What is Open GIScience?
While my previous understanding of the term “open source” was in the context of using free software such as QGIS, this weeks’ readings (Rey, 2009 and Singleton, Spielman, and Brunson, 2016) offered insight into what Open Source GIScience really means, as well as its benefits and risks. Open Source GIScience is defined as “a revolutionary collection of tools and processes through which individuals create, share, and apply new software and knowledge” (Rey, 2009). Open Source GIScience can open wide doors to collaboration and progress in creating tools available for all, however, because of its collaborative nature, there is much room for error.
A concept that these readings urged me to think about was “free” versus “open source” — terms that I had previously understood to be synonymous. However, Rey (2009) breaks down that Open Source GIScience actually entails both free software and open source as two different concepts. He explains these more colloquially as “free beer” (free) versus “free speech” (open source). Free beer was how I previously (and erroneously) understood open source to mean: free as in no payment required. This entails free usage, however does not imply access to the source code or rights to redistribution. Tools such as Google Earth Engine are free, but not open source. Anyone can download GEE off of the internet and use it, however the source code is inaccessible and protected by Google, thus the software would be incredibly difficult to reproduce. Free speech, on the other hand, means that anyone can modify or contribute to the software — a process akin to a “market bazaar” as described by Rey, meaning that a “larger community of far-flung bands of largely volunteer kernel programmers” develop the software “through a process of network collaboration” (194). This is how software such as QGIS is developed and is a collaborative process that allows for continued improvements. Much of open source software is protected by “copyleft,” meaning the code is protected from use in a commercial project. Open source software has many benefits, however in regard to government or private business use, open source software may complicate things in terms of security and possibility for error.
Rey and Singleton et al. ‘s pieces explore that there would be much benefit from collaboration between academia and open source communities. The utilization of Open Source software rather than protected software would enable researchers to create work that is more reproducible and easier to follow. Singleton et al. pushes for a new model of open publishing “oriented towards the social and scientific benefits of increased transparency and reproducibility in academic ‘publishing’ while respecting the tension between openness, reproducibility and intellectual property” (1508). However, there are critiques to this process and open source software. Among other criticisms, many argue that open source communities can foster technological elitism in that only skilled developers can contribute, and there can be a steep learning curve for those who are outside of the community. Technological literacy can serve as a massive hurdle for those who are eager to join the world of open source, which is worsened by poor documentation within the code. As someone with no coding experience, it does seem like an incredibly daunting and out-of-reach possibility to become a contributor.
Obviously, because open source software’s foundation lies in readily accessible and collaborative code, this creates difficulty in classes such as ours that seek to engage with the open source community values of collaboration, while simultaneously respecting the honor code in place in a class setting. I think that open source principles create a wonderful opportunity for group work that do not go against the honor code so long as the code is well documented and each contributor writes their own reflections about the process in a blog post.
Sources
Rey, S. J. 2009. Show me the code: spatial analysis and open source. Journal of Geographical Systems 11 (2):191–207. http://dx.doi.org/10.1007/s10109-009-0086-8
Singleton, A. D., S. Spielman, and C. Brunsdon. 2016. Establishing a framework for Open Geographic Information science. International Journal of Geographical Information Science 30 (8):1507–1521. http://dx.doi.org/10.1080/13658816.2015.1137579