Query Performance Evaluation of Sensor Data Integration Methods for Knowledge Graphs

Gernot Steindl, W. Kastner
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引用次数: 3

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.
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面向知识图谱的传感器数据集成方法查询性能评价
本文介绍了一种基于语义Web技术的智能数据服务,通过增强数据分析能力,为控制工程师在数据驱动模型开发过程中提供支持。作为这种服务的附加条件,由语义元数据和时间序列数据组成的传感器数据必须集成到所谓的知识图中。因此,我们对文献中发现的三种不同的集成方法的查询执行性能进行了评估和比较。讨论了这三种方法的特点和局限性,以确定其具体应用的条件。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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