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Talks and Poster Presentations (with Proceedings-Entry):

G. Steindl, W. Kastner:
"Query Performance Evaluation of Sensor Data Integration Methods for Knowledge Graphs";
Talk: 6th IEEE International Conference on Big Data, Knowledge and Control Systems Engineering, Sofia, Bulgarien; 2019-11-21 - 2019-11-22; in: "Proceedings of the 6th IEEE International Conference on Big Data, Knowledge and Control Systems Engineering", (2019).



English abstract:
In this paper, a Smart Data Service, based on Semantic Web technology is introduced, which supports the control engineer during the data-driven model development process by enabling enhanced data analysis. As a perquisite for such a service, sensor data consisting of semantic meta data as well as time series data have to be integrated into a so-called knowledge graph. Therefore, three different integration approaches, found in the literature, were evaluated and compared regarding their query execution performance. The characteristics and limitations of these three methods are discussed to specify the conditions for their specific utilization.

Keywords:
semantic sensor networks, ontology, time series data, linked data


Related Projects:
Project Head Wolfgang Kastner:
BIM4BEMS


Created from the Publication Database of the Vienna University of Technology.