Reproducibility in Open Source GIS

How does open source GIS help solve the problems of the reproducibility crisis for geography?

Open-source GIS helps to solve aspects of the reproducibility crisis for geography in that it encourages research transparency in the collection of data, underlying code, and the computational methods used to analyze the data NASEM, 2019. Furthermore, open-source GIS enables science to be done in a more egalitarian manner. By making analysis methods accessible, both students and researchers are able to collectively use previous work to expand on their own analyses or to replicate and ensure the accuracy of previous work.

The ethos of open-source assists in combatting the ‘publish or perish’ mentality often found in academia that seeks to increase impact factors by publishing in prestigious journals (described by Dr. Rachel Ainsworth in her Ted Talk: Research culture is broken, open science can fix it). Open-source research also ensures that findings are not locked behind a paywall of academic journals, an ivory tower only accessible to individuals with money or at academic institutions but are rather available to the masses as it is an accessible platform that can be customized to suit research needs particularly when there detailed documentation which allows for more replicable and reproducible work to be done.

While reproducibility and replicability can encourage collaboration among researchers as well as transparency of data and methods, it does not guarantee the quality of the data and methodology used to analyze it. Therefore, to use open-source code and data, one must think critically about the methods employed when reproducing work or customizing source code written by others to ensure full understanding of the methods used before implementing them and to ensure that there was not bias in the data collection process.

National Academies of Sciences, Engineering, and Medicine. (2019). Reproducibility and replicability in science.