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Digital Twin technology has emerged as a pivotal tool in digital transformation, offering virtual representations of physical components, systems, or processes to enable remote monitoring and control. The functional suitability of digital twin systems relies on accurately capturing, modeling, and exchanging data from their corresponding assets or processes. Consequently, achieving interoperability among various components of digital twins and among different digital twins is crucial. However, this remains an open challenge due to the diversity of data models employed by current digital twin solutions. This thesis proposal addresses this challenge by proposing a model-driven engineering approach, utilizing higher-order transformations alongside the Asset Administration Shell standard as a pivotal model. The approach aims to automate translations to and from the Asset Administration Shell standard, eliminating manual crafting of model transformations.