Looking at John Snow’s Cholera map from the twenty first century: A practical primer on reproducibility and open science

Daniel Arribas-Bel*, Thomas de Graaff, Sergio J. Rey

*Corresponding author for this work

Research output: Chapter in Book / Report / Conference proceedingChapterAcademicpeer-review

Abstract

This chapter (This manuscript is a chapter version of the original document, which is a reproducible online notebook. The entire, version-controlled project can be found online at: https://bitbucket.org/darribas/reproducible_john_snow.) presents an entirely reproducible spatial analysis of the classic John Snow’s map of the 1854 cholera epidemic in London. The analysis draws on many of the techniques most commonly used by regional scientists, such as choropleth mapping, spatial autocorrelation, and point pattern analysis. In doing so, the chapter presents a practical roadmap for performing a completely open and reproducible analysis in regional science. In particular, we deal with the automation of (1) synchronizing code and text, (2) presenting results in figures and tables, and (3) generating reference lists. In addition, we discuss the significant added value of version control systems and their role in enhancing transparency through public, open repositories. With this chapter, we aim to practically illustrate a set of principles and techniques that facilitate transparency and reproducibility in empirical research, both keys to the health and credibility of regional science in the next 50 years to come.

Original languageEnglish
Title of host publicationRegional Research Frontiers
Subtitle of host publicationVol. 2 - Methodological Advances, Regional Systems Modeling and Open Sciences
EditorsRandall Jackson, Peter Schaeffer
PublisherSpringer International Publishing Switzerland
Pages283-306
Number of pages24
Volume2
ISBN (Electronic)9783319505909
ISBN (Print)9783319505893, 9783319844367
DOIs
Publication statusPublished - 2017

Publication series

NameAdvances in Spatial Science
ISSN (Print)1430-9602
ISSN (Electronic)2197-9375

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