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Data-driven Aspects of Engineering The Use of Operational Data in SoS Engineering: Chances and Challenges

机译:工程的数据驱动方面在SoS工程中使用操作数据:机遇与挑战

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System of systems engineering moves towards the realization of smart systems. Information and its underlying data forms the backbone for such cyber-physical systems, especially within the application domains of the internet of things and of infrastructure systems of systems. Data therefore becomes a key component within system engineering. In this context, the rise of applied data science allows for novel uses of systems' operational data for engineering purposes. We recognize several areas for which data-driven approaches yield promising results, but also identify challenges that render success difficult. These challenges, i.e., data sparsity, the skewness of statistical distributions w.r.t. relevant objects and the semantics of the context of systems, are in parts known to the data science community, but require an appropriate interpretation for engineering purposes. In our own work, we rely on existing domain knowledge to complement data driven aspects of system of systems engineering within a modelbased approach to address these and similar challenges.
机译:系统工程系统趋向于实现智能系统。信息及其底层数据构成了此类网络物理系统的骨干,尤其是在物联网和系统基础架构系统的应用领域内。因此,数据成为系统工程中的关键组成部分。在这种情况下,应用数据科学的兴起允许将系统操作数据用于工程目的的新颖用途。我们认识到数据驱动的方法可以在某些领域取得可喜的成果,但同时也要找出使成功变得困难的挑战。这些挑战,即数据稀疏性,统计分布的歪曲性相关对象和系统上下文的语义在某些方面是数据科学界已知的,但出于工程目的需要适当的解释。在我们自己的工作中,我们依靠现有的领域知识以一种基于模型的方法来补充系统工程系统的数据驱动方面,以应对这些挑战和类似挑战。

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