Providing scientific visualisation for spatial data analysis: criteria and an assessment of SAGE

A consistent theme in recent work on developing exploratory spatial data analysis (ESDA) has been the importance attached to visualization techniques, particularly following the pioneering development of packages such as REGARD by Haslett et al (1990). The focus on visual techniques is often justified in two ways: (a) the power of modern graphical interfaces means that graphics is no longer a way of simply presenting results in the form of maps or graphs, but a tool for the extraction of information from data; (b)graphical, exploratory methods are felt to be more intuitive for non-specialists to use than methods of numerical spatial statistics enabling wider participation in the process of getting data insights. Despite the importance attached to visualisation techniques, very little work has been done to assess the effectiveness of techniques, either in the wider scientific visualisation community, or among those working with spatial data. This paper will describe a theoretical framework for developing visualisation tools for ESDA that incorporates a data model of what the analyst is looking for based on the concepts of "rough" and "smooth" elements of a data set and a theoretical scheme for assessing visual tools. The paper will include examples of appropriate tools and a commentary on the effectiveness of some existing packages