WO2020204690A1

WO2020204690A1 - Data brokerage and valuation system and method

Info

Publication number: WO2020204690A1
Application number: PCT/MY2020/050013
Authority: WO
Inventors: Puvan Jegaraj SELVANATHAN
Original assignee: Trace Blue Sdn. Bhd.
Priority date: 2019-03-29
Filing date: 2020-03-09
Publication date: 2020-10-08

Abstract

A data brokerage and valuation system (102) for facilitating brokerage and valuation service between sellers and buyers of data in a complex network, such as in a global supply chain, is provided herein. The data brokerage system (102) includes a profile 5 module (202) configured to build profiles of data sellers and data buyers, based upon registration information of the data sellers and the data buyers. The data brokerage system (102) further includes a valuation module (204) configured to determine value of the required data by the at least one data buyer; order module (206) configured to enable at least one data buyer to place order for the required data. The data brokerage 0 system (102) further includes a match module (208)configured to match the buyers required data and the seller's data using artificial intelligence and valuation module (204) configured to value the data to be exchanged between seller and buyer. The data brokerage system (102) further includes a payment module (210) configured to enable the at least one data buyer to make payment for the required data. The data brokerage 5 system (102) further includes a transfer module (212) configured to transfer matched data to the at least one data buyer, based upon successful payment.

Description

DATA BROKERAGE AND VALUATION SYSTEM AND METHOD FIELD OF THE INVENTION

Embodiments of the present invention generally relate to providing data brokerage and valuation services to individuals and various entities, and in particular to individuals and various entities in supply chains globally.

BACKGROUND

A supply chain is a connected system of various entities or partners involved in growing produce, manufacturing products or providing services. A typical example is the processing of a food product by taking raw produce and ingredients from various farmers and suppliers, then processing and packaging them into final food products in a factory involving workers using various machines. Recently, attention is being focused on improving supply chain visibility. Companies, particularly those with major brands, are increasingly required to show their supply chains are sustainable and transparent. Accordingly, growers, producers, traders, manufacturers, and retailers want to be seen and their efforts toward good practice recognized.

Further, some customers want to know the farmers who grow what they eat and the workers who stitch what they wear. Customers want assurance that companies in supply chains do not use child or forced labor, and do operate using environmentally- friendly practices. However, increased globalization means global supply chains today span many countries and involve various entities in between like farmers, workers, organizations, places, and things. The sheer volume of information, combined with a lack of transparency at the origin of chains and the many stages each chain involves, makes evidencing that a particular global supply chain is sustainable and free from social and environmental risks, very challenging.

Further, it is not possible to continue certifying good practices at the scale and pace that consumers today demand. This is because doing so substantially raises costs for both farmers and companies, translating into higher costs for products and services to consumers. Billions of dollars are spent on auditing, especially in food and garment supply chains. The increased overheads make it unprofitable and unviable for businesses to continue their license to operate and enjoy access to global markets. This is all done to uphold trust and transparency, which are very much required in supply chains.

Further, conventional systems lack a reliable data brokerage and valuation service that can enable individuals and various entities, such as those within global supply chains or other complex network systems, to package and sell data for additional earning, and further enable buyers to buy data that can improve their business efficiency, for example about supply chains. Hence, conventional systems lack a mechanism to broker or value data between data sellers and data buyers for efficient and transparent data exchange in complex network systems such as global supply chains. Therefore, there is a need for a better system and method to improve transparency in data exchange in complex network systems (such as global supply chains), and further to provide data brokerage and valuation service between data sellers and data buyers to resolve the abovementioned disadvantages associated with conventional methods.

SUMMARY

According to an aspect of the present disclosure, a data brokerage and valuation system (102) for facilitating brokerage service between sellers and buyers of data, such as in a supply chain, is provided herein. The data brokerage and valuation system (102) includes a profile module (202) configured to build profiles of data sellers and data buyers, based upon registration information of the data sellers and the data buyers. The data brokerage system (102) further includes a data valuation module (204) to determine the value of data required by user; and an order module (206) configured to enable at least one buyer to place order for the required data. The data brokerage system (102) further includes a match module (208) configured to match the buyers required data and the seller’s data using artificial intelligence. The data brokerage system (102) further includes a payment module (210) configured to enable the at least one buyer to make payment for the required data. The data brokerage system (102) further includes a transfer module (212) configured to transfer matched data to the at least one buyer, based upon successful payment. According to another aspect of the present disclosure, a computer-implemented method for facilitating brokerage and valuation service between sellers and buyers of data is provided herein. The computer-implemented method includes building profiles of data sellers and data buyers, based upon registration information of the data sellers and the data buyers. The computer-implemented method further includes enabling at least one buyer to place order for the required data. The computer-implemented method further includes matching the buyers required data and the seller’s data using artificial intelligence. The computer-implemented method further includes enabling the at least one buyer to make payment for the required data. The computer-implemented method further includes transferring the bundled data to the at least one buyer, based upon successful payment. The preceding is a simplified summary to provide an understanding of some aspects of embodiments of the present invention. This summary is neither an extensive nor exhaustive overview of the present invention and its various embodiments. The summary presents selected concepts of the embodiments of the present invention in a simplified form as an introduction to the more detailed description presented below. As will be appreciated, other embodiments of the present invention are the possible utilization, alone or in combination, of one or more of the features set forth above or described in detail below.

BRIEF DESCRIPTION OF THE DRAWINGS

The above and still further features and advantages of embodiments of the present invention will become apparent upon consideration of the following detailed description of embodiments thereof, especially when taken in conjunction with the accompanying drawings, and wherein:

FIG. 1 is a block diagram depicting a network environment according to an embodiment of the present invention; FIG. 2 is a block diagram of modules stored in memory, according to an embodiment of the present invention;

FIG. 3 is a schematic diagram of type of entity and required information from entities for registration, according to an embodiment of the present invention;

FIG. 4 is a schematic diagram of types of profiles built for various entities including a person, organization, place or thing, according to an embodiment of the present invention;

FIG. 5 is a schematic diagram of globally unique identification numbers created for different entities like people, organization, place or thing, according to an embodiment of the present invention; FIG. 6 is a schematic diagram of an exemplary format of the globally unique identification number, according to an embodiment of the present invention;

FIG. 7 is an exemplary diagram showing status of sustainable development targets (SDG) for various persons having globally unique identification number (GUID), according to an embodiment of the present invention; FIG. 8 is an example of bluenumber consisting of GUID;

FIG. 9 is a schematic diagram of exemplary data bundle being transferred to a data buyer, according to an embodiment of the present invention; and

FIG. 10 depicts an exemplary flowchart illustrating a method of facilitating brokerage and valuation service between sellers and buyers of data using artificial intelligence, according to an embodiment of the present invention.

To facilitate understanding, like reference numerals have been used, where possible, to designate like elements common to the figures.

DETAILED DESCRIPTION

As used throughout this application, the word“may” is used in a permissive sense (i.e., meaning having the potential to), rather than the mandatory sense (i.e., meaning must). Similarly, the words “include”, “including”, and “includes” mean “including” but not“limited to”.

The phrases “at least one”, “one or more”, and “and/or” are open-ended expressions that are both conjunctive and disjunctive in operation. For example, each of the expressions“at least one of A, B, and C”,“at least one of A, B, or C”,“one or more of A, B, and C”,“one or more of A, B, or C” and“A, B, and/or C” means A alone, B alone, C alone, A and B together, A and C together, B and C together, or A, B, and C together. The term“a” or“an” entity refers to one or more of that entity. As such, the terms“a” (or“an”),“one or more” and“at least one” can be used interchangeably herein. It is also to be noted that the terms“comprising”,“including”, and“having” can be used interchangeably. The term“automatic” and variations thereof, as used herein, refers to any process or operation done without material human input when the process or operation is performed. However, a process or operation can be automatic, even though performance of the process or operation uses material or immaterial human input, if the input is received before performance of the process or operation. Human input is deemed to be material if such input influences how the process or operation will be performed. Human input that consents to the performance of the process or operation is not deemed to be“material”.

FIG. 1 illustrates an exemplary network environment of a network environment (100) where various embodiments of the present invention may be implemented. The network environment (100) includes a data brokerage and valuation system (102) connected to various entities such as a data seller entity system (104) and data buyer entity system (108) via a network (106). In an embodiment, various entities such as data seller entity system (104) and data buyer entity system (108) may belong to any complex network system such as a global supply chain including (but not limited to) a manufacturer system, a producer system, a distributor system, and a user/consumer/client via a network (106). Further, the complex network may be a network of buyers and sellers belonging to different supply chains globally. The Network (106) may include, but is not restricted to, a communication network such as Internet, PSTN, Local Area Network (LAN), Wide Area Network (WAN), Metropolitan Area Network (MAN), and so forth. In an embodiment, the network (106) can be a data network such as the Internet.

Further, the messages exchanged between the data brokerage and valuation system (102) and the various entities (104) and (108) can comprise any suitable message format and protocol capable of communicating the information necessary for the data brokerage and valuation system (102) to assign globally unique identification numbers to the various entities (a person, a thing, an organization, and a place) and provide data brokerage and valuation service between data buyers and data sellers. The data buyer entities (108) may utilize the data brokerage and valuation system (102) to perform valuation of data and buy required data from the data seller entities (104). In a preferred embodiment, the system may be enabled to perform valuation of data sold by sellers. In an embodiment of the present invention, the data brokerage and valuation system (102) may be a computing device. In operation, an entity (such as data buyer entity or data seller entity) connected to the supply chain may access the data brokerage and valuation system (102) to register itself, by providing required information about itself.

The data brokerage and valuation system (102) includes a processor (110) and a memory (112). In one embodiment, the processor (110) includes a single processor and resides at the data brokerage and valuation system (102). In another embodiment, the processor (110) may include multiple sub-processors and may reside at the system as well as the user devices of the various entities. Further, the memory (112) includes one or more instructions that may be executed by the processor (110) to build profiles of data sellers and data buyers of different global supply chains, to enable buyers to place order for the required data, to enable buyers or sellers to perform valuation of data; to match the buyers required data and the sellers data using artificial intelligence, to enable the buyers to make payment for the required data, and to transfer the bundled data to buyers, based upon successful payment.

In one embodiment, the memory (112) includes the modules (114), a profile database (116), and a globally unique identification number database (118), and other data (not shown in Figure). In an embodiment, the profile database (116) may include various profiles built by the system (102) based on registration information of entities. The globally unique identification number database (118) may include globally unique identification numbers generated by the system (102) with corresponding entities details. The other data may include various data generated during processing of the collected registration information from various entities and matching of the seller data and buyer required data. In one embodiment, the profile database (116) and the globally unique identification number database (118) are stored internal to the system (102). In another embodiment, the profile database (116) and the globally unique identification number database (118) may be stored external to the system (102), and may be accessed via the network (106). Furthermore, the memory (112) of the system (102) is coupled to the processor (110).

Referring to FIG. 2, the modules (114) include a profile module (202), a valuation module (204), an order module (206), a match module (208), a payment module (210), and a transfer module (212). The modules (114) are instructions stored in the memory and may process collected data to provide brokerage and valuation service between the different data buyers and the data sellers.

According to an embodiment of the present invention, the profile module (202) is configured to build profiles of buyers and sellers of data. In an embodiment, the profile module (202) is configured to enable the users (such as the buyers and the sellers) to register a profile themselves. In another embodiment, the profile module (202) may create a profile for users and assign the profile to the users at the data brokerage and valuation system (102). Further, in an embodiment, as shown in FIG. 3, based on a type of entity (for example, person, organization, place, or thing), the users are required to provide different data to the profile module (202). In an embodiment, if the entity is a person, then information about that person may be required such as name, address, date joined, type, and gender. Further, some required information may be optional such as affiliation, website, email, etc. Further, in case the entity is an organization, place or thing, information like name, address, joining date, and type of entity is required, as shown in FIG. 3. Further, consent may be taken from the users (data sellers) upon or after registration to make available their data for generation, presentation, analysis and sale to data buyers. Further, the profile module (202) is configured to save the profiles generated in the profile database (116).

The profile module (202) is further configured to profile the received data of various users based on a predetermined data structure/format. In an embodiment, the ‘person’ category may be further categorized based on the profession of the person. For example, a person may be a farmer, factory worker, fisherman, garment worker, or trader, as shown in FIG. 4. Similarly, organizations may be academic, commercial, government, intergovernmental, non-profit, or research in nature. Further, the place may be a dock, estate, factory, farm, mill, office, processor, refinery, retail, transport hub, or warehouse. Furthermore, the thing may be a machine, vehicle, or any other, as shown in FIG. 4. Further, according to an embodiment of the present invention, the profile module (202) is configured to assign a globally unique identification number to each data buyer and data seller (such as person, place, organization, and thing), as shown in FIG. 5. In an embodiment, the globally unique identification number includes a predetermined format/template shown in FIG. 6. In an embodiment, the globally unique identification number generated by the profile module (202) is complex, random, and unique. Further, the profile module (202) is configured to save the assigned globally unique identification numbers in the database (118).

Further, in an embodiment, as shown in FIG. 6, the globally unique identification number includes‘20’ characters that include‘4’ letters, and‘16’ numbers. Further, the globally unique identification number is randomly assigned with no reference values. Further, the globally unique identification number references a single entity in the database (118). Those skilled in the art will appreciate that the complex, random, and unique nature of the globally unique identification number assures the privacy to the entity (the person, thing, organization, or place).

The data valuation module (204) is configured to perform valuation of data supplied by data seller entities (104) and determine a price for the data. In an embodiment, the valuation of the data may be based on market research and analytics. In another embodiment, the valuation of the data may be based on predetermined rules. Further, the valuation module (204) is configured to establish a contract to broker the data at the determined price.

In a preferred embodiment, data collection to be fed to the valuation module (204) may be performed by various means, or methodologies. In accordance with an embodiment of the present invention, data may be collected via various means or methodologies. For instance, data may be collected via surveys as a form of questionnaires to produce a scorecard to measure the United Nations (UN) Sustainable Development Goals (SDGs). In a further example, the data collected for the scorecard is accordingly prepared as being beneficiary-centric where at least one set of questions could lead to quantifying the well-being or prosperity of a person or a place, relative to the SDGs. It is anticipated that such surveys for data gathering or collection can be manual (by conducting interviews, at seminars, etc.) or via distribution of surveys over the internet or via applications readable or executable by handheld devices. Examples of how the surveys can be conducted include, but not limiting to the following: i) Manual Surveys: Providing a questionnaire that is tailored based on SDG scorecard survey;

11) Handheld Device based Surveys: Users enter information through an application that is configured to be executable by a handheld device or a computer;

Based on the surveys above, information or data obtained may be further analysed to produce a structured report with predetermined criteria or parameters. For example, a sustainability report may be produced from crowdsourced survey data to assess results against the SDGs metrics and support an entity’s claims regarding their promotion of the SDGs. It is anticipated that the application interface (API) may be developed based on a predetermined design or criteria based on the features of the present invention. It is further anticipated that data collected by scorecards may be used by external modules or systems for further analysis or processing.

In an embodiment, data may be fed by the the profile module (202) which is configured to enable the users (such as the buyers and the sellers) to provide answers to a questionnaire related to sustainable development goals (SDG). In an embodiment, answers to the questionnaire includes predefined thresholds including‘low’,‘progress’ or‘high’ scores for different targets under each SDG. Those skilled in the art will appreciate that according to United Nations Development Program (UNDP), each member country has to try and achieve‘17’ sustainable development goals (SDG) that includes‘169’ targets under different SDG, for each of their citizens.

In an embodiment, the profile module (202) is further configured to measure and determine number of targets achieved for different SDG for a particular person, based on answers provided by that particular person in the questionnaire. For example, as shown in FIG. 7, (reference numeral 400), the profile module (202) may determine a particular individual is not poor, not hungry, have good health, well educated, access to clean water and sanitation, based on the answers. The profile module (202) is further configured to certify such individuals as individuals who have achieved SDG or not achieved SDG.

The profile module (202) is further configured to determine whether a particular individual has achieved some targets but not achieved other targets under SDG. For example, a particular individual may need nutrition, needs education, needs good health, but is not poor. The profile module (202) is configured to highlight such unachieved targets under SDG using a color wheel over that person profile, as shown in FIG. 7. Further, in an embodiment, the profile module (202) is configured to calculate average score of all targets within each SDG achieved by a particular individual, and display the score over the profile of the individual. The profile module (202) is further configured to add details of targets achieved under each SDG by individuals in their stored profile.

In an embodiment, the profile module (202) is further configured to enable various stakeholders report on number and type of people within their influence. For example, companies can report on supply chain sustainability, NGO can report on practical training programs that have contributed to achieving SDG targets. Further, the profile module (202) is configured to collate different reports and results from different stakeholders and may determine individual level using the globally unique identification numbers assigned to each individual.

Now referring to the valuation module (104), using the gathered/collected information, the valuation module (204) is configured to perform valuation of data required by the data buyer. In an embodiment, for direct auction market, the valuation module (204) is configured to first determine whether the seller sells the data at fixed price or the sellers sells the data through auction. In an embodiment, the valuation module (204 may determine such information based on registration information of sellers. In case, the sellers sell at fixed price, the valuation module (204) is configured to compare the fixed price set by the seller with the floor price.

In another case, if the seller sells through auction, the valuation module (204) is configured to enable the buyers to submit bids by the buyers. Further, the valuation module (204) is configured to select a highest bid submitted by the buyer. Further, in an embodiment, the valuation module (204) is configured to check whether the highest bid received or the fixed price set by seller is above floor price or minimum price against the data set, based on comparison of the highest bid with the floor price. In case, the highest bid received from buyer for the data or the fixed price set by the seller is above the floor price, the valuation module (204) is configured to set/establish such price as price for that dataset. Alternatively, if the highest bid received from buyer for the data or the fixed price set by the seller is less than the floor price, the valuation module (204) is configured to cancel such bidding/fixed price and invite the buyers to bid again or invite the seller to set fixed price again for the particular data set. Those skilled in the art will appreciate that such floor price may facilitate avoiding market failures such as seller monopoly or buyer monopoly in the online market, and provide for healthy competition among the buyers or among the sellers.

Further, in case of reversed auction market, whereas buyer submitted the required final product (or dataset), the valuation module (204) is configured to invite sellers to bid for the product submitted by the buyer. In an embodiment, for reversed auction market, the valuation module (204) is configured to first determine whether the seller sells the data at fixed price or the sellers sells the data through auction. In an embodiment, the valuation module (204) may determine such information based on registration information of sellers. In case, the sellers sell at fixed price, the valuation module (204) is configured to compare the fixed price set by the seller with the floor price.

In another case, if the seller sells through auction, the valuation module (204) is configured to enable the sellers to submit bids for the product submitted by the buyer. Further, the valuation module (204) is configured to select a lowest bid submitted by the seller. Further, in an embodiment, the valuation module (204) is configured to check whether the lowest bid received or the fixed price set by seller is above the floor price or minimum price against the data set.

In case, the lowest bid received from a seller or the fixed price set by the seller is above the floor price, the valuation module (204) is configured to set/establish such price as price for that dataset. Alternatively, if the lowest bid received from the seller for the data or the fixed price set by the seller is less than the floor price, the valuation module (204) is configured to cancel such bidding/fixed price and invite the sellers to bid again or invite the seller to set fixed price again for the particular data set. Those skilled in the art will appreciate that such floor price may facilitate avoiding market failures such as seller monopoly in the online market, promotes healthy competition among sellers, and enables even small sellers to compete against big sellers.

Further, the data valuation module (104) in accordance with the preferred embodiment of the present invention advantageously provides governments, companies, and communities with data about sustainable development goals (SDG) targets of individuals, thereby enabling them to focus on lagging indicators on SDG activities and helping them to achieve SDG. Thus, the data valuation system is configured to supplement on-going efforts of various national statistical offices in gathering data to both monitor and achieve SDG. For example, for Indonesian Oil Palm sector, globally unique identification numbers may be issued for all smallholders, businesses, estates, and other actors, thereby further allowing baseline SDG parameters, geolocation, and relationships. For example, farmer profiles may show their location, what training they received, market opportunity open for them, their household income, and extent of their financial and digital inclusion.

Further, according to an embodiment of the present invention, the order module (206) is configured to enable the data buyer entity (108) to place order for the required data. For example, a particular type of buyer may be interested in a particular type of data belonging to sellers that may increase and optimize business efficiency of the buyer organization. Further, in an embodiment, the order module (206) is configured to enable the buyer to choose bundle of data and packaging of the data. Those skilled in the art will appreciate that the data may be chosen to be packaged in both aggregated and disaggregated ways by the data buyers/users. Further, the order module (206) is configured to create‘exchange traded data (ETF) format’ that enables the buyers to place orders without specifying individuals or subset of interests.

Further, according to an embodiment of the present invention, the match module (208) is configured to automatically match the buyers required data and the sellers available data. In an embodiment, the match module (208) is configured to use artificial intelligence (for example, machine learning and deep learning) and the globally unique identification numbers to match buyers required data and available data of sellers. For example, a particular distributor (or data buyer) of a supply chain may require data on particular manufactures and particular producers of the supply chain in order to improve logistics of the distribution business.

The match module (208) is configured to match particular needs of particular buyers in a supply chain with available particular data sellers in same supply chain. Further, the match module (208) is configured to match particular needs of particular buyers in a supply chain with available particular data sellers in different supply chain as well. Those skilled in the art will appreciate that successful matching of data may be fed back to the machine learning in order to improve matching of the buyers required data and the seller’s available data. Further, the match module (208) is configured to enable a marketplace for data by providing facility such as auction and reverse auction of data.

Further, in an embodiment, the match module (208) is configured to match buyers required data with the seller’s data, after the buyer has specified preference or interest. In another embodiment, the match module (208) is configured to match buyers required data with the seller’s data, even when the buyer has not specified preference or interest, but the buyer is likely to show interest after knowing about such data. Those skilled in the art will appreciate that such data may be marketed on the platform provided by the data brokerage system or other digital platforms to attract such data buyers.

Further, according to an embodiment of the present invention, the payment module (210) is configured to enable the data buyers to make payment for the data. For example, the payment module (210) may connect the buyer with a payment gateway, and provide different options like credit card, debit card, and Internet or electronic banking for making the payment. In an embodiment, the payment module (210) is configured to provide various payment facility to buyers, such as direct payment, unit- type trust data (i.e., each data contributor has a unit share), dividend type data (dividend they receive if and when they become member of the data cooperative).

Further, according to an embodiment of the present invention, the transfer module (212) is configured to transfer the required data by buyers in a bundle with a contract note to the data buyer, based upon successful payment by the data buyer. In an embodiment, the bundled data my include data about a person (such as name, location, profession, gender etc.) and place (location, product, area etc.) as shown in FIG. 8. In an embodiment, the contract may electronic contract and may include minimum (proprietary specification) and provision of both property data rights and a mechanism to set floor prices for the data by the buyers or sellers. Further, according to an embodiment of the present invention, the transfer module (212) is configured to split the revenue received from the data buyer among the data sellers, the platform (for example, commission fee), and the government applicable taxes. In an embodiment, the transfer module (212) is configured to transfer seller profit sharing portion to the seller electronically. Further, the transfer module (212) is configured to transfer government taxes to government authority electronically. Further, the remaining revenue amount may be saved for the data brokerage platform (i.e., data brokerage system) income by the transfer module (212).

FIG. 9 illustrates an exemplary flowchart of a method of facilitating brokerage service between sellers and buyers of data in a complex network (for example, a global supply chain) using artificial intelligence, according to an embodiment of the present invention. Initially, at step 902, user accounts are created, as users are required to register and provide their details on the data brokerage platform. In an embodiment, if the entity is a person, then name, address, date joined, type, and gender about the person may be required. Further, in case the entity is an organization, place or thing, information like name, address, joining date, and type of entity may be required.

At step 904, globally unique identifier numbers are issued to each user (data buyer as well as data seller) and profiles are created. In an embodiment, the globally unique identification number includes a predetermined format/template and includes ‘20’ characters. At step 906, supply chain is built using globally unique identification number (GUIN). At step 908, a user is asked whether s/he would like to become data seller. If yes, method proceeds to step 912. Otherwise, at step 910, seller value proposition is created.

At step 912, user data is taken as input. At step 914, seller datasets are built. For example, profiles may be built for different type of sellers. For example, a person may be a farmer, factory worker, fisherman, garment worker, or trader. Similarly, organizations may be academic, commercial, government, intergovernmental, non- profit, or research in nature. Further, the place may be a dock, estate, factory, farm, mill, office, processor, refinery, retail, transport hub, or warehouse. Furthermore, the thing may be a machine, vehicle, or any other.

At step 916, input of buyers of data is taken. At step 918, data targeting is performed and data input is evolved and method returns to step 912, as shown in FIG. 9. At step 920, buyer datasets are created. For example, buyers may choose how to bundle and package data required by them. At step 922, buyer datasets and seller datasets are matched. According to an embodiment of the present invention, artificial intelligence (for example, machine learning) and globally unique identification numbers may be used to match datasets between the buyers required data and sellers available data.

At step 924, data value is determined. In an embodiment, the valuation of the data may be based on market research and analytics. At step 926, buyer value proposition is understood. At step 928, data is packaged. In an embodiment, the data may be packaged according to preference of the buyer as specified.

At step 930, price of data is established. At step 932, packaged data is promoted among data buyers. At step 934, buyer makes payment for the data. At step 936, payment process is performed. In an embodiment, various payment facilities may be provided to buyers, such as direct payment, unit-type trust data, or dividend type data. At step 938, seller value proposition is maintained. After the successful payment by the buyer, the bundled data and a contract note to the buyer may be transferred. Further, the revenue received from the buyer may be split among the sellers, the platform, and the govt taxes, and the method concludes.

The data brokerage and valuation system (102) and the method (800) performed by the data brokerage system (102) advantageously provides data brokerage service between data buyers and data sellers in a complex network (i.e., network of buyers and sellers belonging to different supply chains globally). Further, the data brokerage system (102) enables the data sellers (such as individual in supply chain) to cash in their data and increase income/revenue for themselves. Further, the data brokerage system (102) acts a platform for data brokerage and provides necessary data to the data buyers to enable them to improve their business performance and increase visibility in the supply chain. Further, the data brokerage system provides a secured platform between a buyer, a seller, trader, producer, manufacturer, and retailer. In an embodiment, various services such as auction, reverse-auction may be provided by the data brokerage system (102) in the secured network. Further, the globally unique identification number assigned by the data brokerage system may be used to determine who grows or supplies raw material or manufactured goods, where they are located, business risks, and opportunities for improvements in the global supply chains. Further, the data brokerage system (102) enables the data buyers to access such critical data legally. Further, the data brokerage and valuation system (102) and the method (800) performed by the data brokerage and valuation system (102) advantageously makes supply chains transparent for the companies involved in the supply chain. Further, the data brokerage system enables producers, traders, manufacturers, and retailers to be seen and have their efforts recognized as being sustainable. Further, the system of the present invention enables everyone in the supply chain to show them, and volunteer their good practices (for example, environmentally clean practices).

Further, the system of the present invention provides many advantages to persons such as farmers and factory workers. For example, by having a globally unique identification number and being connected to the data brokerage system, a farmer may access various benefits such as additional income/revenue from his/her data, prices, market information, connectivity, family support, government training, self- improvement, farm technology, certification, shared services, remote sensing, insurance, discounts, logistics support, community support, finance support, banking services, direct selling service, etc.

The foregoing discussion of the present invention has been presented for purposes of illustration and description. It is not intended to limit the present invention to the form or forms disclosed herein. In the foregoing Detailed Description, for example, various features of the present invention are grouped together in one or more embodiments, configurations, or aspects for the purpose of streamlining the disclosure. The features of the embodiments, configurations, or aspects may be combined in alternate embodiments, configurations, or aspects other than those discussed above. This method of disclosure is not to be interpreted as reflecting an intention that the present invention requires more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single foregoing disclosed embodiment, configuration, or aspect. Thus, the following claims are hereby incorporated into this Detailed Description, with each claim standing on its own as a separate embodiment of the present invention.

Moreover, though the description of the present invention has included descriptions of one or more embodiments, configurations, or aspects and certain variations and modifications, other variations, combinations, and modifications are within the scope of the present invention, e.g., as may be within the skill and knowledge of those in the art, after understanding the present disclosure. It is intended to obtain rights which include alternative embodiments, configurations, or aspects to the extent permitted, including alternate, interchangeable and/or equivalent structures, functions, ranges, or steps to those claimed, whether or not such alternate, interchangeable and/or equivalent structures, functions, ranges, or steps are disclosed herein, and without intending to publicly dedicate any patentable subject matter.

Claims

1. A data brokerage and valuation system (102) for facilitating brokerage service between sellers and buyers of data in a complex network, the data brokerage system (102) comprising a processor (110) and a memory (112), the memory (112) storing:

a profile module (202) configured to build profiles of data sellers and data buyers, based upon registration information of the data sellers and the data buyers;

an order module (206) configured to enable at least one data buyer to place order for the required data;

a valuation module (204) configured to determine value of the required data by the at least one data buyer;

a match module (208) configured to match the buyers required data and the sellers available data using artificial intelligence;

a payment module (210) configured to enable the at least one data buyer to make payment for the required data; and

a transfer module (212) configured to transfer matched data to the at least one data buyer, based upon successful payment.

2. The data brokerage and valuation system (102) of claim 1, wherein the profile module (202) is configured to assign a globally unique identification number to each data buyer and each data seller.

3. The data valuation system (102) of claim 1, further comprising a profile module (202) configured to measure number of targets achieved for sustainable development goals (SDG) by a particular person, based on answers provided by the particular person in a questionnaire.

4. The data brokerage and valuation system (102) of claim 1, further comprising a valuation module (204) that is configured to determine valuation of data supplied by data sellers.

5. The data brokerage and valuation system (102) of claim 1, wherein the order module (206) is configured to enable the buyer to choose to bundling of data and packaging of data.

6. The data brokerage and valuation system (102) of claim 1, wherein the match module (208) is configured to use machine learning to match data between the data sellers and data buyers.

The data brokerage and valuation system (102) of claim 1, wherein the valuation module (204) is configured to determine whether the at least one seller sells the data at fixed price or through action.

7. The data valuation system (102) of claim 1, wherein the valuation module (204) is configured to determine value of the data based on auction, in case the seller sells through auction.

8. The data brokerage and valuation system (102) of claim 1, wherein the valuation module (204) is configured to enable the at least one buyer to submit bid for the required data.

9. The data brokerage and valuation system (102) of claim 7, wherein the valuation module (204) is configured to determine value of the data, based on highest bid received from the at least one buyer, in case the highest bid received is above a floor price.

10. The data brokerage and valuation system (102) of claim 1, wherein the valuation module (204) is configured to determine value of the data as a fixed price set by the at least one seller, in case the at least one seller sells the data at fixed price and the fixed price is higher than a floor price.

11. The data brokerage and valuation system (102) of claim 9, wherein the valuation module (204) is configured to invite the at least one seller to bid for the product submitted by the at least one buyer.

12. The data brokerage and valuation system (102) of claim 1, wherein the payment module (210) is configured to enable the at least one data buyer to make direct payment, unit-type trust data, or dividend type data.

13. The data brokerage and valuation system (102) of claim 1, wherein the transfer module (212) is further configured to transfer a contract note to the at least one data buyer, based upon successful payment by the data buyer.

14. The data brokerage and valuation system (102) of claim 13, wherein the contract note includes minimum proprietary specification and a provision of property data rights.

15. The data brokerage and valuation system (102) of claim 1, wherein the transfer module (212) is further configured to split the revenue received from the data buyer between the data sellers and the platform.

16. The data brokerage and valuation system (102) of claim 15, wherein the transfer module (212) is configured to transfer a profit sharing portion to the data seller electronically.

17. A computer- implemented method for facilitating brokerage and valuation service between sellers and buyers of data in a complex network, the computer- implemented method comprising:

building profiles of data sellers and data buyers, based upon registration information of the data sellers and the data buyers; enabling at least one data buyer to place order for the required data; matching the buyers required data and the seller’s data using artificial intelligence; determining the value of required data; enabling the at least one data buyer to make payment for the required data; and transferring the bundled data to the at least one data buyer, based upon successful payment.

18. The computer-implemented method of claim 17, wherein the globally unique identification number includes a predetermined format.

19. The computer-implemented method of claim 17, further comprising transferring a contract note to the at least one data buyer, based upon successful payment by the data buyer.

20. The computer-implemented method of claim 17, further comprising splitting the revenue received from the data buyer, and transferring a profit sharing portion to the data seller electronically.