Modeling temporal information in cultural heritage knowledge graphs is essential to understand history, society and the world. However, due to the binary nature of RDF predicates, representing time in RDF is a challenge. This work addresses the challenge and explores various approaches for integrating time into knowledge graphs. In particular, the work aims at answering key research questions, such as best practices for temporal representation in RDF, crucial requirements in the cultural heritage context, and evaluating RDF extensions for modeling time. Additionally, it is investigated how RDF can reason over temporal relationships and how the new insights can be used to develop a lightweight and intuitive approach for modeling time in RDF based on domain requirements. Fundamentally, the research argues for embracing the persistence of temporality in KGs, as it is crucial for understanding our changing heritage, recognising the influence of the past on the present, and shaping a knowledgeable future.