An attention to location, spatial interaction, spatial structure and spatial processes lies at the heart of research in several subdisciplines in the social sciences. Empirical studies in these fields routinely employ data for which locational attributes (the "where") are an important source of information. Such data typically consist of one or a few crosssections of observations for either micro-units, such as households, store sites, settlements, or for aggregate spatial units, such as electoral districts, counties, states or even countries. Observations such as these, for which the absolute location and/or relative positioning (spatial arrangement) is taken into account are referred to as spatial data. This paper reviews the linkage between spatial data analysis in the social sciences and GIS. Simply put, the power of a GIS as an aid in spatial data analysis lies in its georelational data base structure, i.e., in the combination of value information and locational information. The link between these two allows for the fast computation of various characteristics of the spatial arrangement of the data, such as the contiguity structure between observations, which are essential inputs into spatial data analysis.