Data management apparatus

Abstract

To appropriately determine a consideration for provision of data.SOLUTION: A data management apparatus (for example, a data management server 110) includes: a database 172 that holds data (for example, personal data) provided from a provider (for example, a providing business operator); a value evaluation section 152 that evaluates a value of the data; a provision consideration determination section 154 that determines a first consideration (for example, a token), which is a consideration for provision of the data, on the basis of an evaluation result of the value of the data; and a consideration granting section 156 that grants the first consideration to the provider.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present invention relates to a data management device for managing data. [Background technology]

[0002] Big data refers to a wide variety of data that is generated daily. Conventionally, a system has been established in which data is automatically collected and aggregated as big data. For example, Patent Document 1 discloses a technology in which a data center is connected to each user's drive recorder via a communication network, and the data center accumulates road images, driving speed, driving route, and the like transmitted from the drive recorder as big data. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2015-210713 Summary of the Invention [Problem to be solved by the invention]

[0004] To improve the accuracy of big data, it is desirable for each business to collect its own data as big data. However, when trying to collect data from each business, the problem arises of how to define the benefits to the business for providing the data. Furthermore, if businesses are only able to receive a fixed fee for providing data regardless of the quality or quantity of the data, this could lead to a sense of unfairness among businesses, which could hinder the progress of big data.

[0005] In view of the above problems, an object of the present invention is to provide a data management device that can appropriately determine the price for providing data. [Means for solving the problem]

[0006] In order to solve the above problems, the data management device of the present invention comprises a database that holds data provided by a provider, a value assessment unit that assesses the value of the data, a provision fee determination unit that determines a first fee, which is compensation for providing the data, based on the evaluation result of the value of the data, and a fee award unit that awards the first fee to the provider.

[0007] The value assessment unit may assess the value of the data based on the reliability of the data.

[0008] The value assessment unit may assess the value of the data based on the degree of influence on user acquisition among users who use the data.

[0009] The data management device may include a data extraction unit that extracts data to be used by the user from the data stored in the database, a usage fee determination unit that determines a second fee as compensation for the use of the extracted data, and a fee collection unit that collects the second fee from the user.

[0010] The first consideration determined by the provision consideration determination unit and the second consideration determined by the usage consideration determination unit may both be expressed as tokens (virtual currency or various points) unique to the data management device.

[0011] The providers may include multiple businesses, the database may hold data provided by the multiple businesses, and the data provided by the businesses may include personal data of users of the businesses. [Effects of the Invention]

[0012] According to the present invention, it is possible to appropriately determine the compensation for providing data. [Brief explanation of the drawings]

[0013] [Figure 1] FIG. 1 is a block diagram for explaining an outline of a data management system. [Figure 2]FIG. 2 is an explanatory diagram for explaining how personal data is provided in the data management system. [Figure 3] FIG. 3 is a flowchart showing the flow of processing by the data management server. [Figure 4] FIG. 4 is an explanatory diagram for explaining how personal data is used in the data management system. [Figure 5] FIG. 5 is a flowchart showing the flow of processing by the data management server. [Figure 6] FIG. 6 is an explanatory diagram for explaining the processing of the value estimation unit. [Figure 7] FIG. 7 is a flowchart showing the flow of processing by the data management server. [Figure 8] FIG. 8 is an explanatory diagram for explaining an example of use of the data management system. DETAILED DESCRIPTION OF THE INVENTION

[0014] Preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Dimensions, materials, and other specific values ​​shown in the embodiments are merely examples for facilitating understanding of the invention and, unless otherwise specified, do not limit the present invention. In this specification and drawings, elements having substantially the same functions and configurations are designated by the same reference numerals to avoid redundant explanation, and elements not directly related to the present invention are not shown.

[0015] (Data Management System 100) 1 is a block diagram for explaining an outline of a data management system 100. As shown in FIG. 1, the data management system 100 includes a data management server 110, a provider business server 120, and a user business server .

[0016] The data management server (data management device) 110 is a server owned by a data manager, and manages data, for example, personal data, as big data. The data management server 110 is configured with a semiconductor integrated circuit including a processor (CPU) (not shown), a ROM storing programs, etc., and a RAM as a work area.

[0017] Here, personal data refers to information related to an individual. However, personal data does not only refer to personal information in the narrow sense defined by law (such as name, address, date of birth, and telephone number), but also includes various information that expresses individual characteristics, such as a user's attribute information, travel history, behavioral history, purchase history, physical information, property information, service acceptance status, and personal preferences. Personal data also includes information on people flow and product information that has been processed to prevent the identification of a specific individual, and the boundary between such information and personal information is unclear. Therefore, personal data is a wide range of information that can be found to have a relationship with an individual. Note that, while information related to a person (user) is used as the subject of personal data in this description, it is not limited to this case; it can also refer to information related to highly individual objects or organizations, such as households, real estate, vehicles, equipment, corporations, and communities.

[0018] The provider server 120 is a server owned by a provider (provider) that can provide personal data. The provider server 120 is composed of a semiconductor integrated circuit including a processor (CPU) (not shown), a ROM storing programs and the like, and a RAM as a work area. The provider server 120 is connected to a network 140 and can establish communication with the data management server 110. Note that, in this description, the provider is an organization that operates for profit or other purposes, but the provider is not limited to this case and may also be a non-profit organization or an individual.

[0019] The use business server 130 is a server owned by a user business (user) attempting to use personal data. The use business server 130 is composed of a semiconductor integrated circuit including a processor (CPU) (not shown), a ROM storing programs, etc., and a RAM as a work area. The use business server 130 is connected to a network 140 and can establish communication with the data management server 110. Note that, while the user here is described as a business user business, the user is not limited to this case and may also be a non-profit organization or an individual.

[0020] In order to improve the accuracy of big data used in such data management system 100, it is desirable for providers to collect their own personal data as big data. However, the benefits of providers providing their customers' personal data are not clear. Furthermore, if providers receive only a fixed fee for providing personal data regardless of the quality or quantity of the personal data provided by the providers, providers may not receive compensation commensurate with the value of the personal data they provide, which could lead to a sense of unfairness. Therefore, in this embodiment, a business structure (data linkage platform) is constructed that promotes the provision and use of personal data by appropriately determining the fee for providing personal data.

[0021] 2 is an explanatory diagram illustrating how personal data is provided in the data management system 100. Here, the processor of the data management server 110 operates programs in cooperation with the ROM and RAM, thereby functioning as functional units such as a data acquisition unit 150, a value assessment unit 152, a provision consideration determination unit 154, and a consideration provision unit 156. The data management server 110 also has storage means such as an HDD or SSD that function as a buffer 170 and a database 172.

[0022] In the data management system 100, user 1 receives services or purchases products from providers. Hereinafter, services, products, etc. provided to user 1 by providers or user businesses described below may be referred to as "offerings." User 1 includes customers who purchase or use offerings from each business. Note that user 1 also includes those who provide their personal data to each business without purchasing or using offerings.

[0023] The provider may acquire personal data of user 1 when providing a provision to user 1. The provider may also digitize information that it has independently obtained in the course of business, such as notes on paper forms, and store this as personal data. When the provider business server 120 acquires the personal data of user 1, it stores the data in association with an identifier that identifies the provision provided to user 1. The provider business server 120 may provide the personal data of user 1 to the data management server 110.

[0024] 3 is a flowchart showing the flow of processing by the data management server 110. The data acquisition unit 150 temporarily stores the personal data acquired from the provider business server 120 in the buffer 170 (S100).

[0025] The value assessment unit 152 assesses the value of the personal data held in the buffer 170 for each information item of each user 1 (S102). The processing of the value assessment unit 152 will be described in detail later.

[0026] The provision consideration determination unit 154 determines the consideration (first consideration) for the provision of the personal data based on the evaluation result of the value of the personal data (S104), and presents the consideration to the provider server 120. Here, a token is used as the consideration. The processing of the provision consideration determination unit 154 will be described in detail later. Here, a token refers to a crypto-asset (virtual currency) that is used in place of conventional coins or paper money, and examples include virtual currency and various points.

[0027] The provider confirms the token, which is compensation for the provision of personal data, through the provider business server 120. The compensation granting unit 156 determines whether the provider has agreed to the token and has received information from the provider business server 120 indicating that the provider has agreed to the token (S106). When the provider has agreed to the token and has received information from the provider business server 120 indicating that the provider has agreed to the token (YES in S106), the compensation granting unit 156 grants the token to the provider business server 120 (S108). The data acquiring unit 150 associates the personal data temporarily stored in the buffer 170 with its value, the granted token, and the agreement history, and stores them in the database 172 (S110).

[0028] Furthermore, if the provider does not agree to the token (NO in S106), the value granting unit 156 deletes the personal data acquired from the provider business server 120 from the buffer 170 (S112).

[0029] In this way, the data management server 110 can appropriately determine the compensation for the provision of personal data. Furthermore, by evaluating the value of the personal data, the data management server 110 can quantify the extent to which the personal data will contribute to the business of a user business when the user business acquires the personal data. Therefore, even if personal data is shared between businesses (enterprises), the total value of the personal data owned by each party can be quantified, making it possible to conduct transactions under appropriate conditions.

[0030] Furthermore, by providing compensation for the provision of personal data on the platform and making it possible to use the data in transactions on the platform, providers can record indirect non-operating profits as direct core business sales. Furthermore, providers can use the compensation they receive for other commercial transactions, improving convenience. Furthermore, by providing compensation as tokens that can be used in a closed marketing space, the use of the data management system 100 can be stimulated.

[0031] 4 is an explanatory diagram for explaining how personal data is used in the data management system 100. The processor of the data management server 110 operates programs in cooperation with the ROM and RAM, and thereby functions as functional units such as a data extraction unit 158, a usage fee determination unit 160, and a fee collection unit 162.

[0032] In the data management system 100, a user business attempts to provide a provision to a user 1. However, the user business has no way of knowing which of the many users 1 needs the provision. Even if the number of opportunities to prompt the user 1 to provide the provision is randomly increased, the provision of the provision will not be promoted if the user 1 does not need the provision or if the timing is not right for the user 1 to need the provision.

[0033] Therefore, the user business wishes to match the offering with the user 1 based on the personal data and identify the user 1 who needs the offering. Therefore, the user business server 130 attempts to acquire the personal data from the data management server 110.

[0034] 5 is a flowchart showing the processing flow of the data management server 110. The data extraction unit 158 ​​acquires information on information items desired by the user business from the user business server 130. Based on this information, the data extraction unit 158 ​​extracts personal data to be used by the user business from the personal data held in the database 172 (S150).

[0035] The usage consideration determination unit 160 determines a token as consideration (second consideration) for the usage of the extracted personal data (S152).

[0036] The using business confirms the token for use of the personal data through the using business server 130. The fee collection unit 162 determines whether the using business has agreed to the token and has received information from the using business server 130 indicating that the token has been agreed to (S154). If the using business has agreed to the token and has received information from the using business server 130 indicating that the token has been agreed to (YES in S154), the fee collection unit 162 collects the token from the using business (S156) and transmits the personal data to the using business server 130 (S158). On the other hand, if the using business has not agreed to the token (NO in S154), the fee collection unit 162 does not collect the token from the using business and does not transmit the personal data to the using business server 130.

[0037] Note that the user businesses to which the fee collection unit 162 can transmit personal data may be limited to businesses that have the right to handle personal data, thereby preventing leakage and unauthorized distribution of personal data.

[0038] The user business uses the acquired personal data to match the offerings that the user business can provide with the user 1. In this way, the user business can identify the user 1 to whom it can provide its offerings and the timing of providing them.

[0039] The tokens determined by the provision fee determination unit 154 and the tokens determined by the usage fee determination unit 160 are unified as crypto assets (virtual currencies) specific to the data management system 100. Therefore, for example, a business operator can use the tokens granted by the fee granting unit 156 based on the provision of personal data as a provider, and can acquire other personal data from the data management server 110 as a user. Here, by making available tokens specialized for the data management system 100, it is possible to promote the circulation of tokens in a business space with a limited scope of use.

[0040] Here, due to the synergistic effect of the provision and use of personal data, the personal data in the database 172 will be enriched, and as a result, the number of user businesses wishing to use the personal data will increase. This will expand the market size of the data linkage platform. Furthermore, due to this expansion of the market size, the token will be used exclusively, thereby providing a market advantage. Therefore, even if a third party were to build a system similar to the data management system 100, they would not be able to establish a business advantage.

[0041] The processing of the value assessment unit 152 and the processing of the provision consideration determination unit 154 of the data management server 110 will be described in detail below.

[0042] 6 is an explanatory diagram for explaining the processing of the value assessment unit 152. The value assessment unit 152 first determines whether the personal data provided by the provider is new personal data, that is, whether it overlaps with personal data that has already been stored.

[0043] As shown in Fig. 6, personal data is classified into a plurality of predetermined information items for each user 1. For example, no personal data has yet been associated with the address and date of birth of person B in Fig. 6. In the example of Fig. 6, when the provider provides personal data relating to person B's address and date of birth, the value assessment unit 152 adds the data to the database 172 as new personal data. On the other hand, when the provider provides personal data relating to real estate owned by person B in Fig. 6, this data overlaps with existing personal data, so the value assessment unit 152 does not add the personal data, determining that it is not new personal data.

[0044] However, some personal data related to information items, such as address, date of birth, gender, and possessions, have only one possible answer, while other personal data may allow multiple possible answers. A case in which multiple possible answers are allowed is when there are multiple options, such as the name of a vehicle owned, a desired magazine to purchase, an account, or text information used in a social networking service (SNS). When multiple possible answers are allowed, if the content is not duplicated, value assessment unit 152 adds the personal data to database 172 as new personal data.

[0045] If the personal data provided by the provider is new, the value assessment unit 152 assesses the value of the personal data based on the "quality" and "quantity" of the personal data. Here, an example of value assessment regarding the "quality" and "quantity" of personal data will be described.

[0046] The value assessment unit 152 assesses the reliability of the personal data as the "quality" of each information item of the personal data. Specifically, the value assessment unit 152 derives a reliability coefficient α as an index of reliability. The reliability coefficient α takes a value ranging from 0 to 1. The value assessment unit 152 derives the reliability coefficient α in consideration of the characteristics of the personal data, such as "when the data was recorded," "whether it is an estimated value, an input value, or a secondary acquisition," and "the data credibility of the provider."

[0047] With regard to the "data recording date" among the above factors, the value assessment unit 152 derives the reliability coefficient α based on the date the personal data was registered. For example, a predetermined value proportional to the difference between the date the personal data was registered and the present is subtracted from the reliability coefficient α. Therefore, the older the date the personal data was registered, the lower the value determined as the reliability coefficient α. However, in the case of age, etc., entered by the user 1 himself, reliability does not decrease over time, so the reliability coefficient α remains at 1.

[0048] With regard to whether the value is an estimated value, an input value, or a secondarily acquired value among the above factors, if the value is an "input value" input by the user 1 himself / herself, the value assessment unit 152 sets the reliability coefficient α to 1. Furthermore, if the trustworthiness of the provider itself is 1, the value assessment unit 152 sets the reliability coefficient α to 1. On the other hand, if the input value is an "estimated value" and its reliability is 50%, the value assessment unit 152 sets the reliability coefficient α to 0.5. Furthermore, if the value is secondarily acquired, the value assessment unit 152 sets the reliability coefficient α to a value less than 1.

[0049] Of the above factors, with regard to the "data credibility of the provider," the value assessment unit 152 updates the trust coefficient α based on the transition of the continuously provided personal data and public and private company information.

[0050] For example, the value assessment unit 152 compares the provided personal data before and after in a chronological order. Specifically, when personal data relating to the same information item is collected at different times, the value assessment unit 152 compares the personal data in a chronological order. The value assessment unit 152 analyzes how the personal data changes over time and evaluates the consistency of the personal data. For example, if the personal data of a certain information item has similar hobbies and preferences to the personal data of other information items of the same user 1 or other personal data provided at the same time for the same user 1, the reliability coefficient α will be relatively high.

[0051] Furthermore, the value assessment unit 152 cross-checks the personal data accumulated in the data management system 100. Specifically, the value assessment unit 152 determines the consistency of the personal data by comparing personal data collected from different personal data sources or by different methods. If the value assessment unit 152 finds a matching pattern or trend as a result of comparing the personal data, it sets the reliability coefficient α to a high value.

[0052] Furthermore, the value assessment unit 152 verifies the internal consistency of the provided personal data. Specifically, it verifies whether the personal data is internally consistent. The value assessment unit 152 evaluates the consistency within the data set, for example, by checking whether the answers to different questions are consistent, and increases the reliability coefficient α of personal data with high consistency.

[0053] Furthermore, the value assessment unit 152 performs external verification. Specifically, the value assessment unit 152 confirms the reliability of the personal data by, for example, comparing the personal data with highly reliable personal data information sources or existing literature. In this way, the value assessment unit 152 evaluates whether the personal data is consistent with other information sources through external verification, and increases the reliability coefficient α of personal data with high consistency.

[0054] In this way, by using the reliability coefficient α as the "quality" of each information item of personal data, the value of the personal data can be appropriately evaluated.

[0055] Furthermore, the value assessment unit 152 assesses the value of the information in addition to the reliability (trust coefficient α) as the "quality" of each information item of the personal data. Specifically, the value assessment unit 152 derives a value coefficient β. The value coefficient β is composed of a profit rate P, an influence coefficient E, and a discount D, and is expressed by the following mathematical formula 1.

number

[0056] The profit margin P indicates the profit per user (profit / person) that a user business can expect to earn when it uses personal data. Furthermore, if a user business can obtain added value when it uses personal data, a fee corresponding to the added value can be added to the profit margin P. For example, if multiple user businesses wish to use the personal data, each user business can be asked to propose a fee commensurate with the added value (a so-called auction). The value evaluation unit 152 then adds the highest fee among the proposed fees to the profit margin P, and provides the personal data to the user business that proposed the highest fee. The profit margin P can be any of an actual value, an estimated value, or a simulated value. Note that the profit margin P may be a constant and not included as a variable in Equation 1.

[0057] The influence coefficient E is an index that indicates the degree of influence that a user business that uses personal data has on acquiring User 1. Specifically, the influence coefficient E indicates the degree to which an information item of personal data affects the acquisition of User 1, that is, the probability (correlation coefficient) that a user business can acquire User 1 by possessing that information item. For example, if a user business can always acquire User 1 with any personal data, the influence coefficient E is 1 (100%).

[0058] The value assessment unit 152 may reflect the results of the use of the personal data by the using business operator to improve the accuracy of the profit margin P and the influence coefficient E. In this way, by using the influence coefficient E as the "quality" of each information item of the personal data, the value of the personal data can be appropriately assessed.

[0059] Discount D indicates a value deducted for each information item due to external factors such as preferential treatment based on the usage history of the user business operator, campaigns, etc. If no value is deducted, discount D may not be included in formula 1.

[0060] Next, value assessment unit 152 derives a value for all information items of the personal data provided by the provider. Value V is calculated by accumulating αβM for each information item over n, the number of information items, and is expressed by the following formula 2.

number

[0061] The consideration determination unit 154 determines the token T based on the value V evaluated by the value evaluation unit 152. The token T is derived by the following Equation 3.

number

[0062] In this way, by appropriately determining the token (compensation) for the provision of personal data, the user business can clearly understand the effect of using the personal data. Therefore, the user business can appropriately predict the profit from using the personal data and can appropriately return the profit to the user 1.

[0063] In addition, when personal data is provided to add new personal data to an information item that does not have any personal data, the value V or token T may be increased compared to when personal data is added to an information item that already has personal data. In this way, it is possible to encourage the addition of new users and information items.

[0064] In addition, the usage fee determination unit 160 determines a token for the use of personal data based on the token determined by the provision fee determination unit 154, for example, by multiplying the token determined by the provision fee determination unit 154 by the number of information items.

[0065] In the data management system 100 described above, the data management server 110 can appropriately determine the compensation for providing personal data. Furthermore, by evaluating the value of the personal data in the data management server 110, it is possible to quantify the extent to which the personal data will contribute to a business when a user business acquires the personal data. Furthermore, by making it possible to use tokens specialized for the data management system 100 as compensation used between the data manager, provider, and user business, it is possible to promote the circulation of tokens in a business space with a limited scope of use.

[0066] (Matching by data administrator) The above description was given with an example in which the user business server 130 of the user business acquires personal data from a database and performs matching within the user business between the offering and the user 1. Here, an example will be described in which the data management server 110 of the data manager matches the offering of the user business with the user 1, for example, by machine learning, and provides the matching results to the user business.

[0067] The using business can match the offering with the user 1 within its own business based on the personal data. However, in this case, the using business needs to select what personal data is necessary to provide the offering to the user 1. Therefore, the using business may wish to transmit information about the offering to the data management server 110 and perform matching within the data management server 110. In this case, the using business server 130 transmits information about the offering to the data management server 110.

[0068] 7 is a flowchart showing the flow of processing by the data management server 110. The data acquisition unit 150 stores information about the offering acquired from the offering business server 120 in the database 172 (S200).

[0069] The data management server 110 refers to the personal data in the database and the information related to the provision, and matches the provision with the user 1 through machine learning to derive (extract) a matching result (S202). In addition to matching the provision with the user 1, the data management server 110 may also derive the timing of providing the provision to the user 1. The data management server 110 may also derive the timing of providing information (mail newsletter, direct mail, etc.) about the availability of the provision. Such machine learning algorithms are widely known as existing technologies, and therefore a detailed description thereof will be omitted here.

[0070] The usage fee determination unit 160 determines tokens as a fee for performing matching (S204).

[0071] The using business confirms the token for the matching result through the using business server 130. The fee collection unit 162 determines whether the using business has agreed to the token and has received information from the using business server 130 indicating that the token has been agreed to (S206). If the using business has agreed to the token and has received information from the using business server 130 indicating that the token has been agreed to (YES in S206), the fee collection unit 162 collects the token from the using business (S208) and transmits the matching result to the using business server 130 (S210). On the other hand, if the using business has not agreed to the token (NO in S206), the fee collection unit 162 does not collect the token from the using business and does not transmit the matching result to the using business server 130.

[0072] Furthermore, the data management server 110 may provide solutions from each business operator instead of matching results. Solutions are the results of solving the issues and problems that business operators face using various methods, such as systems, know-how, knowledge, and human resources.

[0073] Here, the offering is provided to the user 1 at an appropriate time, so the using business can expect an increase in the user 1's willingness to purchase.

[0074] In this way, in the data management system 100, personal data and tokens are circulated between the data manager, provider, and user business, facilitating the provision of offerings to the user 1. An example of the use of the data management system 100 will be described below.

[0075] 8 is an explanatory diagram for explaining an example of use of the data management system 100. First, the data manager cooperates with a provider and receives personal data from the provider through the data management server 110. Through such cooperation of personal data with the provider, the personal data is accumulated in the database 172 (1).

[0076] Next, the data manager cooperates with the user business and allows the user business to use the personal data through the data management server 110. The user business matches the user 1 with the offering based on the personal data (2). Specifically, the user business estimates the user 1 to whom the user business can offer its offering and the timing of the offering. Note that the data management server 110 may acquire information about the offering from the user business, perform matching self-containedly, and provide the matching results to the user business.

[0077] Next, the user business or the data manager proposes to provide the user 1 with an offering based on the matching result (3). For example, the data management server 110 estimates the timing of the purchase of a home by the user 1 based on the date of birth, annual income, family composition, etc. of the user 1, and sends an article introducing real estate that matches the user's annual income and family composition at that timing via an email newsletter, etc.

[0078] Finally, the results of such collaboration between the data manager, provider, and user are analyzed. For example, the data management server 110 analyzes whether the user or data manager actually provided the item to the user 1 as a result of proposing the provision of the item to the user 1 (4). Based on the results of this analysis, the data management server 110 attempts to improve the accuracy of matching, etc.

[0079] In this way, the accumulation and use of personal data is promoted, and the configuration for evaluating matching results promotes the utilization of the data management system 100. Furthermore, by appropriately determining the compensation for the provision of personal data, a data linkage platform is established that promotes the provision and use of personal data. Furthermore, this data linkage platform realizes the construction of a platform for matching information and services, the participation of companies from different fields, and the linkage of customer bases between business establishments. In this way, it is possible to increase the satisfaction of user 1 and contribute to the profits of the data manager, provider, and user business.

[0080] While the preferred embodiments of the present invention have been described above with reference to the accompanying drawings, it goes without saying that the present invention is not limited to such embodiments. It is clear that those skilled in the art can conceive of various modifications and alterations within the scope of the claims, and it is understood that such modifications and alterations also fall within the technical scope of the present invention.

[0081] For example, in the above-described embodiment, personal data has been described as an example of data used in the data management system 100. However, this is not the only case, and various other data can be used, such as data that identifies an object, a service, a solution, a region, etc.

[0082] Furthermore, while tokens were mentioned above as payment, various other payments can be applied, including Japanese yen, foreign currency, and crypto assets (virtual currencies) already in circulation.

[0083] Additionally, although an example has been described in which personal data of user 1 is provided from provider server 120 to data management server 110, the present invention is not limited to this case, and user 1 may provide personal data directly to data management server 110 without going through provider server 120. This configuration improves the reliability coefficient α of the personal data and allows many information items to be filled in.

[0084] Note that the processing steps of the data management server 110 described using Figures 3, 5, and 7 do not necessarily have to be processed chronologically in the order described in the flowchart, and may include parallel or subroutine processing. [Explanation of symbols]

[0085] 1 user 100 Data Management System 110 Data management server (data management device) 120 Service provider server 130 User Business Server 150 Data Acquisition Unit 152 Valuation Department 154 Provision Price Determination Department 156 Compensation Department 158 Data Extraction Unit 160 Usage Fee Determination Department 162 Fee Collection Department 172 databases

Claims

1. a database for storing data provided by the provider; a value assessment unit that assesses the value of the data; a provision consideration determination unit that determines a first consideration as consideration for providing the data based on an evaluation result of the value of the data; a consideration providing unit that provides the first consideration to the provider; A data management device comprising:

2. The data management device according to claim 1 , wherein the value assessment unit assesses the value of the data based on the reliability of the data.

3. The data management device according to claim 1 , wherein the value assessment unit assesses the value of the data based on the degree of influence on user acquisition among users who use the data.

4. a data extraction unit that extracts data to be used by a user from the data stored in the database; a usage fee determination unit that determines a second fee as a fee for using the extracted data; a fee collection unit that collects a second fee from the user; The data management device according to claim 1 , comprising:

5. The data management device according to claim 4 , wherein the first consideration determined by the provision consideration determination unit and the second consideration determined by the usage consideration determination unit are both represented by a token unique to the data management device.

6. The provider includes a plurality of businesses, the database holds the data provided by the plurality of businesses; The data management device according to claim 1 , wherein the data provided by the business includes personal data of users of the business.

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