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.
Open Source GIScience: Open source software refers to programs that operate under a public domain, and the source code for the program is available for public use. The realm of open source GIS has continuously grown in popularity, and includes programs such as QGIS and OSGeo. R studio software is another example of a popular open source software, which allows for synthesis of quantitative data from a variety of disciplines. It is important to note some differences in accessibility within the code and programs that sit under the umbrella of “open source.” Open source software, (the strict definition is based on the licensing), includes software that is free for distribution, the code is publicly available, and the software can be modified (Rey 2009). While “Free software” is similar, and often falls into the category of open source, it further emphasizes the importance of user freedom and any “free software” must follow an even stronger set of freedom guidelines (Rey 2009).
Why Use Open Source Software? Both the readings by Rey (2009) and Singleton et al. (2016) emphasize the idea that we currently sit at a turning point in academic spatial analysis work, where significant research is underway in the world of open source GIScience. This is a crucial stage for the future of spatial analysis work, because the growth of open source platforms helps to break down elitism in academia and academic publication work, and emphasize collaboration efforts. Especially in 2021, collaborative and open source data and code for research about the COVID-19 pandemic, the climate crisis, and problems of racial and social inequities can be crucial in helping build community resilience and finding solutions. By addressing these problems as a group, knowledge discovery can be shared and celebrated, instead of gate kept, as it has been previously in research settings. While there are shortcomings and problems that come with open source work, it is an alternative to closed source models that allows for more collaborative work, reproducibility, and access. Despite the increased accessibility resulting from open source platforms, there are still barriers that exist, such as the spaces in which open source software and coding languages are traditionally taught (colleges/universities).
Open Source GIScience in the Classroom: The use of open source GIScience in a liberal arts, undergraduate setting is aligned with many of the common learning goals here at Middlebury. In Rey (2009) the article uses an analogy to describe open source work as a “conversation” “from which ideas for new products, processes, and innovation can be gained.” Just as many of my most meaningful classroom experiences have come from enriching discussion, I hope to gain the same in this course from working in this collaborative platform and getting to watch my classmates explore the world of open source GIS as I do the same. Additionally, the expansion and replication of successful open source software requires well documented workflows, that help readers follow the steps that have been taken to work with the data. The process of both creating workflows and replicating existing GIS workflows in a number of geography courses at Middlebury helps students prepare for engaging with open source software. In my prior experience with GIS courses at Middlebury, I have enjoyed the process of creating workflows and talking through data visualization plans, because oftentimes the people I work with have problem solving approaches that differ from my own. The workflow and work documentation process also creates an atmosphere that is well suited for collaboration, where peers can learn from each other in non traditional ways. In order to use GIS in a collaborative setting, undergraduate institutions must encourage students to adopt the mentality of valuing collaboration, giving credit when credit is due (including proper citation), and placing value on all steps of the GIS process, not just a specific end result. Historically speaking, the traditional grading system places an extreme emphasis on rigid grading, and reaching a final end answer that is correct. One of the largest problems is that rarely in academic settings are we given the opportunity to correct our work and reflect on where things went wrong. In terms of grading and expectations for this class, I believe that a grading method that encourages class participation, collaboration, and growth would be most valuable, and reflective of the nature of open source GIScience. I also believe that grading policies that encourage those qualities disincentivize the stress and anxieties about bad grades that often leads to instances of academic dishonesty.