Data Importance Assessment in Sharing Platforms
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Solution Overview
Problem
Current data sharing models do not effectively differentiate the importance of user data among various services, leading to equal valuation of all user data, despite some data being more valuable to services than others, which limits user control and potential benefits in data sharing.
Innovation Solution
A data sharing platform that computes an importance metric for user data based on access and usage across multiple sharing services, allowing users to selectively share data and receive appropriate compensation or access to services based on its value.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a data sharing platform allows users to share data with multiple services, then user control and potential benefits are improved, but the complexity of assessing data importance to different services increases
Solution Approach 1:
The patent segments data importance assessment by creating separate importance metrics for each data consumer. The system divides the assessment process into individual evaluations for each service that consumes user data, rather than treating all data equally. This allows the platform to maintain user control while managing complexity through structured, service-specific importance measurements.
Solution Approach 2:
The patent introduces dynamic parameters including data importance scores, consumer demand metrics, and compensation values that change based on service usage and data value. These parameters are continuously updated to reflect current service needs and user preferences, enabling adaptive data sharing decisions without requiring complex manual assessment mechanisms.
2Ease of manufacture
If all user data is valued equally in exchange for service access, then the data sharing model is simple to implement, but it fails to recognize that certain data types are more useful to services than others
Solution Approach 1:
The patent applies local quality by assigning different importance values to different types of data based on their specific utility to various services. Instead of uniform valuation, the system evaluates each data element's importance locally according to the consuming service's needs, preserving accurate data value information while maintaining implementation feasibility through automated assessment.
Solution Approach 2:
The patent implements feedback mechanisms where data importance assessments are continuously refined based on service usage patterns, consumer demand, and user preferences. This feedback loop allows the system to learn and adapt data valuation automatically, maintaining simplicity while avoiding loss of data value differentiation through iterative improvement.
Data Source
AI summary
In one embodiment, a data sharing platform uses data associated with a data owner to share data via a plurality of sharing services, each sharing service in the plurality of sharing services providing a different type of data. The data sharing platform tracks access to each of the plurality of sharing services. The data sharing platform computes, based in part on the access to each of the plurality of sharing services, an importance metric for the data associated with the data owner. The data sharing platform provides an indication of the importance metric for display to the data owner.