Introduction

GESIS Workshop: Introduction to Geospatial Techniques for Social Scientists in R

Stefan Jünger, Anne Stroppe & Dennis Abel

2026-04-23

The goal of this course

This course will teach you how to exploit R and apply its geospatial techniques in a social science context.

By the end of this course, you should…

  • Be comfortable with using geospatial data in R
  • Including importing, wrangling, and exploring geospatial data
  • Be able to create maps based on your very own processed geospatial data in R
  • Feel prepared for (your first steps in) spatial analysis

We are (necessarily) selective

There’s a multitude of spatial R packages

  • We cannot cover all of them
  • And we cannot cover all functions
  • You may have used some we are not familiar with

We will show the use of packages we exploit in practice

  • There’s always another way of doing things in R
  • Don’t hesitate to bring up your solutions

You can’t learn everything at once, but you also don’t have to!

Prerequisites for this course

  • Knowledge of R, its syntax, and internal logic
  • Affinity for using script-based languages
  • Don’t be scared to wrangle data with complex structures
  • Working versions of R (and Rstudio) on your computer

About us (Stefan)

  • Senior Researcher in the team Survey Data Augmentation at the GESIS department Survey Data Curation
  • Ph.D. in Social Sciences, University of Cologne
  • Research interests:
    • Quantitative methods, Geographic Information Systems (GIS)
    • Social inequalities
    • Attitudes towards minorities
    • Environmental attitudes
    • Reproducible research

About us (Anne)

  • Postdoctoral Researcher in the team Survey Data Augmentation at the GESIS department Survey Data Curation
  • Ph.D. in Political Science, University of Mannheim
  • Research interests:
    • Quantitative methods, Geographic Information Systems (GIS)
    • Political trust, resentment and voting
    • Spatial Disparities
    • Data Quality of Linked Data

About us (Dennis)

  • Postdoctoral Researcher in the team Survey Data Augmentation at the GESIS department Survey Data Curation
  • Ph.D. in Political Economy, University of Cologne
  • Research interests:
    • Quantitative methods, Geographic Information Systems (GIS)
    • Environmental attitudes and behavior
    • Public policy
    • Open source software

About you

  • What’s your name?
  • Where do you work/research?
  • What are you working on/researching?
  • What is your experience with R or other programming languages?
  • Do you already have experience with geospatial data?

Course schedule

Day Time Title
April 09 10:00-11:30 Introduction
April 09 11:30-11:45 Coffee Break
April 09 11:45-13:00 Data Formats
April 09 13:00-14:00 Lunch Break
April 09 14:00-15:30 Mapping
April 09 15:30-15:45 Coffee Break
April 09 15:45-17:00 Spatial Wrangling
April 10 09:00-10:30 Spatial Wrangling
April 10 10:30-10:45 Coffee Break
April 10 10:45-12:00 Applied Spatial Linking
April 10 12:00-13:00 Lunch Break
April 10 13:00-14:30 Spatial Analysis
April 10 14:30-14:45 Coffee Break
April 10 14:45-16:00 Spatial Econometrics & Outlook

Now

Day Time Title
April 09 10:00-11:30 Introduction
April 09 11:30-11:45 Coffee Break
April 09 11:45-13:00 Data Formats
April 09 13:00-14:00 Lunch Break
April 09 14:00-15:30 Mapping
April 09 15:30-15:45 Coffee Break
April 09 15:45-17:00 Spatial Wrangling
April 10 09:00-10:30 Spatial Wrangling
April 10 10:30-10:45 Coffee Break
April 10 10:45-12:00 Applied Spatial Linking
April 10 12:00-13:00 Lunch Break
April 10 13:00-14:30 Spatial Analysis
April 10 14:30-14:45 Coffee Break
April 10 14:45-16:00 Spatial Econometrics & Outlook

“All things are connected”

Catchphrase #1: Tobler’s Law: “I invoke the first law of geography: everything is related to everything else, but near things are more related than distant things.” (Tobler 1970)1

Catchphrase #2: Tobler’s Addendum: “near can take on many meanings in different situations.” (Tobler 2004)2

\(\rightarrow\) “Space is more than geography” (Beck et al. 2006)3


Spatial Association