Is GIS a Science?
Even after studying Geography for the past four years, I’ve always struggled to explain what GIS is to those unfamiliar with it. Up until taking this course, I thought of GIS as strictly a tool — to keep it simple, I’d describe it as a software that allows users to spatially analyze various data. However, this relatively straightforward description fails to capture the magnitude of just how powerful GIS is. The applications of GIS in classes prior to this course were very much as a tool — learning ways in which I could use the software to draw conclusions about the organization of space. Where is most underserved by public transportation? What is the most ideal location to place solar panels? GIS was a stepping stone to reach answers to spatial questions. After reading Wright et al.’s “GIS: Tool or science? Demystifying the persistent ambiguity of GIS as “tool” versus “science,” I was challenged to confront the various definitions of GIS and reflect on my prior understanding of the software.
Wright et al. explains GIS on a spectrum from a tool, as toolmaking, and as science. My introduction to Open Source GIS has shown me that GIS goes beyond just being a tool, but is toolmaking, and that we can construct models that apply spatial theories. However, I do think it is important to think more critically about GIS applications that arise as GIS as a science. While there are numerous different definitions of science, one characteristic of science that is particularly applicable to GIS is as stated in chapter 2 of “Reproducibility and Replicability in Science,” is that it is a “communal enterprise” (32). While science is traditionally a hierarchical field that gains legitimacy through elite publications, I think the aspect of science as a communal enterprise can help break down some barriers to this field. Open Source, as discussed in my previous blog post, thrives off of collaboration, which is vital to its success and growth.
This segues well into a discussion of how open source GIS can contribute to solving problems of the “reproducibility crisis.” Open source GIS challenges some of the elitism found in science by encouraging collaborating and sharing code, data and methods. This push towards transparency for the purpose of both improvement and reproducibility lends itself well to a more accessible (albeit there is a large technological literacy hurdle) model of science. While I am still new to the world of open source GIS, my understanding is that users are typically transparent in their workflow and link their data. So long as code is well documented and easy to follow, I think open source GIS can be a large contributor to solving the reproducibility crisis.
Sources
Dawn J. Wright , Michael F. Goodchild & James D. Proctor (1997) Demystifying the Persistent Ambiguity of GIS as ‘Tool’ versus ‘Science’, , 87:2, 346-362, DOI: 10.1111/0004-5608.872057
National Academies of Sciences, Engineering, and Medicine 2019. Reproducibility and Replicability in Science. Washington, DC: The National Academies Press. https://doi.org/10.17226/25303.