Semantic based Data Integration in Scientific Workflows

Abstract

Abstract-Data Integration has become the most prominent aspect of data management applications, especially in scientific domains like ecology, biology, and geosciences. Today's complex scientific applications and the rise of diverse data generating devices in scientific domains (e.g. sensors) have made data integration a challenging task. In response to these types of challenges, data management applications are providing groundbreaking functionalities which come at the price of high complexity. This paper presents a semantic data integration framework which is based on the exploitation of ontologies. Exploiting a Description Logics formalism and associated reasoning procedures, the framework is able the handle heterogeneous formats and different semantics. Besides an indepth discussion of the ontology-based integration capability, the paper also discusses a brief overview of the system architecture and its application in a real world scenario taken from ecological research.