Distributed Ledger Data Valuation via Similar Record Retrieval
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Solution Overview
Problem
Existing data management methods fail to efficiently determine the appropriate trading price of data sets, as they do not account for the value of data, leading to difficulties in valuation.
Innovation Solution
A data management method utilizing a distributed ledger system where servers store transaction data, allowing terminals to obtain and determine the value of a target data set by referencing similar data sets stored in the ledger, ensuring transparency and tamper-proof valuation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If data is collected and shared using distributed file sharing technique, then data can be shared over distributed network, but the value of data cannot be determined efficiently
Solution Approach 1:
The system implements feedback mechanisms where transaction records of similar data sets are retrieved from the distributed ledger and used to determine the value of the target data set. This feedback loop enables continuous refinement of value determination based on market transactions, resolving the contradiction between efficient data sharing and accurate value determination.
Solution Approach 2:
The distributed ledger serves as an intermediary that stores transaction records of similar data sets, enabling terminals to determine data values without direct negotiation. This intermediary mechanism allows efficient data sharing while providing accurate value determination through historical transaction data.
2Ease of operation
If traditional data management methods are used, then data can be stored and accessed, but transparency and tamper-proof valuation cannot be achieved
Solution Approach 1:
The system creates a distributed copy of the ledger across multiple servers, where transaction records are replicated and stored immutably. This copying mechanism ensures that data can be accessed conveniently while maintaining transparency and tamper-proof valuation through distributed verification.
Solution Approach 2:
The patent replaces traditional centralized data management with a distributed ledger system that uses cryptographic hashing and distributed consensus mechanisms. This substitution of mechanical centralized control with distributed cryptographic verification achieves both ease of operation and reliability.
3Device complexity
If centralized data management system is used, then data can be managed centrally, but system reliability is reduced due to single point of failure
Solution Approach 1:
The system segments the centralized data management function into multiple distributed nodes that collectively maintain the ledger. Each node stores copies of transaction records, eliminating the single point of failure while keeping the overall system structure relatively simple through modular architecture.
Solution Approach 2:
The patent transitions from a single-point (0D) or centralized (1D) data management approach to a distributed multi-node architecture (2D/3D). This dimensional expansion from centralized to distributed structure increases system reliability without proportionally increasing complexity.
Data Source
AI summary
In a data management method, a plurality of servers store, in a distributed ledger, at least one instance of transaction data each including record information; the record information includes a record of at least one data set; and each data set includes at least one instance of data, among a plurality of instances of data generated by a plurality of devices, satisfying a condition corresponding to the data set. The data management method includes a first terminal owned by a first user of a target data set, or a second terminal owned by a second user of the target data set, performing the following: obtaining the record of at least one similar data set similar to the target data set from the record information; and determining a value of the target data set based on the record obtained.