An ontology based approach to automating data integration in scientific workflows

Abstract

Due to the proliferation of data generating devices such as sensors in scientific applications, data integration has become most challenging task since the data stemming from these devices are extremely heterogeneous in terms of structure (schema) and semantics (interpretation). In practice, integration and transformation is typically performed by the scientists manually; in fact extensive efforts are required. The approaches for automating data integration task as much as possible are badly needed. DaltOn is a generic framework that offers various functionalities for managing the data in scientific applications. In this paper, we present DaltOn's functionality for automating data integration task based on exploitation of ontologies. In addition, we also elaborate the specific module of our framework which is responsible for implementing the functionality. At last, we also present core algorithms that demonstrate a good evaluation of our approach.