In this report we discuss the efforts of the First Mile Connectivity Consortium (FMCC) to shape a Geographic Information System (GIS) platform into a tool for data-driven policy advocacy. This work took place in the context of a lack of robust, accurate data concerning broadband access in Canada’s northern and remote regions. Given this challenge, we sought to develop a transparent methodology to (re)present the limited existing statistical data on broadband access and affordability in maps of remote and Northern Indigenous communities in Canada. This was done to outline a GIS design process that we can adopt and adapt as more accurate data from these regions becomes available, as well as highlight and reflect on the design choices we made throughout this project.
Suggested Reference to the guide:
Smith, T.J., McMahon, R., Whiteduck, T. (2017). An Open Source GIS and Mapping Methodology for Internet Access in Remote and Rural Indigenous Communities. First Mile Connectivity Consortium. February. 43 pages.
- Click here for a PDF copy of the report (43 pages). An Open Source GIS and Mapping Methodology for Internet Access in Remote and Rural Indigenous Communities.
Our methodology involves first defining a geographic community of interest, and then collecting, formatting and spatially encoding statistical data in visualizations that we used to contribute to an intervention in a regulatory proceeding on digital infrastructure and services in Canada’s northern, rural and remote regions. We discuss the digital literacy challenges that we encountered in this project, considering how they may impact further adoption, adaption and sustainability of our methodology by community groups.
In the future, we hope these steps can be taken up and used by community-based organizations to generate their own GIS-supported data visualizations. In our opinion, this methodology might be useful for such groups to: 1) collect and display in a useful way all of the statistical information available about a community or region; and 2) show relationships between or among various statistical indicators.