May 10 | u_Lecture ‘Open and Reproducible Spatial Data Analysis for Spatial Data – Ideas and Examples’

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May 10 | u_Lecture ‘Open and Reproducible Spatial Data Analysis for Spatial Data – Ideas and Examples’

May 10 | u_Lecture: ‘Open and Reproducible Spatial Data Analysis for Spatial Data – Ideas and Examples’

Registration now open for the u_Lecture webinar presentation by Professor Chris Brunsdon, on May 10 at 5pm CEST.  Register here >>>

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, Professor Chris Brunsdon, Professor of Geocomputation at Maynooth University, Ireland, will discuss key ideas and justifications for reproducible research, 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, a critique of multivariate indices of well-being and the production of tutorial materials.

2017-05-03T09:40:04+00:00 March 30th, 2017|Blogs, Events, Webinars|0 Comments