Image: Fabien Barral via Unsplash
Using the Geographical Information System QGIS for data analysis
Mon 14 Nov 2022

Geographical and georeferenced data are gaining increasing importance in social science research. For example, it is becoming more common to add geographical data related to the social or physical environment as contextual variables to social surveys or to aggregate social survey results at various geographical scales.

The hands-on workshop in July 2022 was designed to address the needs of researchers with an interest in the spatial analysis of socioeconomic data, but lacking the programming skills to do so using R or Python.

About GIS tools

Using geographical data in research necessitates additional analytical skills and workflows, usually related to some sort of Geographical Information System (GIS). GIS can be defined as a collection of tools to process, analyse and visualise data containing spatial information.

Such tools have been developed as “packages” for statistical software R or for the programming language Python, but they require intermediate to advanced coding skills. There are also GIS software solutions from various corporations which may be unaffordable for certain contexts, such as independent researchers of non-governmental organisations.

Barriers and solutions

One of the barriers for social scientists using technologies for spatial/geographical analysis is the knowledge of specific software, as well as the relatively steep learning curve required by such tools. There is also a misconception that geospatial analysis tools always require computer programming skills that some social science researchers may not possess.

QGIS was the Geographical Information System (GIS) used for this event as it provides an ideal training environment for three reasons:

  1. It is a free/open source GIS, thus eliminating licence fees/costs. 

  2. It can be easily installed and operated via an intuitive user interface that does not require coding skills. 

  3. There is a large international community of developers and trainers offering high quality learning resources (many of these available for free) alongside a large user base for support.

Using the free and open software QGIS

The purpose of this event was the delivery of hands-on training on Geographic Information Systems (GIS) for social scientists with very little or no experience in this technology. 

The free and open software QGIS was used throughout and the training was structured into seven parts: (1) Introduction to GIS; (2) Exercise 1; (3) Description of GIS formats and Tabular Data Processing; (4) Exercise 2; (5) Introduction to spatial data analysis and mapping; (6) Exercise 3; (7) Closing, Q&A. 

The workshop was attended by 80 participants and participants were grateful for the hands-on nature of the event. This workshop demonstrated the need for alternatives to R and Python for geographical analysis. 

The participants expressed interest in sessions addressing specific research questions, constructing geospatial data, for example in relation to a particular country and performing advanced spatial analysis (e.g. hotspot analysis with health-related data).

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