This paper deals with the production of statistical maps as part of the wider reproducible research paradigm. The current and most widespread ways to produce statistical maps combine several software products in a complex toolchain that use a range of data and file formats. This software and diversity of formats makes it difficult to reproduce the same analysis and maps. The aim of this paper is to put forward a unified workflow that allows map production in a reproducible process. We suggest hereby the cartography package, an extension of the R software, that fills the need of specific thematic mapping solutions.
KeywordsReproducibility Open-source R Statistical cartography Map workflow
- Bivand, R., Keitt, T., & Rowlingson, B. (2016). rgdal: Bindings for the geospatial data abstraction library. https://CRAN.R-project.org/package=rgdal.
- Bivand, R., & Rundel, C. (2016). rgeos: Interface to geometry engine—Open source (GEOS). https://CRAN.R-project.org/package=rgeos.
- Bivand, R. S., Pebesma, E., & Gomez-Rubio, V. (2013). Applied spatial data analysis with R (2nd ed.). Springer, NY. http://www.asdar-book.org/.
- Claerbout, J., & Karrenbach, M. (1992). Electronic documents give reproducible research a new meaning. In Proceedings of 62nd Annual International Meeting of the Society of Exploration Geophysics (pp. 601–604).Google Scholar
- Giraud, T., & Commenges, H. (2016). SpatialPosition: Spatial position models. https://CRAN.R-project.org/package=/SpatialPosition.
- Giraud, T., & Lambert, N. (2016). Cartography: Create and Integrate Maps in your R Workflow. JOSS, 1(4). doi: 10.21105/joss.00054.
- Knuth, D. E. (1992). Literate programming. CSLI lecture notes, Stanford, CA: Center for the study of language and information (CSLI), 1992, 1.Google Scholar
- Openshaw, S., & Taylor, P. J. (1979). A million or so correlation coefficients: three experiments on the modifiable areal unit problem. Statistical Applications in the Spatial Sciences, 21, 127–144.Google Scholar
- Pebesma, E. J., & Bivand, R. S. (2005). Classes and methods for spatial data in R. R News, 5(2), 9–13.Google Scholar
- Stodden, V., & Miguez, S. (2013). Best practices for computational science: Software infrastructure and environments for reproducible and extensible research. Available at SSRN 2322276.Google Scholar