The emerging new technologies such as AI/machine learning, cloud/mobile computing, and big data analytics have triggered a new wave of digital transformation for the public sector including NMAs. These new technologies, which are pervasively sensed in scientific labs and in smartphones, add further incentives to deal with some long-standing mapping issues as automatic map generalization. More importantly, there is a massive amount of geospatial big data emerging from the Internet or social media, such as OpenStreetMap data and massive Tweet locations. The importance of the emerging big data has been well recognized for updating conventional geodatabases. There is an increasing need for new types of maps and services from the society and users in a mobile/cloud environment. Conventional geodatabases are gathered largely for the purpose of producing paper maps or showing on computer screens rather than in a cloud/mobile environment. From the large-size paper maps or screen maps to phone-size maps, there is an issue of visualization and generalization. In the current cloud/mobile environment, there is an incentive to develop more personalized maps for individual mobile users or the society as a whole. In this connection, the above-mentioned new technologies, particularly AI/machine learning, will help develop solutions to the new maps or new ways of mapping.

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