Entity Identification via Distributed Identifier Tuples
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Solution Overview
Problem
Current relational database systems face challenges in tracking relationships between entities without globally unique identifiers, leading to constraints on data sharing and management, especially when new information arises about entity identities, requiring manual and time-consuming processes for merging or splitting entities.
Innovation Solution
The approach eliminates the need for a single central database by using tuples of entity identifiers within local data stores, allowing entities to be identified and verified through multiple sources, with each data store maintaining ownership and provenance, and enabling local computation of identifiers for accessing relevant information without central identifier assignment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a single central database is used to track relationships between entities, then data consistency and global identification are improved, but device complexity and loss of information occur when new information arises about entity identities
Solution Approach 1:
The patent divides the centralized identification system into distributed local data stores, each maintaining its own tuples of identifiers. This segmentation eliminates the single central database while maintaining data consistency through local tuple relationships, resolving the contradiction between reliability and device complexity.
Solution Approach 2:
The patent introduces tuples as intermediary structures that link identifiers from different data sources. These tuples act as mediators that maintain relationships between entities without requiring a central database, allowing data consistency to be preserved through local tuple references rather than central authority.
2Reliability
If manual processes are used for merging or splitting entities, then data integrity is maintained, but loss of time and reduced productivity occur
Solution Approach 1:
The system enables automated self-service for entity identification through local computation. Each data store can independently compute and verify identifier matches using local tuples, eliminating the need for manual merging or splitting operations while maintaining data integrity through automated verification processes.
3Ease of operation
If local data stores maintain ownership of identifiers, then ease of operation and data security are improved, but loss of information may occur during data sharing
Solution Approach 1:
The patent merges data from multiple local data stores by creating tuples that reference identifiers across different stores. This combining approach allows each data store to maintain ownership and control over its identifiers while enabling comprehensive data sharing through the shared tuple structure, resolving the contradiction between ease of operation and information completeness.
Data Source
AI summary
Exemplary embodiments of the present disclosure provide a method, apparatus, and computer-readable medium for identifying. An exemplary method includes providing a plurality of identifiers from a plurality of data sources, the plurality of identifiers corresponding to a plurality of entities, and creating a plurality of tuples based on the plurality of identifiers, wherein each one of the plurality of tuples corresponds (i) a particular one of the plurality of data sources and (ii) to at least two identifiers that are linked together. The method further includes receiving an identifier, and determining whether the received identifier matches any of the plurality of tuples.