Global country referenced data have become widely available and represent a useful resource for researchers particularly those looking at interdisciplinary themes. Researchers can waste a lot of time formatting data and getting bogged down with country names and codes. This time could be much better spent addressing their research topic. rworldmap is a well documented, user friendly (according to user testimonials*) package that lessens some of the constraints to users displaying country- referenced data. While it is relatively easy to get started with rworldmap, it also has the flexibility to produce more complex visualisations. A tutorial is ideal to get novice R users started with data manipulation and mapping, and to introduce more experienced R users to advanced functionality. Whilst the package contains boundaries for global maps it also contains functions to enable users to map their own polygons. For example see nhsmaps.co.uk which uses rworldmap and shiny to create an interactive map of English health service regions.
How to :
Little. To have installed R, to know what a dataframe is. Knowledge of data manipulation in R and some experience with rworldmap will help attendees get more from the tutorial.
Anyone who wants to visualise global data (or any other data on a polygon map), particularly for use in papers and presentations (e.g. academics and researchers).
South, A.B. (2011) rworldmap: A New R package for Mapping Global Data. The R journal 3, 35-43.