Geospatial Data, Maps & Spatial Analysis

Since 1790, the US Census has been THE source of data about American people, providing valuable insights to social scientists and humanists. Mapping these data by census geographies adds more value by allowing researchers to explore spatial trends and outliers. This workshop will introduce three key packages for streamlining census data workflows in R: tigris, tidycensus and tmap. Participants will learn how to download census tabular data for one or more geographic aggregation units or years, download the associated census geographic data and then join these data for analysis and mapping.

This workshop will introduce methods for working with geospatial data in QGIS, a popular open-source desktop GIS program that runs on both PCs and Macs as well as linux computers. Participants will learn how to load, query and visualize point, line and polygon data. We will also introduce basic methods for processing spatial data, which are the building blocks of spatial analysis workflows. Coordinate reference systems and map projections will also be introduced.

Geospatial data are an important component of data visualization and analysis in the social sciences, humanities, and elsewhere. The R programming language is a great platform for exploring these data and integrating them into your research. This workshop focuses on fundamental operations for reading, writing, manipulating and mapping vector data, which encodes location as points, lines and polygons.

Geospatial data are an important component of data visualization and analysis in the social sciences, humanities, and elsewhere. The R programming language is a great platform for exploring these data and integrating them into your research. This workshop focuses on fundamental operations for reading, writing, manipulating and mapping raster data, which typically represents geographic information in a grid of regular sized cells.