Towards Message-Driven Ontology Population - Facing Challenges in Real-World IoT

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Abstract

Large-scale Internet-of-Things (IoT) environments as being found in critical infrastructures such as Intelligent Transportation Systems (ITS) are characterized by (i) massive heterogeneity of data, (ii) prevalent legacy systems, and (iii) continuous evolution of operational technology. In such environments, the realization of crosscutting services demands a conceptual IoT representation, most promising, in terms of a domain ontology. Populating the ontology’s A-Box, however, faces some challenges, which are not sufficiently addressed by now. In this respect, the contribution of this short paper is three-fold: Firstly, in order to point out the complexity of addressed real-world IoT environments, we identify prevalent challenges for (semi-)automatic ontology population by means of a real world example. Secondly, in order to address these challenges, we elaborate on related work by identifying promising lines of research relevant for ontology population. Thirdly, based thereupon, we sketch out a solution approach towards message-driven ontology population.

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Graf, D., Schwinger, W., Kapsammer, E., Retschitzegger, W., Pröll, B., & Baumgartner, N. (2020). Towards Message-Driven Ontology Population - Facing Challenges in Real-World IoT. In Advances in Intelligent Systems and Computing (Vol. 1159 AISC, pp. 361–368). Springer. https://doi.org/10.1007/978-3-030-45688-7_37

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