2 minute read

While any given scientific experiment might rely on different principles or follow slightly different rules in general, science endeavors answer questions through evidence and logic. The scientific method of hypothesizing, evidence gathering, testing of hypotheses, and logically drawing conclusions from evidence in a way that can be communicated to others is the core of science. However, if we endeavor to answer questions in a way that we can trust with a minimum of error, it is important that if the same conditions are replicated the same result should be achieved. Otherwise, we cannot trust the methods that we are attempting to use. I was planning on majoring in psychology for a long time, and we spent a lot of time on research methods, but one of the things we learned about was validity in scientific research. For example, a study might not be reproducible because its subjects were not a representative cross-section of the population, or perhaps some condition was not administered to them all by the same researcher. I am curious to see how what I learned in Research Methods in Psychology translates to something like GIS.

I feel that I have most often viewed GIS as a tool. I think I tend to focus more on what answers a given software can provide to me or how I can use it to assist in solving some spatial problem. However, in my Conservation Planning course, we did spend some time specifically measuring how changing different parameters in a Google Earth Engine function would affect an output and also how different softwares might handle a problem in different ways. In my mind, this is getting closer to the idea of GIS as a science. In that class I spent time thinking about the question of how small tweaks in my methodology impact the results that I get, and what happens when I put a lot of time into coming up with a methodology to answer some spatial question I have instead of just trying to find the exact existing tool that will answer my needs. I think for me it is difficult to get past my initial impression of GIS as a tool, but I do believe that many of the core ideas of what make science what it is, also apply to GIS. Any spatial problem can have a hypothesis made about it, which can then be tested by applying certain steps to gather evidence.

References:
NASEM (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

St. Martin, K., and J. Wing. 2007. The discourse and discipline of GIS. Cartographica 42 (3):235–248. DOI:10.3138/carto.42.3.235-248