Reproducible and Open GIScience

Open source GIS has the potential to revolutionize the way we see reproducibility and replicability in the field of geography. “Open source” should be distinguished from “free” in that it requires not just zero cost, but the availability and modifiability of all source code. As a result, open source research encourages transparency, collaboration, and rigorous methodology. The open publication of all code and data associated with a study minimizes the possibility of unchecked errors from mistakes in the code or data analysis by allowing peer reviewers to reproduce the same results, and ensures the validity of results by exposing any fraudulent research practices. When it is easy to use another researcher’s code to replicate the same analysis with different data or in different contexts, we can rapidly expand the limits of our understanding by finding where rules do and do not apply, a central tenet of the scientific process.

However, the nature of open source GIS does not solve the issues within the broader culture of academia. There is intense competition among researchers to publish frequently in “high-impact” journals, a profit-centric model that determines the professional success of a scientist by the quantity, rather than quality, of their publications. While researchers within the field of geography may enjoy successful advances in knowledge through collaboration in open source networks, they will still feel the pressure on their careers to participate in the competitive, paywall-restricted culture of journal publications. This pressure is not only professional, but financial, as it costs additional fees to publish to an open journal. Open source GIS also does not yet address the tension between replicability and discovery; it will always be more profitable to pursue independent groundbreaking results than to produce easily replicable research or to replicate the work of others.

Open source GIS has been characterized as a “gift economy,” contrasted with the standard capitalist economy of academia in that a researcher’s professional standing is determined by how much they share and contribute, rather than by how much they own and control. However, while the open science model has the potential to radically change the way research is conducted, it may take some time before this new way of thinking can permeate the systems within the established culture of academia.

Here is more information about the class I’m taking, Open GIScience.

References:

• NASEM. 2019. Reproducibility and Replicability in Science. Washington, D.C.: National Academies Press. DOI: 10.17226/25303. Chapter 3, Understanding reproducibility and replicability (pages 31-43 )
• Rey, S. J. 2009. Show me the code: Spatial analysis and open source. Journal of Geographical Systems 11 (2):191–207. DOI: 10.1007/s10109-009-0086-8
• Dr. Rachel Ainsworth discusses open science culture: https://youtu.be/c-bemNZ-IqA