GIS and Academic Portfolio
I feel like the debate as to whether GIS is a science would be easier to have if we spent more time defining terms. I think the term ‘GIS’ is being applied to many different things, all of which constitute a specific part of GIS but aren’t exactly the same. For example, when I first started taking GEOG 120, I thought that GIS was the name of one computer program that was used for geographic analyses. In reality, a bunch of different softwares are called GIS. But the act of doing using these softwares, is also referred to as just ‘doing GIS-work.’
The hypothetical analogy that I would draw for this is to statistics. There are a lot of programs that can be used to conduct statistical research such as R and Stata. None of these programs on their own are considered to be a science, they are tools with which we conduct the science of statistics, or more often than not, apply statistics to other scientific disciplines. Statistics themselves are still a tool, just as GIS is a tool, but that doesn’t mean there isn’t science going on behind the curtain. Our concepts of statistics were invented, as were the concepts that go into GIS. As more techniques are discovered, they are integrated into software to be used as tools in their own right. There was a first person to create a gravity model, and if they had done so on a computer, it would have been considered GIS research. But GIS research also includes times when the GIS is a tool for an answer.
I don’t think that the GIS we’ve done in class thus far is science. It seems like it fits more into toolmaking than anything. You can’t really divorce the GIS from the theory and concepts of health geography that we’re discussing, so in my opinion there isn’t much room for the GIS aspect of the project to stand on its own. Instead, we’ve been making tools to run gravity models designed for health geography, but that could be applied to anything.
Having GIS be open source would contribute greatly to the reproducibility crisis. If techniques, software, and data are made publicly available then third parties will be able to reproduce the methods to verify that everything has been executed correctly. I do wonder how far open data can go in terms of privacy concerns, but the more open and documented these things are the better. The purpose of open source models to begin with is to ensure transparency in the preparation of the data, so as long as these principals are met this will give users a greater ability to fact-check each other, leading to more reproducible research.
Sources
National Academies of Sciences, Engineering, and Medicine. 2019. Reproducibility and Replicability in Science. Washington, D.C.: National Academies Press. DOI: 10.17226/25303
Wright, D. J., M. F. Goodchild, and J. D. Proctor. 1997. GIS: Tool or science? Demystifying the persistent ambiguity of GIS as “tool” versus “science.” Annals of the Association of American Geographers 87 (2):346–362. DOI: 10.1111/0004-5608.872057