Hi there! My name is Brooke and I am a senior Geography and Environmental Studies major at Middlebury College. I am passionate about using GIS, remote sensing techniques, and cartographic design to expand on studies of environmental justice, recreational access, climate change adaptation, and landcover change. On this page you will find my work from various courses, independent study, and research positions.
This week we explored the topics of GIS as a science, and if/how open source GIS can help with improving reproducibility and replicability within science. Before deciding if GIS should be considered a science, (or if instead it should be viewed as a tool), it is important to decide in what ways we define science, and scientific work. In Chapter 2 of Reproducibility and Replicability, the authors explore the definition of sciences, and the ways in which science and science principles have developed. The chapter also states 5 core principles and assumptions regarding scientific inquiry, that include:
“ Nature is not Capricious Knowledge grows through exploration of the limits of existing rules and mutually reinforcing evidence. Science is a communal enterprise. Science aims for refined degrees of confidence rather than complete certainty. Scientific knowledge is durable and mutable.“
(pg 30).
These 5 core principles reflect the broad nature of scientific work, and with this framework for defining scientific inquiry I believe that GIS, and especially open source GIS, should be considered a science. The third principle–that science is a communal enterprise– stood out to me specifically when considering the scientific validity of open source GIS, as it reflects the importance of communal and collaborative work in achieving meaningful problem solving.
However, the 5th principle–that science is durable and mutable– can be used as a means for making distinctions between GIS as a science and the use of GIS as a tool. In order for GIS to be considered a science, I believe there is a set of criteria that the work must follow, which includes durable and replicable work, and transparency with data and scientific processes. The use of GIS software and GIS tools does not inherently make the work science. However, many applications of GIS work, especially when replicable, fall into the 5 core principles of science listed above.
If transparency of data, code, and computation methods are directly linked to reproducibility (Chapter 3) then open source GIS work is a cornerstone in maintaining and creating reproducible science work. In Defining the Ambiguity, Wright et al. state argue that “it is not at all clear what is meant by doing GIS, the GIS community or GIS research, since in all those cases the etymological path between acronym and phrase has become hopelessly muddied” (Wright et al. 2010, pg 347). In order to create a distinction between doing GIS or using GIS tools and GIScience, the main difference is in replicability, clear analysis, and data/ code transparency. Other important key points that delineate between situations where GIS as a science and GIS is a tool are that GIScience should be used to explore questions of scale, spatial phenomena, and map area (Wright et al. 2010).
One final thought is that instances where GIS programming is more simply used as a tool and not part of a larger scientific process should not be thought of as secondary or lower in significance to science. The beauty of geography as a synthesis discipline is that even small amounts of geographic thought or GIS modeling can be utilized to better understand data across different fields. While science is often regarded very highly, and research that is produced in science journals or for the greater understanding of natural systems is important, a sense of eliteness in these fields may make it so that people are hesitant to accept more contemporary forms of science. GIS, and especially open source GIS, is still growing exponentially in potential and popularity, therefore thoughts about the field will continue to transform with the creation of new processes.
Readings for the Week: 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
National Academies of Sciences, Engineering, and Medicine. 2019. Reproducibility and Replicability in Science Chapters 2-3. Washington, D.C.: National Academies Press. DOI: 10.17226/25303