 Int’l Journal of Cognitive Informatics and Natural Intelligence, 1(2), -, April-June 2007 Copyright © 2007, Idea Group Inc. Copying or distributing in print or electronic forms without written permission of Idea Group Inc. is prohibited. KNOWLEDGE REPRESENTATION FOR DISTANCES AND ORIENTATIONS OF REGIONS When we open our eyes, we see a snapshot view of the spatial environment. We perceive and describe objects and their spatial relations in the snapshot view, rather than patterns of hues and brightness. A snap- shot spatial environment is decomposed into objects and spatial relations among them. In snapshot views of spatial environments, ob- jects are projectively as large or larger than the body but can be visually apprehended from a single place without appreciable locomotion (Montello, 1993, p. 315). They are vista spa- tial environments following Montello (1993), or the space surrounding the body following (Tversky, 2005; Tversky, Morrison, Franklin, & Bryant, 1999). From snapshot views of spatial envi- ronments, we can recognize objects, describe theirspatial relations, identify whether it is the environment in which we want to enter, even detect object movements. For example, when you have the frst snapshot view of your offce in the morning, you can recognize objects such Knowledge Representation for Distances and Orientations of Regions Tiansi Dong, University of Bremen, Germany ABSTRACT From the perspective of cognitive informatics (CI), this paper proposes internal relations between distance and orientation knowledge of extended objects, and presents a formal representation of spatial knowledge. The connection relation is taken as primitive. Notions of near extension regions and the nearer predicate are developed. Distance relations between extended objects are understood as degrees of the near extension from one object to the other. Orientation relations are understood as distance comparison from one object to the sides of the other object. Therefore, distance and orientation relations can be internally related through the connection relation. The notion of the fat projection is presented to model the mental formation of the deictic orientation reference framework. This paper introduces a new axiom to govern the connection relation in the literature and presents examples to show diagrammatically the internal relations between distance and orientation relations of extended objects. Keywords: data intergration; knowledge classifcation; spatial data IGI PUBLISHING This paper appears in the publication, International Journal of Cognitive Informatics and Natural Intelligence, Volume 1, Issue 2 edited by Yingxu Wang © 2007, IGI Global 701 E. Chocolate Avenue, Suite 200, Hershey PA 17033-1240, USA Tel: 717/533-8845; Fax 717/533-8661; URL-http://www.igi-pub.com ITJ3653