Data arrangement using techniques like ontology and semantic design plays a crucial role in the design of digital twins. By employing ontology, which represents knowledge about entities and their relationships in a specific domain, data can be structured and organized in a meaningful way. This allows for effective integration and interoperability between various data sources, enabling a comprehensive representation of the physical system being modeled. Semantic design further enhances this process by adding contextual information and defining relationships based on the semantics of the data. This enables accurate interpretation and analysis of data, facilitating advanced functionalities such as predictive modelling, real-time monitoring, and decision-making in the digital twin environment. Overall, a well-organized data arrangement leveraging ontology and semantic design ensures that the digital twin accurately reflects the physical system and supports its simulation, analysis, and optimization with greater efficiency and reliability.