webpage portfolio for open source GIS work
There are three main camps of thinking around the purpose/use of GIS –thinking of GIS as a tool, as toolmaking, and as a science. For those who believe that GIS is a tool, there is a general understanding the GIS is used to help achieve scientific aims but is not itself the scientific end. In this light, GIS is used to achieve the scientific aims of the discipline of geography (Halls 1993; Wright et al. 1997). On the other end of the spectrum, those who believe that GIS is a science equate its development within the geographic and computer science disciplines as a process of creating and formalizing geospatial techniques in a computer-automated platform (Bartlett 1993). If science is an approach to test hypotheses and identify logical answers, this means there needs to be some theory to back up the ways in which experiments are conducted.
In my classes at Middlebury, I think that we have most often used GIS as a tool and for toolmaking, with less emphasis on the idea of GIS as a science. While my introduction into GIS certainly focused on the principles and the “how” of how GIS functions, the emphasis/end point for the class is always using GIS to solve challenges present in society. Through my Senior Thesis, I have certainly thought more about GIS as a science, particulary around critical GIS and ethical uses of GIS in the (re)presentation of nature and conserved areas. As I have advanced through my time at Middlebury, I have been able to explore GIS through a variety of lenses, while noticing that some of my peers within the Geography Department have taken very different approaches to learning GIS. While some have used GIS only as a nominal tool in projects focused on geographic theories and -isms, others have specialized entirely in the theory behind GIS toolmaking and the expansive capacities for this type of research. There is a spectrum of GIS as a tool and as a science, and as Wright, Goodchild, and Proctor (1997) illustrate, this spectrum is necessary to achieve widespread and ehtical use of GIS.
Open Source GIS fits in nicely with the scientific framework of prioritizing transparent and replicable experiments to test theories. In Reproducibility and Replicability in Science (2019), the authors discuss how science is predicated on communal thinking and the sharing of transparent knowledge. Open Source GIS emphasizes community collaboration and contribution, all while documenting everything through openly available code. Through platforms like Github, Open Source GIS users can collaborate on projects and track the changes of peers, helping a community develop scientific processes applicable for a wide range of analyses. In line with Jon Claerbout’s emphasis on the reproducible research movement (1990), the transparency of Open Source GIS allows for experiments to be checked, tested, and replicated in a variety of contexts. This rigorous iteration process already baked into the DNA of Open Source GIS is essential to ensure replicability of experiments and helping to create widely-tested tools.
Works cited: