The project is situated in the domain of geographic information systems (GIS) and digital cartography. Map generalization (short: generalization) is a key function in digital cartography and GIS, needed for a variety of tasks such as the creation and maintenance of geospatial databases at multiple scales, cartographic visualization at variable scales, and controlled data reduction. More specifically, this project will focus on generalization for web and wireless (or mobile) mapping on small, portable end user devices. Hence, we will pay attention to the gradual evolution of GIS and cartography towards the mobile context. Two PhD projects are pursued, linked by a common vision and building on a common service-oriented software architecture and test database.The first subproject will focus on the integration and management of heterogeneous geospatial information in multiple representation databases (MRDBs). In MRDBs geospatial data are organized in several levels of detail (LODs) in order to support the rendering of maps at the appropriate scale and detail. Geospatial software applications in the mobile context, such as location-based services (LBS), typically make use of highly heterogeneous datasets that originate from very different sources, have different levels of accuracy, different temporal validity, and often involve fuzzy spatial delineations. This subproject therefore seeks to develop new MRDB data models capable of accommodating highly heterogeneous data; new methods for integration of such data into MRDBs; and new methods for information reduction and schematization to harmonize and pre-generalize heterogeneous datasets.While the first subproject will primarily concentrate on the off-line phase of mobile applications that takes place before actual information requests are made to the system, the second subproject will mainly focus on the on-line phase. This subproject will study how generalization operations for web and mobile devices can be made sufficiently fast so that the information portrayal can take place in real-time, and so that the scale and content of the map display can be flexibly and instantaneously adapted to the information requests and the context of a web or mobile user. In particular, we seek to propose and experiment with simplified map designs that allow to derive more powerful computational heuristics for on-the-fly map generalization; develop generalization algorithms for point, line and polygon data that exploit the new heuristics; and develop improved methods for real-time portrayal of points of interest (POIs), including icon placement and resolution of symbol overlaps.