Regional Research Frontiers - Vol. 2 pp 283-306

Part of the Advances in Spatial Science book series (ADVSPATIAL)

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
Chapter

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.

References

  1. Arribas-Bel D (2016) Geographic data science’15. http://darribas.org/gds15
  2. Arribas-Bel D, de Graaff T (2015) Woow-ii: workshop on open workflows. Region 2(2):1–2CrossRefGoogle Scholar
  3. BusinessDictionary (2016) Workflow [Online; accessed 15-June-2016]. http://www.businessdictionary.com/definition/workflow.html
  4. Case A, Deaton A (2015) Rising morbidity and mortality in midlife among white non-hispanic americans in the 21st century. Proc Natl Acad Sci 112(49):15078–15083CrossRefGoogle Scholar
  5. Gandrud C (2013) Reproducible research with R and R studio. CRC, Boca Raton, FLGoogle Scholar
  6. Healy K (2011) Choosing your workflow applications. Pol Methodologist 18(2):9–18Google Scholar
  7. Hempel S (2006) The medical detective: John Snow and the mystery of cholera. Granta, LondonGoogle Scholar
  8. Perez F (2015) Ipython: from interactive computing to computational narratives. In: 2015 AAAS Annual Meeting (12–16 February 2015)Google Scholar
  9. Rey SJ (2009) Show me the code: spatial analysis and open source. J Geogr Syst 11:191–207CrossRefGoogle Scholar
  10. Rey SJ (2014) Open regional science. Ann Reg Sci 52(3):825–837CrossRefGoogle Scholar
  11. Stodden V, Leisch F, Peng RD (2014) Implementing reproducible research. CRC, Boca Raton, FLGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Daniel Arribas-Bel
    • 1
  • Thomas de Graaff
    • 2
  • Sergio J. Rey
    • 3
  1. 1.Department of Geography & PlanningUniversity of LiverpoolLiverpoolUK
  2. 2.Department of Spatial EconomicsVrije Universiteit AmsterdamAmsterdamThe Netherlands
  3. 3.School of Geographical Sciences and Urban PlanningArizona State UniversityTempeUSA

Personalised recommendations