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Research, remote sensing, GIS, and mathematics.

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Is GIS a Science?

In this post, I’ll explore the question: does working with Geographic Information Systems (GIS) qualify as “science”? But before I get there, I’d like to explain why we care if GIS is a science.

It’s not immediately obvious that the distinction matters. Would we not use GIS in the same ways tomorrow, if we unilaterally declared GIS a science today? GIS analysts would perform the same spatial analysis to solve the same problems. In this manner, the debate seems like a dispute over mere semantics.

And let’s be frank: this distinction really is about semantics. But as Wright et al aptly point out in Demystifying the Persistent Ambiguity of GIS as ‘Tool’ versus ‘Science’, semantics matters. According to these academics, the term, “science”, often serves “as a rather crude but convenient shorthand for academic legitimacy.” The notion of a Geographic Information Science helps secure funding and academic recognition for research and instruction surrounding Geographic Information Systems. One illustration of this came up in class today, when Professor Holler mentioned that the classification of GIS as a science allows geographers, including him, to take grants from one of the largest funders of academic research, the National Science Foundation. Although it may seem pedantic to debate whether GIS technically qualifies as a science, when it comes to funding and academic opportunities, the distinction carries real weight.

So, does GIS qualify as “science”?

To answer this question, let’s first define science. We often use the term colloquially to refer to the study of physical and biological processes, but for our purposes, we want to a more rigorous definition. According to Reproducibility and Replicability in Science, science is defined as “a mode of inquiry that aims to pose questions about the world, arriving at the answers and assessing their degree of certainty through a communal effort designed to ensure that they are well grounded.” As such, the degree to which one’s work with GIS qualifies as science depends on whether one uses the scientific method, receives collegial feedback, and employs appropriate methods. It is possible to use GIS in a scientific manner; it is equally possible to use GIS in a non-scientific manner.

Wright et al articulate three main approaches to GIS: “(1) GIS as a tool, (2) GIS as toolmaking; and (3) the science of GIS.” Each perspective could be a valid characterization of an individual’s use of GIS, depending on how one uses the software. Let’s examine the three approaches to GIS in more detail.

  1. GIS as a tool: GIS is a software, used by scientists and analysts of a variety of fields to conduct spatial analysis. Rather than being a field in and of itself, GIS is a tool that salespeople market; and researchers, students, and professionals use to investigate individual problems. These problems are particular to a separate field and the individual uses GIS to solve the problem, with no other motives.

  2. GIS as toolmaking: This perspective revolves around the development and improvement of GIS software. Software developers fall under this category, as they write the code to improve the tools and processes of GIS.

  3. GIS as a science: Geographic Information Scientists focus on problems that predate GIS but are more pressing because of it. Those problems include spatial analysis, data uncertainty & error, looking for new ways to analyze spatial data, among other analytical geographic topics. Essentially, GIScience is a more theoretical approach to using GIS which seeks to expand not just our tools’ capabilities, but also the theory behind those tools.

Thus far, my personal experiences using and studying GIS have fallen under the category “GIS as a tool”. At this point, my only experience with GIS comes from taking a course called Human Geography with GIS. In this class, we learned to use the tools within and solve spatial problems with QGIS. Through our labs and independent problems, we analyzed issues ranging from policing to flood hazards to the long-term impacts of redlining and beyond. While these uses of GIS are substantive and relevant, they only instructed me in the tool side of GIS. Developing GIS software and conducting scientific research on spatial data simply were not the focus of the class.

While I cannot claim experience from the toolmaking and science approaches to GIS, I anticipate my perspective will change dramatically during this course. In just the first two weeks, we read papers that introduced the latter perspectives theoretically, and I understand that our coursework, which will include basic coding and replicating actual studies, will introduce us to these perspectives in practice. I’m thrilled to explore the toolmaking and scientific world of GIS, and will be sure to keep you posted about my journey on this blog.

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