Query Performance Evaluation of Sensor Data Integration Methods for Knowledge Graphs

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.