Data Monetization Client for Marketplace Valuation
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Solution Overview
Problem
Leveraging operational technology (OT) data in a data marketplace environment is challenging due to disparity in valuation algorithms, lack of conversion algorithms to currency, variety of cryptocurrency options, protocol disparities, and lack of mechanisms for data donations and balance sheet auditing.
Innovation Solution
A method that involves obtaining data valuations, converting them into a value for presentation in a data marketplace, brokering data transfers, managing data receipt, and using a data monetization client to advertise and monetize data sets, handle donations, and manage cryptocurrency transactions through a secure data pool framework with blockchain and EdgeX Foundry™ software.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If data valuations are obtained and converted into corporate currency for presentation in a data marketplace, then data monetization effectiveness is improved, but the complexity of handling multiple valuation algorithms and conversion processes increases
Solution Approach 1:
The patent introduces a data monetization client as an intermediary component that mediates between the data set and the data marketplace environment. This client handles the complex tasks of obtaining data valuations, converting them into corporate currency, and brokering data transfers, thereby shielding the overall system from the complexity of multiple valuation algorithms and conversion processes while maintaining effective data monetization
Solution Approach 2:
The data monetization client is designed as a multi-functional component that performs multiple operations including obtaining data valuations, converting valuations to corporate currency, brokering data transfers, managing data receipts, and handling cryptocurrency transactions. This universal approach consolidates multiple functions into a single component, improving productivity while managing complexity through integration
2Adaptability or versatility
If multiple data marketplace protocols are supported for data transfer, then adaptability to different data consumers is improved, but the difficulty of managing protocol disparities increases
Solution Approach 1:
The data monetization client acts as an intermediary that manages communications across multiple data marketplace protocols. It handles the complexity of protocol disparities by implementing protocol-specific logic within the client itself, allowing the system to support multiple protocols (improving adaptability) while centralizing protocol management in a single component (managing complexity)
Solution Approach 2:
The system segments protocol-specific functionality into separate modules or handlers within the data monetization client. Each protocol is managed by dedicated code segments that can be independently maintained and updated, reducing the overall complexity of managing multiple protocols while maintaining broad compatibility
3Reliability
If blockchain technology is used for secure data pool framework and cryptocurrency transactions, then transaction security and auditing capability are improved, but the computational overhead and transaction processing time increase
Solution Approach 1:
The system performs preliminary actions by pre-configuring blockchain wallets and establishing secure data pool frameworks before actual data transactions occur. This preparation work is done in advance, so that when actual data monetization transactions occur, the blockchain infrastructure is already in place and ready to process transactions securely without excessive delays
Data Source
AI summary
Techniques for leveraging data in a data marketplace environment are provided. For example, a method comprises the following steps. A representation of one or more data valuations for a given data set is obtained. The representation of the one or more data valuations for the given data set is converted into a value for presentation to a data marketplace environment. The data marketplace environment comprises one or more data marketplace protocols that each enable one or more data consumers to obtain data. The method brokers a transfer of the given data set through at least one of the data marketplace protocols to at least one data consumer. The method manages transfer of the given data set to the at least one data consumer and receipt of a result of the transfer from the at least one data consumer.