Endowing geographic information systems with a cognitive level

Geographical Information Systems bundle together data of different nature, such as text, images and multimedia. This is because reality is commonly thought as a categorical set of perceivable information -time, space,colours- As a matter of fact we use present information systems for reading the railroad timetable and -in the case of GIS - to realize that our car is lost somewhere on the surface of Earth. At present the problem of higher level layers in Geographic information systems has been tackled by using pictorial languages and data mining techniques.. Recently other models for knowledge representation were proposed such as mathematical concept models or lattice concept (See for example [10]) In this work we point out some problems inherent to picture languages and we propose an alternative knowledge representation model. The advancement of cognitive science has yield some computational models, called "conceptual spaces" (cfr [5], [6]) in which concepts are modelled as a geometric manifold which has evolved inherent to human mind. Each concept is modelled through a partition of flexible surfaces -NURBS- whose control points are prototypical elements.