Open Source GIS (Fall 19)
You can access my Distance and Direction model for QGIS here
Additionally, you can see plots for both the distance and direction in relation to rent prices in the Boston Metro area, created using the model and executed with Data Plotly.
For my data, I used the following geopackage, which features U.S. Census data for the Boston Metro area, including Median Gross Rent from 2017 and totals of Latinx population.
Open Source in Practice
The more we delve into QGIS in classes and get involved with the actual code behind the software, the more I understand the value of open-source programming. We as students, and by extension any interested persons, have the ability to make the software work for us, making it extremely adaptable to fit one’s personal needs. I can see this being especially useful for grassroots/local organizations interested in applying GIS technology to their work, as they are able to implement tools built specifically for their varied interests without having to rely on some technological pedagogue (such as ESRI). This becomes increasingly important when discussing GIS as a technology and what it represents. I think this ability to customize in open-source is paramount in combatting common misconceptions surrounding GIS, like that it is a homogenous, universally-applicable tool that cares only for quantifiable, scientific facts (St. Martin, Wing 2007). QGIS and other open-source software is a very big step forward in terms of dismantling these ideas and breaking down barriers of access and application.
However, it is my belief that this concept of accessibility in GIS can be pushed even further. One thing I struggled with during this week’s lab, for example, was translating what I already know of GQIS models and functions into actually writing the code for models. Even when I conceptually understand what I want to implement and the work flow that would help me go about tackling it, I ran into countless errors concerning the mere syntax of the code. One wrong parenthesis or a space where there shouldn’t be is the quickest recipe for frustration. In my opinion, the high level of knowledge required to build individualized tools in open-source GIS is itself a barrier to access. You shouldn’t need a college education in computer science to use and interact with these programs.
I like the proposition put forth by R.E. Seiber, who suggests that in order to overcome the problems in GIS (misrepresentation, accessibility, homogeneity), one must engage directly with the code in order to build an entirely new GIS (GIS/2) (2004). However, I would like to push that idea further by pondering the possibility of creating a more user-friendly way of coding. Perhaps this means an entirely new language that is more straight-forward, designed for people with no prior experience to coding languages and syntax. If engaging with the code is what is required for improving GIS, that code needs to be much more user-friendly if it truly cares about maintaining open-source principles of accessibility.
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