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Query Performance Evaluation of Sensor Data Integration Methods for Knowledge Graphs

机译:知识图传感器数据集成方法的查询性能评估

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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.
机译:本文介绍了一种基于语义Web技术的智能数据服务,该服务通过启用增强的数据分析在数据驱动的模型开发过程中为控制工程师提供支持。为了获得这样的服务,必须将由语义元数据以及时间序列数据组成的传感器数据集成到所谓的知识图中。因此,对文献中发现的三种不同的集成方法进行了评估,并就其查询执行性能进行了比较。讨论了这三种方法的特征和局限性,以指定其特定使用条件。

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