Personal Data Portability via Mediator and Segmentation
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Solution Overview
Problem
Users face challenges in controlling and accessing their personal data spread across various environments, lacking control over large portions of their data and often not having access to it.
Innovation Solution
A system with a processor and memory configured to initiate data retrieval from a personal data store, organizing and decoupling data types to facilitate portability across environments, using a core data porting engine with templates for configuring data stores and agents to control data transfer.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If personal data is stored across multiple different entities and environments, then data availability and diversity are improved, but user control and data accessibility are worsened
Solution Approach 1:
The patent introduces a personal data store as an intermediary component that sits between the user and multiple data environments. This mediator consolidates access to personal data across different entities and environments, allowing users to control and access their data through a single interface rather than navigating multiple separate systems.
Solution Approach 2:
The patent segments personal data into distinct data types (e.g., personal information, financial information, health information) and organizes them within the personal data store. This segmentation allows for granular control over different categories of data while maintaining centralized management, resolving the contradiction between data diversity and user control.
2Adaptability or versatility
If personal data is stored across multiple different entities and environments, then data diversity is improved, but data accessibility is worsened
Solution Approach 1:
The personal data store is designed as a universal system that can handle multiple types of personal data from various sources (different entities and environments) through a common interface. This multi-functional approach allows the system to maintain data diversity while providing unified access, eliminating the need for users to interact with each environment separately.
Solution Approach 2:
The personal data store acts as a mediator that aggregates data from multiple environments and presents it through a single access point. This intermediary layer maintains the diversity of data sources while simplifying accessibility, allowing users to retrieve personal data regardless of its original environment.
3Adaptability or versatility
If data types are used to decouple personal data from associated environments, then data portability is improved, but system complexity is worsened
Solution Approach 1:
The patent applies parameter changes by defining and standardizing data types as specific parameters that describe personal data independently of its source environment. By changing the representation of data from environment-specific formats to standardized data type parameters, the system achieves portability while managing complexity through consistent parameter definitions.
Solution Approach 2:
The patent segments personal data into distinct data types (personal information, financial information, health information, etc.), separating the data content from its environmental context. This segmentation enables portability by allowing data to be identified and transferred based on type rather than source, while organizing complexity into manageable categorical groups.
Data Source
AI summary
A universal personal data portability capability is disclosed. The universal personal data portability supports automated porting of personal data of a user from a plurality of environments to a personal data store of the user.