Paleogeographic reconstruction is a comprehensive study ofthe surface tectonic processes, the sea- land pattern, and geomorphic environmental characteristics in geological history. This field is represented by the creation of maps that depict the ancient contours of oceans and continents, as well as important topographic and surface environment characteristics. It serves as a fundamental process for restoring Earths evolutionary history, predicting the distribution of energy and mineral resources, and understanding life and climate evolution. The advent of the era of big data has facilitated the application of digital methods in updating and presenting paleogeographic maps in a rapid and user- friendly manner. Currently, several teams worldwide have published digital global paleogeographic reconstruction models and related data and methods, including Earthbyte, PaleoMap, UNIL, Deep- Time Maps, and other teams. Building upon the concept of data- knowledge- model- driven paleogeography reconstruction proposed by the Deep- time Digital Earth (DDE) International Science Program, this study summarizes and presents a new process for updating global paleogeography maps driven by digital methods. Moreover, through continuous efforts to integrate geoscience and information science, several application technologies for paleogeography reconstruction have been developed, encompassing knowledge mapping, big data analysis, and machine learning. As an example, the Permian- Middle Triassic paleogeography reconstruction in the East Tethys domain is considered. The research team reconstructed the plate tectonic framework using a GPlates software platform and employed lithofacies paleogeography maps to automatically generate topographic and geomorphic maps with manual correction. Ultimately, a dynamic digital comprehensive paleogeography reconstruction of the Middle Permian- Middle Triassic East Tethys domain was formed through layer superposition in GPlates. In comparison to the widely used Scotese (2021)s paleogeographic map, this use case significantly enhances mapping efficiency, data abundance, traceability, and model accuracy. Additionally, it offers new constraints and insights for studying major geological events such as plate movements, ice age extinctions, ocean anoxia, and biological mass extinctions during this period.