Ontologies for resolving semantic heterogeneity in information integration among plant phenomics databases

Abstract

Increasing amounts of heterogeneous data are produced every year by plant researchers. For data management relational databases with application-specific schemas are mainly used in this field. However, due to absence of widely shared standards, data integration and exchange between independently developed and heterogeneous databases becomes very challenging. A critical point is to achieve semantic interoperability among these databases. The authors propose to use Semantic Web features for this integration task. Ontologies are the main core of the Semantic Web and are suitable to resolve semantic heterogeneity. In this work a semi-automated ontology based approach is defined for integrating heterogeneous data stored in distributed phenomics databases. The results of a real-world case study show that this approach creates reasonable semantic correspondences between domain-specific databases and publicly available ontologies and can significantly save time compared to classic (specification-driven) engineering approaches.