Open and Reproducible Spatial Data Analysis in the Social Sciences – Ideas and Examples


The idea of reproducible research has gained much recent attention.  This is an approach to publishing reports, documents and web sites relating to data analysis in which complete information regarding the data used and the programming scripts used to perform the analysis are encapsulated in a single object.   The idea is that third parties can not only read the report but they can also reproduce any analytical results or visualisations included in the report.  This allows the scrutiny of methods used,  as well as the adaptation of methods for different data sets or similar but distinct statistical analyses.

In this talk the key ideas and justifications for reproducible research will be discussed,  together with a description of a practical implementation of a reproducible research framework based on the R programming language,  together with RStudio and RMarkdown.   In addition to this,  some examples of ongoing work using a reproducible paradigm will be given,  including an open and reproducible geodemographic classification for the Republic of Ireland.


Chris Brunsdon is currently Professor of Geocomputation, and Director of the National Centre for Geocomputation at Maynooth University. Prior to this he was Professor of Human Geography at the University of Liverpool in the UK, and before that he worked in the Universities of Leicester, Glamorgan and Newcastle, all in the UK. Chris has degrees from Durham University (BSc Mathematics) and Newcastle University (MSc Medical Statistics, PhD in Geography).


Room 314/315, Steele Building (#03)