An Architecture and Information Meta-model for Back-end Data Access via Digital Twins

S. Malakuti, Prerna Juhlin, Jens Doppelhamer, Johannes O. Schmitt, Thomas Goldschmidt, Aleksander Ciepal
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引用次数: 4

Abstract

The lifecycle data of industrial devices is typically maintained in separate data sources operating in silos. The lack of interoperability between the data sources due to the usage of different APIs, data formats and data models results in time-consuming and error-prone manual data exchange efforts. The notion of digital twins is known to be a solution to the data silo problem and the associated interoperability issues. Despite many studies on digital twins, there is still a need for common architectures that offer means for defining digital twins, ingesting backend data in the digital twins, and enabling interoperable data exchange across the lifecycle of the devices via their digital twins. This paper aims to close this gap by proposing a cloud-based architecture, a common information meta-model for defining the digital twins, and variety of APIs to query the lifecycle data of interest via the digital twins.
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基于数字孪生的后端数据访问的体系结构和信息元模型
工业设备的生命周期数据通常维护在孤岛中运行的独立数据源中。由于使用不同的api、数据格式和数据模型,数据源之间缺乏互操作性,导致人工数据交换工作耗时且容易出错。众所周知,数字孪生的概念是数据孤岛问题和相关互操作性问题的解决方案。尽管对数字孪生进行了许多研究,但仍然需要通用架构来提供定义数字孪生的方法,在数字孪生中摄取后端数据,并通过其数字孪生在设备的整个生命周期中实现可互操作的数据交换。本文旨在通过提出基于云的架构、用于定义数字孪生的通用信息元模型以及通过数字孪生查询感兴趣的生命周期数据的各种api来缩小这一差距。
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