Fact Repository Rule Engine for Data Quality
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Solution Overview
Problem
Existing data collection and organization systems face challenges in detecting errors, particularly when dealing with untrustworthy sources and nonstandard information organization, leading to inconsistencies in fact databases.
Innovation Solution
A method and system that utilize a rule creation engine to identify correlations between object types and fact attributes, applying rules to modify objects and improve data quality by storing groomed objects in a repository, thereby enhancing the accuracy and consistency of facts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated data collection and organization is used, then productivity is improved, but measurement precision deteriorates due to errors from untrustworthy sources and nonstandard information organization
Solution Approach 1:
The system applies feedback by using metadata from groomed objects to generate rules that automatically correct and validate facts in the repository. The rule creation engine analyzes patterns in accurately groomed objects and generates validation rules that feed back into the fact correction process, continuously improving data quality without manual intervention.
Solution Approach 2:
The system implements self-service through automated rule application where the repository system itself performs fact correction and validation. The rule application engine automatically applies generated rules to facts, and the system self-adjusts based on metadata patterns, eliminating the need for manual human verification of each fact.
2Measurement precision
If manual verification of facts is performed, then measurement precision is improved, but productivity deteriorates due to time-consuming verification processes
Solution Approach 1:
The system performs self-service by automatically generating and applying rules to verify and correct facts. The rule creation engine analyzes metadata patterns and generates validation rules that the rule application engine executes automatically, replacing manual human verification with automated system-level processing that maintains high accuracy while processing data at machine speed.
Solution Approach 2:
The patent replaces the mechanical manual verification process with an automated computational system. The rule creation and application engines use algorithms to analyze metadata, generate rules, and apply corrections automatically, substituting human cognitive processing with machine-based automated reasoning and pattern recognition.
3Manufacturing precision
If rules are applied to modify objects, then manufacturing precision is improved for data consistency, but device complexity increases due to rule creation and application engines
Solution Approach 1:
The system achieves self-service by having the repository automatically generate and apply its own validation rules. The rule creation engine analyzes metadata from groomed objects and generates rules that the rule application engine executes automatically, allowing the system to self-validate and self-correct without external intervention, thereby managing complexity through automation.
Solution Approach 2:
The system uses feedback mechanisms where metadata from successfully groomed objects feeds back into rule generation. The rule creation engine continuously learns from the repository's metadata patterns and generates updated validation rules, creating a feedback loop that adapts the system's validation logic to maintain high data consistency while managing complexity through intelligent automation.
Data Source
AI summary
Metadata is used to determine rules that can be applied to facts. In one embodiment, correlations are identified among types of objects and the attributes of the facts associated with those objects. In another embodiment, correlations are identified among types of objects, the attributes of the facts associated with the objects, and the format and/or range of the values of the facts having those attributes. When a correlation exists between objects of a given type and the attributes of the facts associated with objects of that type, a rule is created for objects of that type. The rule is applied to objects of the given type.