Enhancing Qualitative Social Science with GIS

ArcGIS has much to offer social scientists using qualitative and mixed-method perspectives in their 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.

This exploration began with a  Technical Workshop at UC 2021  to showcase the power and utility of  ArcGIS for qualitative social science  research, which includes data capture, coding, and analysis workflows. Briefly summarized, the workshop discusses how GIS and Social Science intersect at the use, visualization, and dissemination of diverse data types, e.g., perception data, concepts, behaviors, and values—to address longstanding issues of social and environmental concern.

For an overview, see video:  "Enhancing Qualitative Social Science Research with GIS. 

What's New: Mapping Qualitative Data (January 2024)

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. However, what'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.

Qualitative data can mean a lot of different things for GIS professionals and qualitative researchers, and the different perspectives they bring frame how they encounter and work with such data. For many GIS practitioners, qualitative data often come in the form of things like open-text survey responses, ad hoc or unstructured feedback, or user-defined attributes. Additionally, AI tools have been developed that can automatically pull-out certain kinds of information from documents, images, or video, or that can score sentiment, which can all then be spatialized, if not already. In such contexts, qualitative data are utilized as yet another kind of data source, which must be collected, classified, and extracted so that they can be easily integrated into GIS tools/workflows. Generally, the goal behind this is to create a single "authoritative" view from the data that is used to inform various kinds of action or decisions. As such, the primary concern typically driving how GIS practitioners interact with qualitative data is: “How can I organize, quantify, or make sense of non-numerical data?”

However, to people like human geographers, sociologists, anthropologists, or many other researchers, qualitative data means something quite different. From their point of view, such data consists of things like notes and reflections generated through field-based observation, interview recordings and their corresponding transcripts, photos or videos taken by the researcher or participants, or any number of digital or material things relevant to the project at hand.

In other words, unlike the single, authoritative view from the data that a lot of GIS work aims to create, qualitative researchers are often focused on understanding things from multiple perspectives. This means that many qualitative researchers often use participatory data collection methods that empower participants to become research collaborators who can generate data about their lives and better steer research priorities towards local concerns. The underlying question driving how many social researchers encounter qualitative data is generally: “How can I comprehend and convey the lived realities of our participants on their own terms?"

However, seeing the power of both GIS and qualitative data, in recent years researchers and practitioners across GIS, geography, and social science fields continue to seek new ways to understand the importance of space and place and to use new technologies to uncover insights. Additionally, they are also looking for novel ways to visualize and analyze their data, and other ways to tell stories about the relationships between people and places, oftentimes with the aim of communicating to fresh audiences.

Unsurprisingly, there are different mixed-method and multi-disciplinary projects that have emerged from and helped define this growing field of “Qualitative GIS”. These  real-world examples  show a variety of studies that have successfully combined qualitative and GIS approaches.

There are a number of different ArcGIS tools available to social science researchers to utilize location information to transform their qualitative data, which includes sourcing, collecting, creating, and analyzing.

•  American Community Survey  (US Census Data)
•  American Community Survey FAQs 
•  Household Pulse Survey Data on gender, identity, and sexual orientation 

Contextual data such as satellite imagery or population statistics

•  ArcGIS Earth 
•  ArcGIS Online 
•  ArcGIS Living Atlas of the World 
•  Community Analyst 

Locational, contextual, photo/video, and participant-generated data, surveys

•  ArcGIS Survey123 
•  ArcGIS Field Maps 
•  ArcGIS QuickCapture 
•  Site Scan for ArcGIS 

Identify spatial patterns; triangulate or validate qualitative and geospatial data

•  ArcGIS Maps for Creative Cloud 
•  ArcGIS Pro 
•  ArcGIS Online 

Create engaging stories or interactive digital media; speak to public audiences; build a hub to work on share projects

•  ArcGIS StoryMaps 
•  ArcGIS Hub 
•  ArcGIS Experience Builder 

Below we list some resources to help with further exploration. Send suggestions for additional links to socialscience@esri.com.

 Powers of Qualitative Research  from Nature.com

•  Express Map Overview 
•  Express Map Tutorial 

•  Getting Started with ArcGIS Drone2Map 
•  Creating Imagery Products with Site Scan for ArcGIS 
•  FAQs about Site Scan 
•  FAQs about Drone2Map 

•  Enter data faster and more accurately 
•  Access data results 
•  Go beyond point data 

A. Field Maps Discovery and Migration:

•  5 Things to try in Field Maps 
•  Migrate to ArcGIS Field Maps 
•  ArcGIS Field Maps and the iOS platform 

B. Field Maps Data Collection:

•  Create a map for data collection in Field Maps 
•  Try data collection in ArcGIS Field Maps 
•  Configure a map for data collection in Field Maps 
•  Introducing smart forms in ArcGIS Field Maps 
•  Configuring maps for the field 

C. Field Maps Location Tracking:

•  Field Worker user type - more opportunities to use location tracking 
•  Location Tracking analysis with Field Maps and Velocity 
•  Creating Animations using location tracking data 

D. Field Maps Automation:

•  Use webhooks to automate workflows in ArcGIS Field Maps 

Submit your  Qualitative Social Science Success Story Submission on the portal !