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Utilizing ER Model Extraction for an Industry Data Validation Use Case
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AI
DOI：10.1007/978-3-032-06878-1_14.png)
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Abstract
En 中文
In order to enable domain experts to perform data integration independently, we present a method which involves data integration based on Entity-Relationship (ER) models that are semi-automatically extracted from various data sources. We propose strategies to extract ER models from standard data sources such as relational databases, XML files, and OWL data, with a concept to extend this extraction to other data sources. In case the automatic extraction yields insufficient results, we present an enhancement approach that allows the user to manually adjust the generated ER model. The extracted models support data integration into an ontology-based model, contributing to harmonized knowledge management in heterogeneous data environments. A graphical visualization of the ER models is introduced that allows to review and enhance the extracted models. Moreover, we present exemplarily an industry use case of an extracted model that serves as a foundation for data validation of power grid models. An ER model-based data integration paves the way for FAIR energy data.
Keywords:
Entity relationship model
Model extraction
Data integration
Structural metadata
FAIR principles
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Papers:
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