) who does not know the details of the transaction does not know how much points should be paid for the data until the transaction data is received. , I can't buy the data according to my budget. In addition, even when the holder of the transaction data sells the data, the content of the transaction data (the price of the product in Patent Document 1) can be estimated from the amount of points presented, and the data before the data is provided. There is a problem from the viewpoint of confidentiality.

Thirdly, the decision to provide transaction data will be made by the data holder and for each transaction. When analyzing transaction data as big data, etc., it is convenient for the purchaser of transaction data to purchase data that matches the purpose of analysis, budget, etc. in a lump sum at the timing of the analysis. Such things cannot be realized.

The present invention has been made in view of such a problem, and an object of the present invention is a data price capable of conducting a transaction based on the values of the acquirer of the transaction data while maintaining the confidentiality of the provider of the transaction data. The purpose of the present invention is to provide a calculation device and a data price calculation method.

One of the present inventions for solving the above problems is a data price calculation method for calculating the consideration provided to the provider by the acquirer who acquires the authority regarding the predetermined transaction data from the predetermined provider. Therefore, a data price calculation device having a processor and a memory infers at least the contents of transaction data whose contents have not been acquired by the acquirer, based on public data which is data at least the acquirer can acquire the contents. The private transaction data estimation process to be performed, the private transaction data importance calculation process for calculating the importance of the content of the transaction data based on the content of the estimated transaction data, and the provision based on the calculated importance. The private transaction data pricing process for calculating the consideration to be provided to the person is executed.

According to the present invention, it is possible to perform a transaction based on the values of the acquirer of the transaction data while maintaining the confidentiality of the provider of the transaction data.
Issues, configurations and effects other than those described above will be clarified by the description of the following embodiments.

FIG. 1 is a diagram illustrating an outline of a configuration of a data price calculation system according to the present embodiment. FIG. 2 is a diagram illustrating an example of a function provided in the data price calculation device. FIG. 3 is a diagram illustrating an example of private transaction data. FIG. 4 is a diagram illustrating an example of published transaction data. FIG. 5 is a diagram illustrating an example of a corporate group. FIG. 6 is a diagram illustrating an example of the point balance. FIG. 7 is a diagram illustrating an example of sales rules. FIG. 8 is a diagram illustrating an example of in-house owned transaction data. FIG. 9 is a diagram illustrating an example of transaction data purchase conditions. FIG. 10 is a diagram illustrating an example of hardware included in the data price calculation device. FIG. 11 is a flowchart illustrating an example of the private transaction data price calculation process. FIG. 12 is a diagram illustrating an example of a method of designating private transaction data. FIG. 13 is a diagram illustrating an example of a method of estimating the transaction amount of the private transaction data. FIG. 14 is a diagram illustrating an example of a method of re-estimating the content of the private transaction data. FIG. 15 is a diagram showing an example of private transaction data for which the price of private transaction data has been calculated. FIG. 16 is a diagram showing an example of blockchain data in which the calculation result of the trading amount of the selected data is stored in the form of blockchain data. FIG. 17 is a diagram showing an example of an estimated amount transition display screen. FIG. 18 is a flowchart illustrating an example of private transaction data transaction processing. FIG. 19 is a diagram illustrating an example of conversion from in-house owned transaction data to private transaction data. FIG. 20 is a diagram illustrating an example of a transaction data purchase candidate list. FIG. 21 is a diagram illustrating an example of a transaction data purchase plan. FIG. 22 is a diagram illustrating an example of a data trading request.

Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings.

FIG. 1 is a diagram for explaining the outline of the configuration of the data price calculation system according to the present embodiment. The data price calculation system 1 is managed by at least one seller terminal 200 managed by each seller who collectively sells a plurality of transaction data of the same type, and each purchaser who purchases transaction data from the seller. It is configured to include at least one purchaser terminal 300 and a data price calculation device 100 that mediates the sale and purchase of transaction data between the seller and the purchaser. The data price calculation device 100 is provided, for example, in an information bank that mediates the transaction of information between a seller and a purchaser.

The data price calculation device 100 is a consideration provided to the seller by the purchaser who acquires the authority (use and disposal authority) regarding the predetermined transaction data (in this embodiment, the private transaction data described later) from the seller. Calculate (points). Specifically, the data price calculation device 100 includes an intermediary module 110 that performs transaction intermediation processing, a data seller module 120 that performs processing related to sales by the seller, and a data purchaser that performs processing related to purchase by the purchaser. Each module of the target module 130 is provided. A wired or wireless communication network 3 such as a LAN (Local Area Network), a WAN (Wide Area Network), the Internet, or a dedicated line is used between the data price calculation device 100, the seller terminal 200, and the purchaser terminal 300. It is connected so that it can communicate.

The data seller module 120 and the data purchaser module 130 are provided with storage areas 4 and 5 set for each seller (seller terminal 200) and each purchaser (purchaser terminal 300), respectively. .. Further, the intermediary module 110 is called from the data seller module 120 (or the seller terminal 200) and the data purchaser module 130 (or the purchaser terminal 300), and the intermediary module 110 responds to these calls. , It is possible to impose restrictions such as access restrictions for each seller or each purchaser.

Next, the details of the function of the data price calculation device 100 will be described.
<Intermediary module>
FIG. 2 is a diagram illustrating an example of a function included in the data price calculation device 100. First, the intermediary module 110 includes a private transaction data estimation processing unit 111, a private transaction data importance calculation processing unit 112, and a private transaction data pricing processing unit 113 as data processing functions.

The private transaction data guessing processing unit 111 at least obtains the contents of transaction data (private transaction data) whose contents have not been acquired by the acquirer, based on the public data which is the data whose contents can be acquired by the acquirer. Infer.

Specifically, the private transaction data estimation processing unit 111 calculates the range of evaluation values of a plurality of public data. The private transaction data estimation processing unit 111 calculates a range of evaluation values of public data (first distribution) and a range of evaluation values of other public data calculated based on the range of evaluation values of the public data (first distribution). 2 Identify the difference from the distribution).

The private transaction data importance calculation processing unit 112 calculates the importance of the content of the transaction data based on the content of the transaction data estimated by the private transaction data estimation processing unit 111.

Specifically, the private transaction data importance calculation processing unit 112 calculates the importance of transaction data based on the range of evaluation values calculated by the private transaction data estimation processing unit 111. The private transaction data importance calculation processing unit 112 calculates the importance of transaction data based on the difference in the range specified by the private transaction data estimation processing unit 111 (accuracy indirect influence degree).

Furthermore, the private transaction data importance calculation processing unit 112 calculates the importance of transaction data based on the parameters representing the demand for transaction data (needs actual results). Specifically, the private transaction data importance calculation processing unit 112 calculates the importance of transaction data based on the number of times a predetermined provision request for transaction data, which is a parameter thereof, is received. Alternatively, the private transaction data importance calculation processing unit 112 calculates the importance of the transaction data based on the number of times the content of the transaction data, which is the parameter, is estimated.

The private transaction data pricing processing unit 113 provides to the provider based on the importance (accuracy direct impact, accuracy indirect impact, and actual needs) calculated by the private transaction data importance calculation processing unit 112. Calculate the consideration (points) to be paid.

The private transaction data pricing processing unit 113 is shared with another data price calculation device 100 that stores the consideration calculated by the private transaction data importance calculation processing unit 112 or the calculation history of the calculated importance. Generate blockchain data.

Further, the private transaction data pricing processing unit 113 displays information indicating a range of evaluation values of a plurality of public data calculated by the private transaction data estimation processing unit 111 according to the calculation order of the public data.

The data price calculation device 100 stores, as data, private transaction data 114 that stores private transaction data, public transaction data 115 that stores public data, and a company group to which the seller or purchaser of transaction data belongs. Group 116, private transaction data sales condition 117 that stores the sales conditions of private transaction data, data purchase request 118 that stores transaction requests from the purchaser of transaction data to the seller, and purchase by transactions related to transaction data The point balance 119, which stores the balance of consideration (points) provided by the person to the seller for each entity, is stored.

<Private transaction data>
FIG. 3 is a diagram illustrating an example of private transaction data 114. The private transaction data 114 is a database relating to a plurality of transaction data (private transaction data) whose contents have not been acquired by at least the purchaser. That is, the private transaction data is transaction data that the purchaser cannot access even through the purchaser terminal 300 or the like.
Specifically, the private transaction data 114 uses the table column identifier 350 as the ID 301 of the private transaction data, the holder 302 of the private transaction data related to ID 301, and the buyer 303 in the transaction related to the private transaction data related to ID 301. , Supplier 304 in the transaction related to the private transaction data related to ID 301, Price update request flag 305, which sets a predetermined value when there is a request to calculate the price for the private transaction data related to ID 301, Price update request flag 305 is the set number of requests 306, the latest calculation date 307, which is the date when the price of the private transaction data related to ID 301 was last calculated, and the estimated amount of the transaction amount of the private transaction data related to ID 301. Estimated transaction amount 308, accuracy of private transaction data related to ID301 Direct impact 309, accuracy of private transaction data related to ID301 Indirect impact 310, needs record of private transaction data related to ID301 311 and ID301 It has each element of data price 312, which is the value (compensation or points) of private transaction data. The private transaction data 114 holds a plurality of records 320 having each of these elements. In the example of the figure, the private transaction data 114 is non-public data including a plurality of transaction data including "A003", "A004", "A005", "B012", "B014" and the like. The private transaction data 114 is obtained, for example, from an external predetermined ordering system.

The accuracy direct influence is the estimated transaction amount of the record of the private transaction data 114 when the estimated transaction amount of the record of the private transaction data 114 is obtained from the record of the public transaction data 115 described later. It is an importance parameter that numerically expresses how much the accuracy of the estimation of is improved.

In addition, the accuracy indirect influence is the accuracy of the estimated transaction amount of the record of the private transaction data 114 other than that record of the private transaction data 114 when the estimated transaction amount of the record of a certain private transaction data 114 is calculated. It is an importance parameter that numerically expresses how much sex affects the calculation of the estimated transaction amount.

In addition, the actual needs is an importance parameter that numerically expresses the amount of demand for certain private transaction data.

In the record 320 of the private transaction data 114, each element of the ID 301, the holder 302, the buyer 303, and the supplier 304 is set by the module 120 for the data seller. In addition, among the records 320, each of the price update request flag 305, the number of requests generated 306, the latest calculation date 307, the estimated transaction amount 308, the accuracy direct impact degree 309, the accuracy indirect impact degree 310, the needs record 311 and the data price 312. The elements are set by the private transaction data price calculation process described later.

<Published transaction data>
FIG. 4 is a diagram illustrating an example of published transaction data 115. The published transaction data 115 is a database of public data whose contents have been acquired by at least the purchaser, and is composed of a set of a plurality of data. Specifically, the published transaction data 115 has, as the table column identifier 500, the buyer 502, which is the buyer in the data transaction related to the public data ID 501 and ID 501, and the supplier 503, ID 501, which is the seller in the data transaction related to ID 501. It has each element of the transaction amount 504, which is the amount of money related to the data transaction related to ID 501, and the disclosure destination 505 of the content of the data transaction related to ID 501. The private transaction data 114 holds a plurality of records 520 having each of these elements. In the example of the figure, the published transaction data 115 includes a plurality of data including "A001", "A002", "A006", "B013", "B016" and the like. The data seller module 120 sets each information of the table column identifier 500.

As described above, in the present embodiment, the published transaction data 115 is a set of data in which the transaction amount 504 is published. The published transaction data 115 is based on, for example, publicly available information on a predetermined network, for example, public information of each company on the Internet. The public data may be data used for the transaction of the private transaction data of the present embodiment or data not used for such a transaction.

<Corporate group>
FIG. 5 is a diagram illustrating an example of the corporate group 116. The company group 116 uses the table column identifier 1100 as the company name 1101, which is the name of the company (specifically, the seller or the purchaser) that constitutes the company group according to the group 1103, the industry 1102 of the company according to the company name 1101, and , Has each element of group 1103, which is a corporate group. The corporate group 116 is a database that holds a plurality of records 1120 having each of these elements.

<Point balance>
FIG. 6 is a diagram illustrating an example of the point balance 119. The point balance 119 has a company name 1801 in which the name of the entity (specifically, the seller) related to the transaction data is set as the table column identifier 1800, and a point balance 1802 owned by the entity related to the company name 1801. The point balance 119 is a database that holds a plurality of records 1820 having each of these elements.

<Module for data sellers>
The data seller module 120 shown in FIG. 2 includes a provision rule setting unit 121, a sellable transaction data sharing processing unit 122, and a data transaction processing unit 123 as data processing functions.

Of these, the provision rule setting unit 121 sets the data provision condition (sales rule 124), which is the provision condition of the authority regarding transaction data.

The sellable transaction data sharing processing unit 122 performs processing for sharing transaction data between legal entities.

The data transaction processing unit 123 determines whether or not the acquisition of the authority regarding the transaction data by the acquirer satisfies the data provision condition (sales rule 124), and if it is determined that the data provision condition is satisfied, the acquisition thereof. A process of causing a person to acquire authority regarding transaction data (in this embodiment, a process of executing a sale) is executed.

Further, the data price calculation device 100 stores the sales rule 124 and the in-house owned transaction data 125 regarding the transaction data held by the seller as data.
<Sales rules>
FIG. 7 is a diagram illustrating an example of the sales rule 124. The sales rule 124 uses the table column identifier 1000 as the table column identifier 1000 for the provider 1001 which is a corporate group capable of providing transaction data, and the provider 1001 of the same type of transaction data group specified by the private transaction data 114. It has a maximum provision ratio of 1002, which is the ratio of transaction data that can be provided. Sales rule 124 holds one record having each of these elements. In the example of the figure, the value of "Group 1" is set as the available destination 1001, and the value of "50%" is set as the maximum provision ratio 1002. It should be noted that the service destination 1001 of the sales rule 124 and the group 1103 of the corporate group 116 correspond to each other. For example, if the provision destination 1001 of the sales rule 124 is "Group 1" and the group 1103 of the corporate group 116 is "Group 1", the contents of the company name 1101 of the corporate group 116, that is, "Company A" and "Company A""CompanyB" and "Company C" are companies that can sell transaction data. In addition, the number of sellable transaction data (number of sellable cases) in the same type of transaction data group can be calculated from the maximum provision ratio 1002.

<Own transaction data>
FIG. 8 is a diagram illustrating an example of in-house owned transaction data 125. The in-house owned transaction data 125 is used as a table column identifier 1200 in the transaction data ID1201, the buyer 1202 in the transaction data transaction related to ID1201, the supplier 1203 in the transaction data transaction related to ID1201, and the transaction data transaction related to ID1201. It has each element of transaction amount 1204. The self-owned transaction data 125 is a database that holds at least one or more records 1220 having each of these elements.

<Module 130 for data purchasers>
The data purchaser module 130 shown in FIG. 2 has an acquisition condition setting unit 131 for setting transaction data purchase conditions 136, which is a condition for the purchaser to acquire transaction data, and transaction data purchase conditions 136 as data processing functions. Transaction data purchase candidate list creation unit 132 that creates transaction data purchase candidate list 137 that is a list of transaction data to be satisfied, transaction data purchase plan creation unit 133 that creates transaction data purchase plan 138 that is a transaction data purchase plan, transaction data It has a transaction data purchase request registration unit 134 that creates a transaction data purchase request based on the purchase candidate list 137 and a transaction data purchase plan 138, and a transaction data acquisition processing unit 135 that processes transaction data transactions based on the purchase request. doing.

For example, the acquisition condition setting unit 131 sets data acquisition conditions (transaction data purchase conditions 136, which will be described later), which are transaction data acquisition conditions.

The transaction data purchase candidate list creation unit 132 identifies the private transaction data that satisfies the data acquisition conditions, and outputs a part of the specified private transaction data as private.

The data price calculation device 100 stores transaction data purchase conditions 136, transaction data purchase candidate list 137, and transaction data purchase plan 138 as data.

<Transaction data purchase conditions>
FIG. 9 is a diagram illustrating an example of transaction data purchase condition 136. The transaction data purchase condition 136 has each element of the industry 1401 and the company name 1402 of the person who can provide the transaction data as the table column identifier 1400, respectively. The transaction data purchase condition 136 holds one record 1410 having each of these elements. Each information of the record 1410 is set by, for example, the purchaser terminal 300 (purchaser). In the example of the figure, while the type of business of the seller of the transaction data is "food", it is specified as a purchase condition that the seller does not specifically specify.

Note that FIG. 10 is a diagram illustrating an example of hardware included in the data price calculation device 100. The data price calculation device 100 includes a processor 11 such as a CPU (Central Processing Unit), a memory 12 such as a RAM (RandomAccessMemory) and a ROM (ReadOnlyMemory), an HDD (HardDiskDrive), and an SSD (SolidStateDrive). ), Etc., a communication device 14, an input device 15 such as a keyboard, a mouse, or a touch panel, and an output device 16 such as a display and a touch panel. Each function of the data price calculation device 100 described so far is a program stored in the memory 12 or the storage device 13 by the hardware of the data price calculation device 100 or by the processor 11 of the data price calculation device 100. It is realized by reading and executing. Further, these programs are non-readable by the data price calculation device 100 such as a secondary storage device, a non-volatile semiconductor memory, a hard disk drive, a storage device such as SSD, or an IC card, SD card, DVD, etc. It is stored in a temporary data storage medium.

<< Processing >>
Subsequently, the processing performed in the data price calculation system 1 will be described. First, the intermediary module 110 of the data price calculation device 100 executes a private transaction data price calculation process of estimating (calculating) the price of the private transaction data from the public data. Then, the data price calculation device 100 executes the private transaction data transaction processing that performs the transaction processing of the transaction data based on the trading amount of the private transaction data calculated by the private transaction data price calculation process. The details of these processes will be described below.

<Private transaction data price calculation process>
FIG. 11 is a flowchart illustrating an example of the private transaction data price calculation process. The private transaction data price calculation process is started, for example, when the data price calculation device 100 is activated.

When the private transaction data price calculation process is started, the data price calculation device 100 accepts the designation of the private transaction data to be traded (step S201). Specifically, the data price calculation device 100 receives, for example, input of data corresponding to the private transaction data 114 from a seller (seller terminal 200) who desires to trade the private transaction data. After that, the data price calculation device 100 automatically executes each process (without human intervention) based on the input information.

FIG. 12 is a diagram illustrating an example of a method of designating private transaction data. As shown in the figure, when the seller specifies an arbitrary record of the private transaction data 114, the data price calculation device 100 rewrites the value of the price update request flag 305 of the designated record to "True". As a result, the private transaction data related to the record is designated as the transaction target (price calculation target). In the example of the figure, a total of two pieces of data are specified: the private transaction data of the record whose ID301 value is "A003" and the private transaction data of the record whose ID301 value is "B014". .. At this time, the data price calculation device 100 adds 1 to the current value of the request occurrence number 306 of the record in which "True" is set in the price update request flag 305, and uses it as the basis for calculating the actual needs ( If no value is set for the number of requests generated 306, 1 is set).

Next, as shown in step S202 of FIG. 11, the data price calculation device 100 selects one of the private transaction data specified in step S201. Specifically, the data price calculation device 100 selects one record (hereinafter, referred to as a selection record) of the private transaction data 114. Here, it is assumed that the record whose ID301 value is "A003" is selected, and the subsequent steps S203 to S208 will be described.

The data price calculation device 100 calculates three importance levels of the private transaction data (hereinafter referred to as selection data) selected in step S202 (step S203-step S207).

First, the data price calculation device 100 calculates the degree of direct influence on the accuracy of the selected data (step S203, step S204).

That is, first, the data price calculation device 100 estimates the transaction amount of the selected data by obtaining the probability distribution (first distribution), which is the range of the transaction amount of the public data, by a statistical method (step S203). Specifically, the private transaction data estimation processing unit 111 calculates the estimated transaction amount of the private transaction data based on the public data, and sets the distribution width of the calculated estimated transaction amount to the estimated transaction of the private transaction data 114. Write in the amount 308.

FIG. 13 is a diagram showing an example of the distribution (first distribution) of the estimated amount of private transaction data. In the private transaction data estimation processing unit 111, the information of the buyer 502 and the supplier 503 in each record 520 of the published transaction data 115 matches the buyer 303 and the supplier 304 of the private transaction data 114 related to the selected data, respectively. Extract records. In this example, from the records of the published transaction data 115, a total of two records having ID 501 of "A001" and "A002" are extracted. Then, the private transaction data estimation processing unit 111 calculates a population average using the value of the transaction amount 504 of the extracted record as a sample, and further sets a distribution width twice the standard deviation from the population average. , Calculate the distribution width of the estimated transaction amount. In this example, under the constraint that the estimated transaction amount does not become negative, the private transaction data estimation processing unit 111 sets the estimated transaction amount 308 of the selected record in the range of "0 yen to the maximum value". Write the information "338 yen".

After that, as shown in step S204 of FIG. 11, the data price calculation device 100 calculates the accuracy direct influence of the selected data based on the transaction amount calculated in step S203. Specifically, the private transaction data importance calculation processing unit 112 calculates the difference (range of amount) between the maximum value and the minimum value in the estimated transaction amount 308 calculated in step S203, and selects the calculated value. Record accuracy Write to direct impact 309. The method for calculating the degree of direct influence on accuracy is not limited to this method, and the distribution width may be a value obtained by subjecting a predetermined mathematical expression process.

Second, the data price calculation device 100 calculates the accuracy indirect influence degree 310 of the selected data (step S205, step S206).

That is, first, the data price calculation device 100 estimates the transaction amount of the selected data by obtaining the probability distribution (distribution of the sample data) which is the range of the transaction amount of the public data, as in step S203 (step S205). ). If the estimation result of the transaction amount has already been written in the private transaction data 114 in step S203, the writing process may not be performed here.

Further, the data price calculation device 100 separately estimates the transaction amount of the selected data by fixing the calculated transaction amount to a predetermined value (step S205). Specifically, for example, first, it is assumed that the transaction amount of the private transaction data related to the selected record is the average value of the distribution of the transaction amount estimated in step S205. The private transaction data importance calculation processing unit 112 adds this average value to the sample data (transaction amount data group of public data), and performs the same statistical processing as in step S204 based on the sample data to select a selection record. Calculate the distribution (second distribution) of the estimated amount of private transaction data of the same type of transaction (transaction with the same seller and purchaser) as the transaction related to. Then, the data price calculation device 100 calculates the difference between the first distribution and the second distribution.

Then, the data price calculation device 100 calculates the accuracy indirect influence of the selected data based on the difference in the distribution of the transaction amount calculated in step S205 (step S206). Specifically, the data price calculation device 100 counts the number of private transaction data of the same type of transaction as the transaction related to the selected data (transaction in which the seller and the purchaser are the same). Then, the data price calculation device 100 multiplies the number of the private transaction data by the decrease in the estimated width of the transaction amount calculated in step S205.

FIG. 14 is a diagram showing an example of the distribution (second distribution) of the estimated amount of private transaction data. As shown in the figure, as a result of the same calculation method as in step S205, the data price calculation device 100 obtains a range of estimated amounts of "51 yen to 158 yen". Then, in this example, the data price calculation device 100 can extract the records whose ID 301 is "A004" and "A005", in which the buyer 303 and the supplier 304 of the private transaction data 114 are the same records as the selected records. Get the result. The data price calculation device 100 writes "462", which is obtained by multiplying the result (2 cases) by the above-mentioned decrease "231", in the accuracy indirect influence degree 310 of the selected record. That is, as a result of the estimated range of the transaction amount of the private transaction data being changed from the above-mentioned 338 yen (0 yen to 338 yen) to 107 yen ("51 yen to 158 yen"), it is reduced by "231 yen". ing.

Thirdly, as shown in step S207 of FIG. 11, the data price calculation device 100 calculates the actual needs of the selected data. Specifically, the private transaction data importance calculation processing unit 112 sets the value of the request occurrence number 306 of the selected record of the private transaction data 114 to the needs record 311 of the record.

The data price calculation device 100 estimates the transaction amount of the selected data (private transaction data) by a predetermined calculation formula using these three importance levels (accuracy direct influence degree, accuracy indirect influence degree, and actual needs) as input variables. (Step S208). Specifically, the private transaction data pricing processing unit 113 calculates the transaction amount of the selected record by a predetermined calculation formula, and uses the calculated amount as points (compensation for the transaction) as the data of the private transaction data 114. Set the price to 312. Further, the private transaction data pricing processing unit 113 clears the price update request flag 305 of the private transaction data 114, and sets the latest calculation date 307 to the date of the calculation day (for example, the current date).

FIG. 15 is a diagram showing an example of private transaction data 114 in which the calculated points are set. In the figure, the sum of the value of the accuracy direct influence degree 309 of the private transaction data 114 and the value of the accuracy indirect influence degree 310 is multiplied by the needs actual 311 and reduced to 1/10, which is the data price 312. Is set to. The formula for calculating the transaction amount is not limited to the one described here, and may be calculated using a predetermined weight value, a function, or the like.

As shown in FIG. 16, the data price calculation device 100 may store the calculation result of the transaction amount of the selected data in the form of blockchain data and share it with another data price calculation device 100. The blockchain data 1141 shown in the figure has a hash value 313 and a nonce 315 of the blockchain data generated in the previous transaction, and further, the accuracy direct influence degree 309 and the accuracy indirect related to each transaction. Includes a history of impact 310, needs record 311 and data price 312. As a result, the estimated value of the transaction data and the processing (result) of the calculation of the data price can be expected to be left as a trail on the network and the effect of guaranteeing the validity of the transaction amount can be expected. Regarding the accuracy direct influence degree 309, the accuracy indirect influence degree 310, and the needs actual 311, at least 1 or more may be included in the blockchain data.

Next, as shown in step S209 of FIG. 11, when the transaction amount of the selected data is estimated, the data price calculation device 100 determines whether or not there is other private transaction data for which the transaction amount is estimated. If there is other private transaction data for which the transaction amount is estimated (step S209: NO), the data price calculation device 100 uses the private transaction data as new selection data and repeats the processes after step S202. On the other hand, when there is no other private transaction data for estimating the transaction amount (step S209: YES), the data price calculation device 100 ends the private transaction data price calculation process.

<Estimated amount transition display screen>
After the completion of the private transaction data price calculation process, the data price calculation device 100 displays the distribution (first distribution or second distribution) of the estimated amount of the private transaction data in response to the request from the purchaser terminal 300. The estimated amount transition display screen is displayed on the screen of the purchaser terminal 300 (step S211).

FIG. 17 is a diagram showing an example of the estimated amount transition display screen. On the estimated amount transition display screen 400, the vertical axis represents the range (maximum amount-minimum amount) of the estimated amount of private transaction data (collecting the same type of transaction data), and the horizontal axis represents the date or time when the estimated amount was calculated. This is the screen of the box plot that was set. This box plot visualizes the time variation of the estimation accuracy of the estimated transaction amount 308 of the transaction data in the private transaction data 114. Although this boxplot is not shown, it can be displayed for each type of private transaction data. The prospective purchaser of the private transaction data can confirm whether or not the estimation accuracy of the private transaction data is improved by referring to this box plot (change in the range of the estimated transaction amount 308). .. This makes it possible to determine whether to make a transaction or estimate the amount again.

<Private transaction data transaction processing>
The data price calculation device 100 executes the private transaction data transaction process after the above private transaction data price calculation process is completed. The private transaction data transaction process is started, for example, when a predetermined instruction is input from the seller terminal 200 or the purchaser terminal 300.

FIG. 18 is a flowchart illustrating an example of private transaction data transaction processing. Hereinafter, in the explanation of the figure, it is assumed that "Company A" as a data seller and "Company B" as a data purchaser participate in the sale. Further, for convenience of explanation, only the transaction amount in the transaction data can be kept private, while other information in the transaction data is basically made public.

When the private transaction data transaction process is started, the data seller module 120 of the data price calculation device 100 sets the transaction conditions on the seller side (step S901). Specifically, for example, the provision rule setting unit 121 receives information on the provision conditions input to the seller terminal 200 from the seller terminal 200 while referring to the information of the company group 116 by the company A (seller). , The received information is registered in the sales rule 124.

Then, the module 120 for the data seller makes the transaction data that the seller is trying to sell private (step S902). Specifically, the sellable transaction data sharing processing unit 122 reads the contents of the self-owned transaction data 125, converts the record related to the transaction data that the seller intends to sell into the record of the private transaction data 114, and then converts it into the record of the private transaction data 114. Write to private transaction data 114. As a result, the transaction data that Company A (seller) intends to sell is shared with Company B (purchaser) as partially private data.

FIG. 19 is a diagram illustrating an example of conversion from in-house owned transaction data 125 to private transaction data 114. As shown in the figure, the values of ID 1201, the buyer 1202, and the supplier 1203 of the self-owned transaction data 125 are set to the ID 301, the buyer 303, and the supplier 304 of the private transaction data 114, respectively. Further, by setting the seller to the holder 302 of the private transaction data 114, the record 320 of the private transaction data 114 is added or updated.

The above processes of steps S901 and S902 are repeated a predetermined number of times, for example, a number of times set by the seller terminal 200.

On the other hand, as shown in step S903 of FIG. 18, the module 130 for the data purchaser of the data price calculation device 100 sets the transaction conditions on the purchaser side. Specifically, for example, the acquisition condition setting unit 131 receives the purchase condition information input to the purchaser terminal 300 by the company B (purchaser) from the purchaser terminal 300, and receives the received information as transaction data. Register with purchase conditions 136.

Then, the module 130 for data purchasers identifies all the private transaction data that satisfy the purchase conditions of the purchaser (step S904). That is, the transaction data purchase candidate list creation unit 132 refers to the contents of the transaction data purchase condition 136, the private transaction data 114, the corporate group 116, and the private transaction data sales condition 117, and thereby, the transaction data purchase candidate list 137. To create.

Specifically, the transaction data purchase candidate list creation unit 132 specifies private transaction data that satisfies the conditions of the industry and the corporate group. That is, the transaction data purchase candidate list creation unit 132 acquires the information of the industry 1102 corresponding to the holder 302 by referring to the data of the corporate group 116 for the holder 302 of each record of the private transaction data 114. .. Then, the transaction data purchase candidate list creation unit 132 extracts a record in which the value of the acquired industry 1102 matches the industry 1401 of the record of the transaction data purchase condition 136 from the records of the private transaction data 114. Further, the transaction data purchase candidate list creation unit 132 can provide the group to which the holder 302 belongs for each record of the extracted private transaction data 114 to the contents of the company group 116 and each record of the sales rule 124. Is specified by referring to, and the group to which the specified group belongs, which is specified by the company group 116, is extracted.

Note that the transaction data purchase candidate list creation unit 132 may limit the private transaction data to be specified when the number of sales (the number of possible sales) of the private transaction data is limited by the seller. For example, when the number of records extracted from the private transaction data 114 exceeds the number of sellable records specified by the maximum provision ratio 1002 of the sales rule 124, the transaction data purchase candidate list creation unit 132 determines the number of records that can be sold. Limit the records to be extracted so that they are below. The record to be limited may be randomly selected, or may be selected by a predetermined algorithm in consideration of the selling price of transaction data and the like. In calculating the number of sellable records, the transaction data purchase candidate list creation unit 132 first determines the number of records corresponding to the holder 302 of the acquired record in the private transaction data 114 and the published transaction data 115. Calculated by referring to the data. After that, the transaction data purchase candidate list creation unit 132 calculates the number of sellable cases by multiplying the calculated number of cases by the value of the maximum provision ratio 1002 in the sales rule 124.

In addition, the transaction data purchase candidate list creation unit 132 may hinder data trading based on an appropriate price for private transaction data for which points have not been calculated yet or the date for which points were calculated is old. Therefore, the point may be calculated here. Specifically, when the data price 312 is not set in the record of the extracted private transaction data 114, or when the latest calculation date 307 of the record is before the predetermined date and time, etc., the transaction data purchase candidate list. The creation unit 132 calculates the data price 312 by executing steps S201 to S208.

<Transaction data candidate list>
The details of the transaction data purchase candidate list 137 created as described above will be described.
FIG. 20 is a diagram illustrating an example of the transaction data purchase candidate list 137. The transaction data purchase candidate list 137 uses the table column identifier 1500 as the table column identifier 1500, and is the holder 1502 which is a company holding the transaction data related to the transaction data ID 1501, ID 1501, the estimated transaction amount 1503 of the transaction data related to ID 1501, and the transaction data related to ID 1501. It has each element of accuracy direct influence degree 1504, accuracy indirect influence degree 1505 of transaction data related to ID 1501, need record 1506 of transaction data related to ID 1501, and data price 1507 which is consideration (point) of transaction data related to ID 1501. The transaction data purchase candidate list 137 is a database that holds a plurality of records 1520 having each of these elements. The transaction data purchase candidate list creation unit 132 displays the contents of the transaction data purchase candidate list 137 on the screen of the purchaser terminal 300. In the transaction data purchase candidate list 137, the transaction amount itself of the private transaction data is not disclosed, and instead, the estimated transaction amount estimated from the public data is registered. In this way, the purchaser terminal 300 is provided with information on transaction data (private transaction data) whose contents are partially private.

Next, as shown in step S905 of FIG. 18, the module 130 for the data purchaser of the data price calculation device 100 is based on the private transaction data that satisfies the purchase condition of the purchaser specified in step S904. Create a purchase pattern (purchase plan). Specifically, for example, the transaction data purchase plan creation unit 133 receives a budget input from the purchaser (purchaser terminal 300) in advance, and inputs the ID 1501 of each record and the estimated transaction amount 1503 in the transaction data purchase candidate list 137. By reference, create at least one pattern of the type and number of private transaction data for which the total purchase price falls within the budget. Then, the transaction data purchase plan creation unit 133 writes the pattern of the type and number of the created private transaction data in the transaction data purchase plan 138. The purchase pattern of the private transaction data is not limited to the one mentioned here, and may be based on another predetermined algorithm, may be randomly set, or may be a purchaser ( It may be the one input by the purchaser terminal 300).

<Transaction data purchase plan>
FIG. 21 is a diagram illustrating an example of the transaction data purchase plan 138. The transaction data purchase plan 138 uses the table column identifier 1600 as the plan ID 1601 of the purchase plan (purchase pattern), the estimated transaction amount maximum and minimum 1602 which is the range of the estimated transaction amount in the purchase plan related to the plan ID 1601, and the purchase plan related to the plan ID 1601. Total accuracy direct impact 1603, which is the total value of the accuracy direct impact of all private transaction data, and total accuracy indirect impact, which is the total accuracy of all private transaction data in the purchase plan related to plan ID 1601. 1604, average needs actual 1605 which is the average value of the needs actual of all private transaction data of the purchase plan related to plan ID 1601, total data price 1606 which is the total value of all private transaction data prices in the purchase plan related to plan ID 1601. , And each element of the total number of data items 1607, which is the total number of transaction data items in the purchase plan related to the plan ID 1601. The transaction data purchase plan 138 is a database that holds a plurality of records 1620 having each of these elements.

The above processes from step S903 to step S905 are repeated a predetermined number of times (for example, a number of times specified by the user).

Next, the module 130 for the data purchaser of the data price calculation device 100 selects a plan related to the transaction data to be actually purchased from the list of purchase plans generated in step S905. For example, the data purchaser module 130 of the data price calculation device 100 accepts the selection of one of a plurality of purchase plans from the purchaser (purchaser terminal 300).

Then, the module 130 for the data purchaser of the data price calculation device 100 generates the data of the transaction request based on the selected purchase plan as shown in step S906 of FIG. That is, the transaction data purchase plan creation unit 133 generates the data trading request 118.

<Data trading request>
FIG. 22 is a diagram illustrating an example of the data trading request 118. The data trading request 118 uses the table column identifier 1700 to disclose the transaction data of the selected purchase plan (hereinafter referred to as the Transaction Data) ID 1701, the holder 1702 of the transaction data related to ID 1701, and the transaction data related to ID 1701. It has each element of the tip 1703. The data trading request 118 is database-format information that holds a plurality of records 1720 having each of these elements. The data trading request 118 is generated as follows, for example. The transaction data purchase plan creation unit 133 identifies all the records (records of the transaction data) of the transaction data purchase candidate list 137 specified by the records selected from the transaction data purchase plan 138, and ID 1501 of each identified record and The holder 1502 is set to the ID 1701 and the holder 1702 of the data trading request 118. Further, the transaction data purchase plan creation unit 133 identifies the record of the company group 116 in which the value of the set holder 1702 is set to the company name 1101, and publishes the group 1103 of the specified record to the data trading request 118. Set to 1703.

Correspondingly, as shown in step S907 of FIG. 18, the data seller module 120 is the transaction data sold by the seller (the transaction data) from the data sales request 118 generated by the data purchaser module 130. ) Information is extracted. Specifically, the data transaction processing unit 123 acquires all the records of the data trading request 118 in which the seller information (company A) is set in the holder 1702. The module 120 for data sellers may perform a process of making the transaction data specified by the transaction data purchase plan 138 consistent with the information of the transaction data to be extracted.

The module 120 for data sellers discloses the transaction data and processes the increase / decrease of points based on the information of the transaction data extracted in step S907 (step S908).

Specifically, regarding the disclosure of the Transaction Data, the Data Transaction Processing Unit 123 first reads the value of the ID 1701 of each record of the data transaction request 118 extracted in step S907, and then from the own transaction data 125. , Reads a record having the same value as the read ID1701 as ID1201. Then, the data transaction processing unit 123 sets the values of the ID 1201, the buyer 1202, the supplier 1203, and the transaction amount 1204 of the read record of the self-owned transaction data 125 to the values of the ID 501, the buyer 502, the supplier 503, and the transaction amount 504, respectively. Create a record of published transaction data 115 that you have as. Further, the data transaction processing unit 123 sets the content of the public destination 1703 of the record of the read data trading request 118 to the public destination 505 of the published transaction data 115. This completes the registration of the Transaction Data.

Regarding the increase / decrease of points, the data transaction processing unit 123 updates the point balance 119 according to the content of the data trading request 118 extracted in step S907. Specifically, the data transaction processing unit 123 extracts the record of the private transaction data 114 related to the ID corresponding to the ID 501 of the record of the published transaction data 115 for which the public destination 505 is set, and the extracted record. The record of the point balance 119 is updated based on the value (points) of the data price 312 of. For example, the data transaction processing unit 123 specifies a record with a point balance 119 in which the seller (company A) is registered in the company name 1801, and increases the value of the point balance 119 of the specified record by the calculated points. The data transaction processing unit 123 reduces the value of the point balance 119 of the record of the point balance 119 in which the purchaser (company B) is registered in the company name 1801 by the calculated points.

Finally, the module 120 for the data seller deletes the information of the transaction data on the seller side (step S908). Specifically, the data transaction processing unit 123 deletes the record of the self-owned transaction data 125 corresponding to the record of the published transaction data 115 set in the disclosure destination 505 above, and also deletes the record of the self-owned transaction data 125 in the above. The record of the private transaction data 114 corresponding to the record of the public transaction data 115 set in 505 is deleted.

The purchaser terminal 300 receives and displays only the transaction data information that can be viewed by the purchaser among the transaction data from the data purchaser module 130 (step S909). Specifically, the transaction data acquisition processing unit 135 transmits the information of each record related to the transaction data among the records of the published transaction data 115 to the purchaser terminal 300 of the company B, and the purchaser terminal of the company B. 300 displays this information. In this case, the transaction data acquisition processing unit 135 determines whether or not each of the transaction data is the transaction data disclosed to the corporate group to which the purchaser (Company B) belongs, and is not disclosed. In the case of transaction data, the information of the transaction data is not transmitted to the purchaser terminal 300. Specifically, the transaction data acquisition processing unit 135 specifies the record of the purchaser in the company group 116 by the company name 1101, and specifies the disclosure destination 505 of each record related to the transaction data of the published transaction data 115. Only when the value of the group 1103 of the record is set to the public destination 505, the information of the transaction data related to the record is transmitted to the purchaser terminal 300 of the new record.

With the above, one transaction of the private transaction data group is completed.

As described above, the data price calculation device 100 of the present embodiment receives the consideration provided to the provider by the acquirer (seller) who acquires the authority regarding the private transaction data from the provider (purchaser). When calculating, based on the public data, the content of the private transaction data for which the content has not been acquired by the acquirer is estimated, the importance of the content is calculated based on the content of the private transaction data, and the calculated importance is calculated. Based on, the consideration to be provided to the provider is calculated. As a result, (1) the provider of the private transaction data does not have to provide the contents of the private transaction data to the acquirer, so that the transaction can be performed while ensuring the confidentiality of the data. In addition, for the acquirer of the private transaction data, (2) the value of the private transaction data is calculated based on the public data (for example, the consideration can be calculated using big data), so that the transaction data is private. Even if there is, it is possible to calculate a reasonable consideration according to the content of the transaction. Further, (3) since the consideration can be calculated for each transaction data, the acquirer can collectively trade the transaction data having the same kind of contents. That is, it is possible to buy and sell transaction data based on the value judgment of the business operator who receives the license of the transaction data, and by the user, not the licensee of the transaction data.
As described above, according to the data price calculation device 100 of the present embodiment, it is possible to perform a transaction based on the values of the acquirer of the transaction data while maintaining the confidentiality of the provider of the transaction data.

Further, in the present embodiment, the data price calculation device calculates a range of evaluation values of a plurality of the public data in the private transaction data estimation process, and calculates the calculation in the private transaction data importance calculation process. The importance of the transaction data is calculated based on the range of the evaluation values.

In this way, by calculating the importance of private transaction data based on the range of evaluation values (amounts) of multiple public data, it is important because the wider the range of evaluation values, the more difficult it is to guess the content and the higher the market value. It is possible to set an appropriate importance according to the content of transaction data, such as increasing the degree.

Further, in the present embodiment, the data price calculation device is calculated based on the range of the evaluation value of the public data calculated and the range of the evaluation value of the public data in the private transaction data estimation process. The difference from the range of the evaluation value of the public data is specified, and in the private transaction data importance calculation process, the importance of the transaction data is calculated based on the difference in the specified range.

In this way, by calculating the importance of transaction data based on the difference between the range of evaluation values of public data and the range of evaluation values of other public data calculated based on the range of evaluation values of public data. It is possible to calculate the indirect effect on the evaluation value of public data. As a result, the accuracy of calculating the importance of the private transaction data can be improved.

Further, in the present embodiment, the data price calculation device calculates the importance of the transaction data based on the parameter representing the demand of the transaction data in the private transaction data importance calculation process.

This makes it possible to accurately calculate the importance of transaction data based on the market value.

Specifically, in the present embodiment, the data price calculation device is important of the transaction data based on the number of times a predetermined provision request of the transaction data, which is the parameter, is received in the private transaction data importance calculation process. Calculate the degree.

This makes it possible to accurately calculate the importance of transaction data based on the specific needs of the transaction.

Specifically, the data price calculation device calculates the importance of the transaction data based on the number of times the content of the transaction data, which is the parameter, is estimated in the private transaction data importance calculation process.

This makes it possible to reliably calculate the importance of transaction data based on processing based on the specific needs of the transaction.

Further, in the present embodiment, the data price calculation device displays information indicating a range of evaluation values of the plurality of public data calculated in the private transaction data estimation process according to the calculation order of the public data. To execute.

By displaying the range of evaluation values in the calculation order (for example, time series) in this way, users such as purchasers can grasp changes in the accuracy of the estimation data of private transaction data. Thereby, for example, the purchaser or the like can determine whether or not a new accuracy analysis is required.

Further, in the present embodiment, the data price calculation device is shared with another data price calculation device that stores the calculated consideration or the calculation history of the calculated importance in the private transaction data pricing process. Generate blockchain data.

In this way, by sharing the calculation history and process of transaction data with many users on the network, the validity of the transaction amount can be guaranteed.

Further, in the present embodiment, the data price calculation device identifies and specifies the acquisition condition setting process for setting the data acquisition condition which is the acquisition condition of the transaction data and the predetermined transaction data satisfying the data acquisition condition. Executes output processing that makes part of the contents of the transaction data private and outputs it.

As a result, the acquirer of the transaction data can acquire the authority of the data under the conditions desired by himself / herself, and the provider of the transaction data can maintain the confidentiality of the data.

Further, in the present embodiment, in the data price calculation device, the provision rule setting process for setting the data provision condition which is the provision condition of the authority regarding the transaction data and the acquisition of the authority regarding the transaction data by the acquirer are the data. It is determined whether or not the provision condition is satisfied, and when it is determined that the data provision condition is satisfied, the data transaction process for executing the process of causing the acquirer to acquire the authority regarding the transaction data is executed.

In this way, information control of private transaction data can be performed by the provider side by executing the transaction of the transaction data only when the transaction rule (provision rule) of the provider side of the transaction data is satisfied.

The above description of the embodiment is for facilitating the understanding of the present invention, and does not limit the present invention. The present invention can be modified and improved without departing from the spirit of the present invention, and the present invention includes its equivalents.

For example, in the present embodiment, the data price calculation device 100 includes a module 120 for data sellers and a module 130 for data purchasers, but these may be provided by separate information processing devices.

Further, the seller terminal 200 may have some functions of the module 120 for the data seller. Further, the purchaser terminal 300 may have some functions of the module 130 for data purchasers.

Further, in the present embodiment, an example of buying and selling as a data transaction has been described, but the type of transaction is not limited to this. It suffices if there is an acquirer who acquires a predetermined authority regarding data from a predetermined partner, and the acquirer of the authority provides consideration to the provider. Such transactions include, for example, a transaction for obtaining a license such as a lease contract. In addition, the authority acquired by the acquirer through a transaction may have various authorities such as providing and disclosing the transaction data acquired by the transaction. Then, these transaction and authority conditions may be registered in the sales rule 124 or the transaction data purchase condition 136.

Further, the scope of disclosure or non-disclosure of transaction data may not be a group as in the present embodiment, but may be each entity (company) constituting the group.

Further, in the present embodiment, it is assumed that the transaction data is the same type of data, but different types of transaction data may be handled. In this case, for example, the accuracy direct influence and the accuracy indirect influence are calculated by different statistical distributions for each type of data.

In addition, the statistical method for estimating the range (distribution) of the estimated amount of private transaction data described in this embodiment is an example. For example, the estimated width may be based on the distribution ratio or the value of the transaction amount.

Further, regarding the calculation of the actual needs, the number of requests for private transaction data 306 may be used as the basis, or the price update request flag 305 may be used as the basis, as in the present embodiment.

1 data price calculation system, 100 data price calculation device, 200 seller terminal, 300 purchaser terminal, 110 mediation module, 111 private transaction data estimation processing unit, 112 private transaction data importance calculation processing unit, 113 private transaction Data pricing processing department, 114 private transaction data, 115 published transaction data, 116 corporate groups, 117 private transaction data sales conditions, 118 data sales request, 120 data seller module, 121 provision rule setting department, 122 sales Possible transaction data sharing processing unit, 123 data transaction processing department, 124 sales rules, 125 in-house transaction data, 130 data purchaser module, 131 acquisition condition setting unit, 132 transaction data purchase candidate list creation unit, 133 transaction data purchase plan Creation department, 134 transaction data purchase request registration department, 135 transaction data acquisition processing department, 136 transaction data purchase conditions, 137 transaction data purchase candidate list, 138 transaction data purchase plan

Claims (11)

1. A data price calculation method for calculating the consideration provided to the provider by the acquirer who acquires the authority regarding the predetermined transaction data from the predetermined provider.
   A data price calculator with a processor and memory
   Private transaction data estimation processing that infers the contents of transaction data that the acquirer has not acquired at least based on public data that is data that the acquirer can acquire the contents of.
   Private transaction data importance calculation processing that calculates the importance of the content of the transaction data based on the content of the estimated transaction data, and
   Private transaction data pricing processing that calculates the consideration to be provided to the provider based on the calculated importance, and
   How to calculate the data price.
2. The data price calculation device is
   In the private transaction data estimation process, a range of evaluation values of a plurality of the public data is calculated.
   In the private transaction data importance calculation process, the importance of the transaction data is calculated based on the range of the calculated evaluation value.
   The data price calculation method according to claim 1.
3. The data price calculation device is
   In the private transaction data estimation process, the difference between the calculated evaluation value range of the public data and the evaluation value range of other public data calculated based on the evaluation value range of the public data is specified.
   In the private transaction data importance calculation process, the importance of the transaction data is calculated based on the difference in the specified range.
   The data price calculation method according to claim 2.
4. The data price calculation device is
   In the private transaction data importance calculation process, the importance of the transaction data is calculated based on a parameter representing the demand for the transaction data.
   The data price calculation method according to claim 2.
5. The data price calculation device is
   In the private transaction data importance calculation process, the importance of the transaction data is calculated based on the number of times a predetermined provision request of the transaction data, which is the parameter, is received.
   The data price calculation method according to claim 4.
6. The data price calculation device is
   In the private transaction data importance calculation process, the importance of the transaction data is calculated based on the number of times the content of the transaction data, which is the parameter, is estimated.
   The data price calculation method according to claim 4.
7. The data price calculation device is
   A display process is executed in which information indicating the range of evaluation values of the plurality of public data calculated in the private transaction data estimation process is displayed according to the calculation order of the public data.
   The data price calculation method according to claim 2.
8. The data price calculation device is
   In the private transaction data pricing process, blockchain data shared with other data price calculation devices that stores the calculated consideration or the calculation history of the calculated importance is generated.
   The data price calculation method according to claim 1.
9. The data price calculation device is
   The acquisition condition setting process for setting the data acquisition condition, which is the acquisition condition for the transaction data, and
   It specifies the predetermined transaction data that satisfies the data acquisition condition, and executes an output process of partially disclosing the contents of the specified transaction data and outputting the data.
   The data price calculation method according to claim 1.
10. The data price calculation device is
    The provision rule setting process that sets the data provision condition, which is the provision condition of the authority related to the transaction data, and
    It is determined whether or not the acquisition of the authority regarding the transaction data by the acquirer satisfies the data provision condition, and when it is determined that the data provision condition is satisfied, the acquirer is given the authority regarding the transaction data. Execute the process to be acquired Data transaction process and execute,
    The data price calculation method according to claim 1.
11. It is a data price calculation device that calculates the consideration provided to the provider by the acquirer who acquires the authority regarding the predetermined transaction data from the predetermined provider.
    Has a processor and memory
    Private transaction data estimation processing that infers the contents of transaction data that the acquirer has not acquired at least based on public data that is data that the acquirer can acquire the contents of.
    Private transaction data importance calculation processing that calculates the importance of the content of the transaction data based on the content of the estimated transaction data, and
    Private transaction data pricing processing that calculates the consideration to be provided to the provider based on the calculated importance, and
    A data price calculator that runs.

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