Our GIS is too small

Very nice paper by Mark Gahegan. Here’s the abstract:

GIScience and GISystems have been successful in tackling many geographical problems over the last 30 years. But technologies and associated theory can become limiting if they end up defining how we see the world and what we believe are worthy and tractable research problems. This paper explores some of the limitations currently impacting GISystems and GIScience from the perspective of technology and community, contrasting GIScience with other informatics communities and their practices. It explores several themes: (i) GIScience and the informatics revolution; (ii) the lack of a community-owned innovation platform for GIScience research; (iii) the computational limitations imposed by desktop computing and the inability to scale up analysis; (iv) the continued failure to support the temporal dimension, and especially dynamic processes and models with feedbacks; (v) the challenge of embracing a wider and more heterogeneous view of geographical representation and analysis; and (vi) the urgent need to foster an active software development community to redress some of these shortcomings. A brief discussion then summarizes the issues and suggests that GIScience needs to work harder as a community to become more relevant to the broader geographic field and meet a bigger set of representation, analysis, and modelling needs.

Good food for thought at the beginning of the year, even though I do not agree with all of his points. There is currently a lot of progress being made concerning some of the problems he mentions (such as GeoMesa addressing scalability, or the NSF funding the Geospatial Software Institute, to name just two examples). I also don’t think (or at least hope?) that it is a prevalent position in our field that if it doesn’t fit on a desktop computer, it is some other community that should deal with it.

One point he raises about software platforms really resonates with me, though, since this is something I have been thinking about a lot recently:

Personally, this has driven me to use R, Python, and PostGIS for almost any kind of work, but I’m wondering if that is a viable solution for everyone? Or are the GIsystems he talks about more like classical, GUI-driven GIS systems that can be used without programming skills?

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