The Spatiograph: A Classification Framework for Geospatial Representations

Abstract

Geospatial Information Technology (GIT) is being used in an increasing number of application fields and is relevant for more users than ever before. This diversity of applications and users raise questions about the relevance of different types of georepresentation (such as, maps, aerial photos, satellite imagery, 3D models) and their congruency with different user profiles. Studies have shown that the convergence and divergence of georepresentations between individuals are potential sources of alliance and conflict in organizations, especially during GIT development projects. For a better understanding of the interactions between users, technologies and georepresentations, we need to reach a deeper understanding of each of these elements. More specifically, it remains difficult to understand and describe geo-representations, both cognitive and physical, in a synthetic and practical manner. Many studies suggested classification frameworks of georepresentations, but to our knowledge, none of them have been designed to present the different geo-representations used in an organization. Based on previous studies, we conducted this research in order to build a global and practical classification framework of georepresentations. We attained this goal through a survey, as well as quantitative and qualitative analyses. This paper presents the methodology and the results of this research project: a practical classification framework called Spatiograph. This quantitative study made it possible to conduct exploratory analyses that will define, in a later stage, the Spatiograph as a classification tool on a large scale and to validate it in various domains. The paper concludes with a few examples of visual analyses that may be conducted with the Spatiograph.