Semantically Enabling Map Projections Knowledge

Abstract

Map projections are an area of cartography with a firm mathematical foundation for their creation and display provid ing a basis for a knowledge representation. Using only variations on a single equation set, an infin ite number of projections can be created, but less than 1 00 are in active use. Because each projection preserves specific characteristics, such as area, angles, global look, or a compromise of properties, classifications of map projections have been developed to aid in knowledge representation. These classifications are used for decision-making. They help select the correct projection for the map use. They assist users with determining the correct orientation, standard paral lels and merid ians. The classifications also inform the user how to adjust the selection based on size, extent, and latitude. Semantics can be used to automate map projections knowledge into a knowledge base that can be accessed by humans and machines. This work detai ls a semantic representation of map projections knowledge and provides a simple example of a use case that exploits the knowledge base.