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Show me the code: spatial analysis and open source

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Abstract

This paper considers the intersection of academic spatial analysis with the open source revolution. Its basic premise is that the potential for cross-fertilization between the two is rich, yet some misperceptions about these two communities pose challenges to realizing these opportunities. The paper provides a primer on the open source movement for academicians with an eye towards correcting these misperceptions. It identifies a number of ways in which increased adoption of open source practices in spatial analysis can enhance the development of the next generation of tools and the wider practice of scientific research and education.

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Notes

  1. STARS is a package supporting exploratory space time analysis of areal unit data which was released in early 2006. PySAL is a collaborative effort between the GeoDA (Anselin et al. 2006) and STARS teams to develop a common library of spatial analysis methods. It is planned for release in March 2009.

  2. While many of the issues raised below have relevance beyond spatial analysis to all of scientific research in academia, I focus on my home discipline.

  3. GNU is a recursive acronym for “GNU Not Unix”.

  4. One could interpret ESRI’s adoption of Python as its scripting language as a similar strategic move to tap into user-led innovation.

  5. The spatial data infrastructure stack consists of the data gathering, management and processing functions which are required prior to carrying out spatial analysis and modeling.

  6. See McCullough (1988, 1999) on the issue of identifying hidden problems in statistical software.

  7. In addition to its excellent functionality of state of the art spatial analysis, one of the important reasons for the impressive popularity of GeoDa (Anselin et al. 2006) is the free availability of detailed user documentation.

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Acknowledgments

Portions of this research were supported by National Science Foundation Grants BCS-0602581 and BCS-0433132. Previous versions of this paper were presented at the 2007 Association of American Geographers Meetings, the University of Southern California, Arizona State University and San Diego State University, where I received many valuable comments that have improved the arguments. I have also benefitted from the suggestions and comments of the anonymous reviewers and the Editors.

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  1. School of Geographical Sciences, Arizona State University, Tempe, AZ, USA

    Sergio J. Rey

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Rey, S.J. Show me the code: spatial analysis and open source. J Geogr Syst 11, 191–207 (2009). https://doi.org/10.1007/s10109-009-0086-8

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