In today’s rapidly evolving technological landscape, digital twins are emerging to understand and manage complex systems, and to help stakeholders make informed decisions. Despite the growing importance of this technology, there is a notable gap in the literature, with little attention devoted to developing effective visualization techniques specifically tailored to digital twins.

To fill this gap, the primary objective of this paper is to conduct a thorough review of existing research, encompassing a diverse range of use cases benefiting from different visualization techniques. This exhaustive survey has enabled visualization techniques to be classified according to data types, specific use cases, interactivity requirements and system complexity. The results can be used by researchers and industry practitioners to better design and implement data visualization interfaces for their developed digital twins, enabling visual analysis and heuristic problem solving using integrated digital twin data.