The use of geospatial data – data that can be mapped using geographic information systems (GIS) – has become increasingly widespread in the social sciences. Applications not only extend to the analysis of classical geographical entities (e.g., policy diffusion across spatially proximate countries) but increasingly also to analyses of micro-level data, including respondent information from georeferenced surveys or user trace data from Tweets. In this Methods Bites Tutorial, Stefan Jünger (GESIS) and Denis Cohen (MZES) show how to retrieve, manage, and visualize geospatial data in R.
After reading this blog post and engaging with the applied exercises, readers will be able to:
retrieve geospatial data from Open Street Map and other sources
perform data wrangling with simple features (a geospatial data format)
visualize geospatial information using 2D and 3D maps
Note: This blog post builds up on Stefan’s workshop Management and Analysis of Georeferenced Survey Data in the MZES Social Science Data Lab. The original workshop materials, including slides and scripts, are available from our GitHub. A live recording of the workshop is available on our YouTube Channel. Additional learning materials on this topic are linked in the Further Reading section below.
