Inferring Implicit Data from Relational Schema
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Solution Overview
Problem
Current computer systems lack the ability to persist and utilize implicit information outside of the runtime of a software application, limiting their functionality and compliance with data protection regulations like GDPR, which require access to all personal data of a data subject, including both explicit and implicit information.
Innovation Solution
A computer system is configured to infer implicit information using a schema of a database, identifying relationships between records in different tables to determine implicit information based on the lack of links between explicit data stored in one table and records in another, allowing the use of this information outside the application's runtime for reporting and other processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If implicit information is only processed within application runtime, then processing speed is improved, but data accessibility and system functionality are worsened
Solution Approach 1:
The patent extracts implicit information from the application runtime environment and stores it in persistent storage systems. This allows the information to be accessed outside the original application context, resolving the contradiction by separating the information extraction process from the application runtime while maintaining processing efficiency.
Solution Approach 2:
The system performs preliminary inference of implicit information during application execution and stores it in advance in persistent storage. This preliminary action ensures that the information is readily available when needed later, improving both accessibility and maintaining processing speed by avoiding redundant inference operations.
2Adaptability or versatility
If implicit information is persisted in storage, then data accessibility is improved, but storage complexity and system complexity are worsened
Solution Approach 1:
The patent implements a universal data storage schema that can accommodate both explicit and implicit information using the same database structure. This multi-functional approach allows the system to store different types of data uniformly, improving accessibility without proportionally increasing system complexity.
Solution Approach 2:
The system introduces an intermediary layer (the persistent storage system with standardized schema) between the application and the implicit information. This intermediary handles the complexity of information persistence and retrieval, shielding the application from complexity while providing improved data accessibility.
3Reliability
If all personal data including implicit information is accessed, then compliance with data protection regulations is improved, but data processing time and system resource usage are worsened
Solution Approach 1:
The system performs preliminary inference and storage of implicit information during normal application operation. When compliance requests occur, the pre-computed implicit information is already available in persistent storage, eliminating the need for time-consuming real-time inference and reducing data processing time while maintaining full compliance.
Solution Approach 2:
The patent prepares implicit information in advance and stores it in a compliant format, creating a buffer that protects against future compliance requests. This beforehand cushioning ensures that when compliance audits or data access requests occur, the system can respond immediately without extensive processing, thus maintaining reliability while minimizing time loss.
Data Source
AI summary
Techniques for accessing implicit information that is used by, but not explicitly persisted in, a computer system are disclosed. In some embodiments, a method comprises: storing a schema for a relational database, the schema indicating relationships between tables of the relational database; persisting explicit data concerning a data subject in at least one of the tables; processing the explicit data using a software application, the processing of the explicit data comprising: inferring implicit information based on the explicit data and the schema; and using the implicit information by the software application; receiving a request for a report of personal data concerning the data subject; and in response to the request, generating the report, the generating of the report comprising: inferring the implicit information based on the explicit data and the schema; and including the explicit data and the implicit information in the generated report.