Semantic Ontology Bridge for Lightweight Data Federation
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Solution Overview
Problem
Current systems face challenges in efficiently federating multiple data sources across different domains without normalizing data, as they require complex query management and often rely on costly data warehousing and extraction processes.
Innovation Solution
The system employs semantic data models to generate electronic configuration, metadata, and domain ontologies, along with bridge ontologies, to enable direct querying of diverse data sources, including non-semantic sources, by converting data into semantic formats and re-hosting it in a triplestore database, allowing for unified querying across multiple domains without data normalization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If complex query management and data warehousing are used to federate multiple data sources, then data federation capability is achieved, but system complexity and cost increase
Solution Approach 1:
The patent introduces a semantic layer with ontologies and a mapping layer as intermediaries between diverse data sources and the federation system. These intermediaries translate and harmonize data from different sources without requiring complex query management or data warehousing, thereby achieving data federation while reducing system complexity
Solution Approach 2:
The patent transforms data from various formats and structures into a unified semantic representation using ontologies. By changing the parameter representation of data into semantic triples and mappings, the system achieves interoperability across diverse data sources without complex integration mechanisms
2Adaptability or versatility
If data is normalized through data warehousing, then data compatibility is improved, but data extraction and processing time increase
Solution Approach 1:
The patent performs preliminary semantic annotation and ontology mapping during data ingestion, creating reusable semantic models and mappings in advance. This preliminary action enables fast querying and federation operations without requiring time-consuming data extraction and normalization at query time
Solution Approach 2:
The patent extracts only the essential semantic meaning and structural relationships from source data into ontology-based representations, leaving the original data intact. This selective extraction of semantic information achieves compatibility without full data normalization, reducing extraction and processing time
3Adaptability or versatility
If data warehousing is used for data federation, then unified data access is achieved, but cost and resource requirements increase
Solution Approach 1:
The patent creates lightweight semantic copies and mappings of data sources rather than physical data warehouses. These semantic models and ontology mappings provide unified data access by representing the structure and meaning of source data without duplicating the actual data volumes, thereby reducing resource requirements
Data Source
AI summary
Systems, methods, and program products for federating a plurality of data sources using semantic data models are disclosed. A configuration ontology may be generated for each data source to identify how to access the data source. Generated metadata ontologies may be generated based upon extracted metadata to specify the data present at each data source. Domain ontologies may be generated for one or more target data environments that comprise a respective lexicon for specifying queries of the plurality of data sources. Bridge ontologies may be generated comprising electronic mappings between each data source and each domain ontology. For each data source that cannot be queried in place, a re-hosted data ontology may be generated by extracting the data and converting it to a corresponding triple data structure based upon the respective bridge ontology and the respective extracted metadata. Queries may then be directed to the plurality of data sources.