Final Reproduction Reflection: Urban Environmental Justice of Green Space Access in Chicago Reproduction
After working through four uniquely challenging reproduction studies with the GEOG0361 class, it was finally time to attempt writing my own!
After much deliberation I landed on the idea of reproducing one the labs from my first geography course at Middlebury, Human Geography with GIS, that made me fall in love with geography work: Urban Environmental Justice of Green Space Access in Chicago Reproduction. Coming into this class with minimal computer science background in python, I knew that choosing to write an entire reproduction study from the bottom up would be pose a difficult challenge, but due to the computational simplicity of this lab it presented the fulfilling opportunity of being able to write a reproduction study from start to finish while expanding the scope of my coding skills.
My reproduction of this lab study was ultimately successful! Small discrepancies in the algorithmic specifications for certain spatial science tools such as the buffer tool and centroid tool led to slight deviations in some of the final values however this did not notably impact the validity of the results. The reproducible framework of this study in a single computational notebook also allows for easy reanalysis and replication in the future so that it can be expanded to study different spatial or temporal extents.
More importantly than the successful results from this study, my success in being able to produce a reproduction study is a win for the realm of open GIScience. Not only did it prove that there is a place for effective open science curriculums at the undergraduate level, but the creation of an easily digestible, and computationally simple reproduction study is exactly what is necessary for teaching open science at the undergraduate or high school level. Knowing the impact that the original study had on me in Human Geography with GIS, this study and its research compendium could serve as the gateway to introducing new students to the effective use of open science reproducible principles.
Enjoy!