In the world of the Internet of Things (IoT), heterogeneous systems and devices need to be connected and exchange data with others. How data exchange can be automatically realized becomes a critical issue. An information model (IM) is frequently adopted and utilized to solve the data interoperability problem. Meanwhile, as IoT systems and devices can have different IMs with different modeling methodologies and formats such as UML, IEC 61360, etc., automated data interoperability based on various IMs is recognized as an urgent problem. In this paper, we propose an approach to automate the data interoperability, i.e. data exchange among similar entities in different IMs. First, similarity scores among entities are calculated based on their syntactic and semantic features. Then, in order to precisely get similar candidates to exchange data, a concept of class distance calculated with a Virtual Distance Graph (VDG) is proposed to narrow down obtained similar properties for data exchange. Through analyzing the results of a case study, the class distance based on VDG can effectively improve the precisions of calculated similar properties. Furthermore, data exchange rules can be generated automatically. The results reveal that the approach of this research can efficiently contribute to resolving the data interoperability problem.

中文翻译：

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应用类距离来确定信息模型的相似性以实现自动化数据互操作性

在物联网 (IoT) 的世界中，异构系统和设备需要连接并与他人交换数据。如何自动实现数据交换成为一个关键问题。信息模型（IM）经常被采用和利用来解决数据互操作性问题。同时，由于物联网系统和设备可以有不同的IM，具有不同的建模方法和格式，如UML、IEC 61360等，基于各种IM的自动化数据互操作性被认为是一个紧迫的问题。在本文中，我们提出了一种自动化数据互操作性的方法，即不同 IM 中相似实体之间的数据交换。首先，实体之间的相似度分数是根据它们的句法和语义特征计算的。然后，为了精确地得到相似的候选人来交换数据，提出了使用虚拟距离图（VDG）计算的类距离的概念，以缩小获得的相似属性以进行数据交换。通过对案例研究结果的分析，基于VDG的类距离可以有效提高计算相似属性的精度。此外，可以自动生成数据交换规则。结果表明，本研究的方法可以有效地解决数据互操作性问题。