Using GCI Without Thinking

Chaowei Yang and the other authors of “Geospatial Cyberinfrastructure: Past, Present and Future” believe that the evolution of GCI “will produce platforms for geospatial science domains and communities to better conduct research and development and to better collect data, access data, analyze data, model and simulate phenomena, visualize data and information, and produce knowledge” (264). However, to borrow from Bruno Latour in Science in Action, you can’t help but wonder how much of all of this might just end up being a black box for many disciplines that utilize geospatial data but don’t question how it’s presented and processed. Could this be the quietest revolution in GIS?

The idea of GCIs as black boxes should come as no surprise. Large numbers of people utilize technology that “brings people, information, and computational tools together to perform science” without questioning the underlying “data resources, network protocols, computing platforms and computational services” (267) that help them attain their goals. By using the term black box, I emphasize the meaning Latour intends that it serves a concept or purpose that most people don’t investigate beyond accepting that those in the GCI field have questioned it and made sure it functions.

While I agree with SAH about the exciting potential “a large infrastructure supporting free global geospatial data” holds, I wonder how many people utilizing this network will truly appreciate it. A great deal of people working in academia no doubt. However, users who don’t possess such an academic background or connections to this community might also interact with and contribute to this data source even as GCI remains a black box. While the democratic aspects of this are exciting, I also wonder how we might filter so much data and use it most productively (and ensure its accuracy) in light of the author’s questions about how best to deal with real time data.


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