Posts Tagged ‘GCI’

Geospatial Cyberinfrastructure: Past, Present and Future

Sunday, September 28th, 2014

In Yang et al’s article, the authors briefly, yet with enough detail, explains the origin of “Geospatial Cyberinfrastructure” (GCI), various technologies that contributes to its birth and current uses of it.

From this article, GCI is referred as an infrastructure that can support the collection, management and utilization of geospatial data, information and knowledge for multiple science domains based on recent advancements in geographic information, science, information technology, etc.

As a newbie who just started to explore the world of GIS, it was a surprise to learn about an existence of GCI that encompass even the Geographic Information Science, because I found that the concept of GIScience itself was already quite vast when I first learn about it from this course just a couple of weeks ago.

Putting aside my own impressed feelings, as I was reading further in the article, I found it very informative overall and liked the ‘discussion & future strategies’ where the authors even assessed the future studies required for the GCI to improve further. On the other hand, at some point of the reading, it seems like the authors seem to overly emphasize the importance of developing GCI, but I guess that was the whole point of this article anyway.

ESRI

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GCI and blindness

Friday, February 17th, 2012

The kind of power in the type of GCI we can expect in the future is hard to grasp. Sensors automatically collect petabytes of real-time streaming data that gets send to computers, which harness the computational power of grid computing. Despite the large amounts of data, access and retrieval of information would be easy because computers, being equipped with proper semantics would know what we wanted. We would be able to deal with the most complex issues through multidimensional analysis and achieving excellent interoperability between applications. On one hand, this future is exciting, but on the other, it is also a little daunting to think about how complex systems will become and how well people will be equipped with the ability to question machine outputs.

In part, this is an extension to ClimateNYC’s post. I too am concerned about the opacity of GCIs. Will continuous data feeds really make the world more understandable? The shift in the way science will be done with GCIs will have to be accompanied by an equally educated population, which should include end users as much as developers of the technologies involved. Otherwise, researchers using this technology will not even stand a chance to question the results he obtains. Users must be able to benefit from the amazing potentials of GCI as well as be able to consistently negotiate its terms of developments and the mechanics behind the technologies. The idea of GIC as a black box is a scary one; if we accept it without question, technology (sensors, applications, computational analysis) will be a veil between us and natural phenomena. If we lose the ability to questioning the outcomes we obtain from machines, we will be dominated by technology without even knowing it. Therefore, instead of trying to “relieve scientists and decision makers of the technical details of a GCI”, I believe the opposite must be true. Educating the greater population of the mechanism behind such complex systems is necessary if we do not want to go blind.

– Ally_Nash

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Using GCI Without Thinking

Thursday, February 16th, 2012

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.

-ClimateNYC

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