Data Enrichment for Adaptive Generalisation

This paper presents the research framework for a new project funded by the Swiss National Science Foundation, called DEGEN (Data Enrichment for automated map GENeralisation) which supports two PhD projects. With a focus on thematic cartography (GIS maps, web mapping, location-based services) and the data types prevailing in these map types (polygonal subdivisons, points of interest, etc.), the project aims at developing methods for enriching cartographic databases as well as representing multiscale data of several levels of details (LODs) in multiresolution databases (MRDB). The key working hypothesis is that more adaptive real-time generalisation can be achieved by integrating generalisation methods with MRDB, and particularly by exploiting so-called horizontal and vertical relations. Horizontal relations describe patterns at a particular LOD (e.g. clusters, alignments), while vertical relations are described by links that associate homologous objects or patterns across two or more LODs. The paper reviews the pertinent literature, identifies the research issues and defines the research objectives for the project.