Dataset Valuation Scoring for Certified Data Exchange
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Solution Overview
Problem
Existing data exchange systems fail to systematically gather, score, value, and exchange data in a wide-ranging and efficient manner, limiting its utilization beyond the entity selling the information.
Innovation Solution
A method for valuing datasets through a DIM score, combining objective and subjective components, involving data size, accuracy, relevance, and scarcity, certified by data wranglers, and presented with a certification for exchange.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional data capture methods by individual entities are used, then data can be collected and exploited by the entity, but data availability to other entities is limited and data cannot be used at its highest value
Solution Approach 1:
The patent introduces a data exchange platform as an intermediary between data providers and data consumers. This platform systematically gathers data from multiple entities, applies standardized scoring and valuation methodologies, and facilitates controlled data sharing. The intermediary resolves the contradiction by enabling broad data availability while maintaining organized management through centralized scoring, valuation, and exchange protocols.
2Measurement precision
If no systematic scoring system is implemented, then data exchange can occur informally, but data cannot be valued accurately and exchange efficiency is reduced
Solution Approach 1:
The patent segments data valuation into multiple independent scoring dimensions including data quality, completeness, accuracy, relevance, and scarcity. Each dimension is evaluated separately using specific criteria and weighted appropriately. This segmentation enables precise measurement of data value while keeping the scoring system manageable through modular assessment categories that can be applied systematically.
Solution Approach 2:
The patent establishes a comprehensive parameter system for data valuation that transforms qualitative data attributes into quantifiable scores. By defining specific parameters such as data completeness percentage, accuracy metrics, relevance weights, and scarcity factors, the system enables precise measurement and comparison of data value across different datasets while maintaining a structured approach to assessment.
3Productivity
If data is captured and held by individual entities, then the entity can exploit the data, but the data cannot be exchanged efficiently across networks
Solution Approach 1:
The patent creates a universal data exchange platform that serves multiple functions: data collection from diverse sources, standardized scoring and valuation, quality certification, and facilitated exchange among various entities. This multi-functional system enables efficient data productivity across networks while preserving data utility through systematic assessment and controlled sharing mechanisms that maintain data integrity and relevance.
Data Source
AI summary
A system and method for valuing a plurality of sets of data and similar medium, comprising receiving datasets, creating a first sub-score for each of the datasets, creating a second numerical sub-score for each of the plurality of datasets, the second numerical value varying based on information characteristics, the second sub-score being larger for improved information characteristics characterized by one or more of increased structural quality, increased completeness, increased interconnectivity, increased diversity, decreased redundancy, creating a third sub-score for each of the plurality of datasets, the third sub-score comprising a third numerical value being larger for improved meaning characteristics characterized by one or more of increased impact on a community, an increased number of impacted communities, greater veracity, greater relevance to an impacted community, greater scarcity; creating a composite score for each of the plurality of datasets that is a mathematical combination of the first, second, and third sub-scores.