Ontology Validation for Consistent Shared-Database Data Communication
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Solution Overview
Problem
Existing systems fail to ensure consistent and error-free communication of datasets between multiple parties, leading to potential downstream system crashes or errors due to non-conformant data objects being propagated to shared databases.
Innovation Solution
Implementing a core ontology with defined constraints and an ontology application to validate and enforce data consistency, ensuring datasets conform to the core ontology before storage in a shared database, with the ability to automatically fix non-compliant data items and prevent propagation of errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If datasets are communicated freely between parties without validation, then data communication speed and ease of operation are improved, but data consistency and system reliability deteriorate due to non-conformant data objects being propagated
Solution Approach 1:
The patent introduces an intermediary validation layer (ontology application and core ontology) between data producers and data consumers. This intermediary automatically validates datasets against predefined schemas, constraints, and data models before propagation, ensuring data consistency without requiring manual intervention from parties. The intermediary resolves the contradiction by maintaining ease of communication while enforcing reliability through automated validation mechanisms.
Solution Approach 2:
The patent implements preliminary validation actions by establishing core ontologies, data models, and constraints before data communication occurs. Parties must adhere to predefined schemas and data quality rules in advance, preventing non-conformant data from being propagated. This preliminary action ensures data consistency is maintained from the outset, resolving the reliability issue while preserving communication efficiency.
2Reliability
If data validation and constraint enforcement are implemented, then data consistency and reliability are improved, but system complexity and processing time increase
Solution Approach 1:
The patent creates a universal core ontology and data model framework that serves multiple parties and purposes simultaneously. The same validation rules, constraints, and schemas are reused across different data communication scenarios and parties, reducing the need for separate validation systems for each case. This universality reduces overall system complexity while maintaining comprehensive data consistency enforcement.
Solution Approach 2:
The patent enables datasets to self-validate against predefined ontologies and constraints through automated validation mechanisms. The system performs self-checks on data conformity, identifying and flagging non-conformant data objects without requiring external manual validation. This self-service approach reduces the complexity of manual validation processes while ensuring reliable data consistency.
3Measurement precision
If manual validation of datasets is performed, then data accuracy is improved, but processing speed and productivity decrease
Solution Approach 1:
The patent replaces manual mechanical validation processes with automated computational validation systems. The ontology application and validation engine automatically check datasets against predefined schemas, constraints, and data models, performing validation at machine speed rather than human speed. This substitution maintains high data accuracy through comprehensive validation while dramatically improving processing speed and productivity.
Solution Approach 2:
The patent implements continuous automated validation that operates throughout the entire data communication process without interruption. Validation occurs automatically as data is produced, transmitted, and consumed, maintaining constant verification of data accuracy. This continuous action ensures high data precision while improving overall productivity by eliminating pauses for manual validation checks.
Data Source
AI summary
A method, performed by one or more processors, is disclosed, comprising providing, to a plurality of parties permitted to communicate data via a shared database, an ontology application associated with a common core ontology, the core ontology defining constraints required to be met for producing, from one or more received datasets, one or more data objects for storing in the shared database. The ontology application may be configured to receive one or more datasets from one or more parties and to use the core database ontology to determine if the received one or more datasets conform to the constraints of the core ontology, and store the received one or more datasets as data objects in the shared database, conditional on the constraints being met.