In today’s fast-evolving technological landscape, digital twins are emerging for understanding and managing complex systems and to assist stakeholders in the process of informed decision-making. Despite the growing importance of this technology, there exists a noticeable gap in the literature, with limited attention devoted to crafting effective visualization techniques tailored specifically to digital twins. To rectify this gap, this paper’s primary objective is to conduct a thorough examination of existing research, encompassing a diverse array of use cases benefiting from various visualization techniques. This comprehensive inquiry has led to the categorization of visualization techniques based on data types, specific use cases, interactivity requirements, and system complexity. The outcomes can be used by researchers and industry practitioners to better design and implement data visualization interfaces for their developed digital twins, allowing visual analytics and heuristic problem solving using integrated data of digital twins.