By Esri Social Science Collaborative (Jennifer Mendez, Diana Lavery, Kyle Jones, Lakeisha Coleman, Lain Graham)

Many people understand the power of GIS for quantitative research, but fewer know of its practical applications for qualitative social science work. In a broad effort led by Esri’s Chief Scientist, Dawn Wright, Ph.D., a number of researchers at Esri  are looking at the many ways qualitative social science can benefit from GIS. While ArcGIS can help with an array of quantitative approaches, it also brings many capabilities to enhance qualitative methodologies to address longstanding issues of social and environmental concern.  This article explores where and how common GIS approaches and common qualitative approaches intersect and provides resources for learning more.

Starting with Data

To begin understanding what GIS can do for qualitative social science, we first define what we mean by qualitative, quantitative and spatial data. Table 1 below provides a brief summary. It’s important to note is that although spatial data is distinct, it can be combined to transform other types of data to become spatialized. That is, both quantitative and qualitative data can be combined with spatial data to associate shape, size, location, and other spatial information. For example, when a researcher collects attitudinal data in several neighborhood planning units, she can associate location information with each survey response. This spatialization of resident feedback would enable her to find additional patterns for analysis and comparison between neighborhoods.

Comparison of the characteristics of qualitative data, quantitative data, and spatial data
Figure 1. Comparison of different data types