Knowledge-Based Recommendation for On-Demand Mapping: Application to Nautical Charts

Abstract

Maps have long been seen as a single cartographic product for different uses, with the user having to adapt their interpretation to his or her own needs. On-demand mapping reverses this paradigm in that it is the map that adapts to the user’s needs and context of use. Still often manual and reserved for professionals, on-demand mapping is evolving toward an automation of its processes and a democratization of its use. An on-demand mapping service is a chain of several consecutive steps leading to a target map that precisely meets the needs and requirements of a user. This article addresses the issue of selecting relevant thematic layers with a specific context of use. We propose a knowledge-based recommendation approach that aims to guide a cartographer through the process of map-making. Our system is based on high- and low-level ontologies, the latter modeling the concepts specific to different types of maps targeted. By focusing on maritime maps, we address the representation of knowledge in this context of use, where recommendations rely on axiomatic and rule-based reasoning. For this purpose, we choose description logics as a formalism for knowledge representation in order to make cartographic knowledge machine readable.