Ontology based data integration for an Internet of Things (IoT) ecosystem to support the collaborative research

Abstract

Advances in data-driven technologies, provoked a data deluge of scientific information. Motivated by the analysis and handling of large amounts of data, the electronic facilitation of science, or eScience, emerged as a new science paradigm and has been employed as a complementary technique to the scientific method. The Internet-of-Things (IoT), as a datadriven technology, has been used as a source of data in the eScience context. However, due to the decentralized nature of IoT networks, IoT data is highly heterogeneous, hindering the collection of comprehensible information. This study strived to elaborate a data integration solution for the context of IoT. The challenge of integrating heterogenous data was seen as knowledge representation issue, where it is made necessary to stress relationships between the data sources to be integrated and the integration thereof. Hence, ontologies step in as a set of description logics that allow the modelling, cleansing, standardization, and the integration of data. In this way, the proposed solution was constituted by an ontology-based data integration solution for IoT data sources. In addition, aiming to promote eScience, a collaborative research environment was implemented in a scientific software ecosystem platform, which also implements the IoT data integration solution—composing an IoT ecosystem.