RIA: Formalization, Inference, and Query Processing of Spatial Relations in Geographic Space Scientists and engineers using geographic databases need query languages with powerful spatial selection methods and capabilities to infer spatial information in a manner similar to a human expert. Crucial for geographic databases and geographic information systems (GISs), containing very large amounts of spatial data, are appropriate operators to access and manipulate spatial data in large-scale, geographic space, far beyond what is currently being offered by traditional database management systems. The objective of the investigations is to construct a coherent reasoning system that integrates spatial concepts about topology, cardinal directions, and approximate distances so that they can serve as a spatial extension to geographic databases and query languages. The reasoning system focuses on large-scale, geographic space. The hypothesis is that powerful and complex spatial reasoning can be formalized as the product of the interaction between relatively simple spatial relations with specific inference rules. Individual spatial relations about topology, distance, and direction are formalized and integrated into a comprehensive system, adding more power through the coexistence of the different relationships in a single system. The major result will be a set of primitives, with rules describing their combinations, for the design of domain specific query languages for GISs.