What is Open Source GIS?

Open source software and open science - the practice of publishing detailed workflows, code, and data along with a written scientific report - has the potential to make science far more reproducible, reliable, and equitable. Thinking about open source software and open source GIS is exciting for me in part because it seems particularly well suited for the current historical and cultural moment. The decentralized model of knowledge creation meshes well with many aspects of how pop culture is created and consumed and how social movements have manifested themselves in recent years - there is something about it that just seems like a really good idea. However, open source is not an inherently perfect model, and the way it is implemented should be carefully designed and tailored to the application and context.

In the context of science, education, and business, one of the primary issues with open source is reward structure, as Sergio Rey mentions in this article on the interaction between spatial analysis and open source. Our education system, economy, and broader culture place a high value on getting the ‘right’ answers in the ‘right’ way, which frequently means doing things individually and competitively - the collective, collaborative foundation of open source principles challenges these values and the systems that are built around them. Practically speaking this tension most directly impacts how we distribute currency/value (both financially and socially through status and grades). We can start to adapt areas like academic research to open source by changing how we distribute titles and grant money, and though they may be contentious these changes seem fairly easy since they can be accomplished by individually changing the policies of the institutions that administer them - we’re starting to do this for this class, though within the limits of College grading and academic honesty policies. Changing reward structure for business is much harder and slower, since it involves broad shifts in what consumers want to pay for, what companies want to produce, and how governments want to regulate all of it.

In terms of academic honesty, grading, and expectations for this class, I am finding it particularly difficult to reconcile the collaborative nature of open source with the high value placed on individual effort by the academic systems/settings that I have grown up in and am accustomed to. What comes to mind initially to reconcile this is working in groups for the GIS analyses, though for this class they would be more loosely structured than they usually are - maybe we would start out working separately in groups, but would share ideas and code across groups as needed. The open source ethos of ‘one project, many hands’ is great in principle, but for a class of this size and nature (where we’re surveying many different software environments and methods), it seems far too chaotic and complicated to have everyone working on one thing together.

References: 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

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