Knowledge Object Mapping for Data Compliance Without Data Retention
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Solution Overview
Problem
Traditional database metadata and data catalogs restrict the ability to provide information necessary for data compliance tasks, limiting the analysis and enforcement of data privacy and protection requirements.
Innovation Solution
The use of knowledge objects (KOs) to represent and categorize data without retaining the underlying data, allowing for the mapping and analysis of compliance-related information, enabling enterprises to comply with data subject requests and regulatory mandates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional database metadata and data catalogs are used for data compliance tasks, then data structure organization and relational operations are facilitated, but the ability to provide comprehensive compliance information is restricted
Solution Approach 1:
The patent segments compliance information into distinct knowledge objects (KOs) that represent specific data elements, policies, and regulations. Each KO is independently analyzed and mapped, allowing comprehensive compliance coverage without requiring the entire metadata structure to be processed as a single unit. This segmentation enables targeted compliance analysis while maintaining manageable complexity.
Solution Approach 2:
The patent introduces knowledge objects as intermediary entities between traditional database metadata and compliance requirements. These KOs serve as a mediating layer that translates database structures into compliance-relevant information, enabling comprehensive compliance analysis without directly modifying the underlying database metadata complexity.
2Reliability
If underlying data is retained for compliance analysis, then accurate compliance enforcement is achieved, but data security risks increase
Solution Approach 1:
The patent extracts only the essential compliance-related information from the underlying data into knowledge objects, separating this extracted information from the original data. This extraction process retains sufficient detail for accurate compliance enforcement while removing the actual sensitive data, thereby reducing security risks associated with data retention.
Solution Approach 2:
The patent creates simplified copies of data in the form of knowledge objects that contain compliance-relevant attributes without including the actual sensitive data. These KO copies enable compliance analysis and enforcement actions to be performed accurately while the original sensitive data remains protected and is not retained in the compliance system.
Data Source
AI summary
A system receives a plurality of knowledge objects (KOs). The system receives repository structure definition information, the repository structure definition information specifying one or more repository structure definitions that define respective structures for the one or more data repositories. The system groups the plurality of KOs based on the name, type, and tag attributes of the KOs, and storage paths of the underlying unit of structured, semi-structured, and unstructured data at the one or more data repositories corresponding to the KOs to generate a number of groups of KOs. For each group in the groups of KOs, the system determines a count of KOs in the group. The system generates multiple mapping structures with M to N relationships between the groups of KOs to the one or more repository structure definitions, the mapping relationship including the count of associated KOs.