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An approach for semantic integration of heterogeneous data sources
Giuseppe Fusco1, Lerina Aversano1
1Department of Engineering, University of Sannio, Benevento, BN, Italia.
Peerj. Computer Science
|April 5, 2021
Summary
This study introduces a Data Integration Framework (DIF) for unifying diverse data sources. DIF uses ontologies to overcome semantic challenges in data integration, enabling better interoperability.
Area of Science:
- Computer Science
- Information Science
Background:
- Integrating data from multiple heterogeneous sources is challenging due to varying structures and redundancy.
- Data sources are often application-specific, with unknown schemas and incomplete domain information.
Purpose of the Study:
- To present an approach for semantic integration of heterogeneous data sources.
- To introduce a software prototype supporting complex data integration processes.
Main Methods:
- Developed a Data Integration Framework (DIF) as an ontology-based generalization of Global-as-View and Local-as-View approaches.
- Utilized ontologies as a conceptual schema to represent data sources and the global view.
Main Results:
- The proposed approach addresses semantic heterogeneity and enhances interoperability.
- A software prototype was developed to support the data integration process.
Conclusions:
- Ontology-based data integration provides a unified view of heterogeneous data.
- The DIF approach facilitates efficient information extraction and reconciliation from diverse sources.
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