Some motivating examples

  • Example we’ll be working towards in this workshop: map of railways & secondary sector employment in England 1851 in static and interactive versions.
  • Some examples of thematic maps from a previous workshop.
  • More examples made with tmap, the R package we will be demonstrating are online.
  • Example online press release HIVA - KU Leuven with a interactive map on KU Leuven-website.

Why (not) R for making maps?

Why R Why not R
Learning curve / no GUI
free & open source
large community & ecosystem
very broad range of libraries very broad range of libraries (docs)
statistical programming language statistical programming language

Alternative for example: dedicated GUI-driven GIS-software such as QGis.

With R ecosystem & programming background:

  • Stronger focus on ‘data science’: collecting, reading, manipulating, visualising, communicating about data beyond the ‘traditional’ reporting of statistical analyses. More info: tidyverse, [“R for Data Science”.
  • Spatial data is treated in analysis like a regular dataframe (with a ‘geometry’ column): spatial analysis & “regular” analysis(skilss) move closer [more info: simple features-standard in R

Consequences:

  • Enables quick spatial data-exploration in single program & work-flow.
  • Novel ways of approaching, using, presenting (esp. digital, large scale) datasources.

Example of novel applications using R to combine quering API’s, spatial operations, visualising on externally provided interactive maps, etc.: Exploring historical maps and spatial data with R and OpenStreetMap.

Worked example in this workshop: rail and industry in 1851 England

Data-source: The occupational structure of Britain 1379-1911, Cambridge Group for the History of Population and Social Structure.

We will illustrate throughout example common steps for thematic maps:

  1. Load spatial data.
  2. Load and add “regular” data-of-intrest.
  3. Manipulate (spatial) data.
  4. Plot map.