Wednesday, January 29, 2014

Volunteered Geographic Information in the Social Cyberscape

Fischer’s article from last Spring in Geo-Informatics breeches a subject that most if not all modern Americans have encountered in one form or another: data-driven consumer-focused advertising.  Particularly, Volunteered Geographic Information, or VGI for short, has become a common source for geodemographic data that sites like Amazon, Google Places, Facebook Places, Yelp, Twitter, and other applications utilize in order to expedite crowdsourcing at a reduced price in the ongoing maintenance of their datasets.  

VGI falls under the umbrella term “Big Data.”  Big Data refers to a collection of information that is collected from a large number of sources (think one-billion plus Facebook users) and depending on the analytic technique, the permutations of data are processed for various commercial uses by corporations.  Uses are derived from the source person's habits of behavior, and other seemingly mundane tidbits of information.  As the technology for analyzing this complex data improves, so does its value.  Crawford and Boyd point out, “…VGI becomes a commodity as its social patterns of production are analyzed and applied for social and economic decision-making processes and the data-driven mass customization of goods and services.”  In other words, a world of large-scale personalized advertising grounded in an individual consumer’s behavior. 
The potential uses for VGI is still an open frontier, as well as the nature of how “voluntary” it truly is.  The authors mention that some GIS practitioners remain skeptical of the data’s reliability relative to the accuracy and credibility from which these essentially unregulated sources are pulled.  In Crawford and Boyd’s words, “VGI is a biased source of information which is produced by interest-specific communities and their conceptions of space,” and later, “VGI datasets hardly allow for a reliable interpretation of who and what the analysis represents, let alone a generalization.”
            As mentioned in passing above, the voluntary nature of VGI is dubious when juxtaposing users’ perception of data with data collection agencies’.  Where a user might give Google+ permission to share their location with friends in their social circle, this simultaneously allows Google to track the venues and habits of one’s movements in a decontextualized manner with emphasis on data collection rather than human collaboration.
            Ultimately, for VGI data, Fischer claims, “…the challenge to engage with networked geo-communication as a whole and how people construct meaning from the use of geomedia, denotes an approach towards a social theory of geographic information.”  This harkens to the interpretation that GIS is not merely a technological means towards furthering Big Data-driven profits, but an interactive medium whereby informed users can deepen their understanding of the topographical relationships around them while navigating a socially significant medium with others.     

Fischer, Florian. (2012, April-May).  A New but Delicate Data-Source: VGI as Big Data.  GeoInformatics, 15(3), 46-47.

Accessed here:


  1. I think is presents interesting implications. Because most user are unaware of the fully extent of the information that is obtained and the manner in which it is used. While I think it is a unique application of data collection, I think it presents interesting connotations in terms of privacy. It would be interesting to see if people how viewed these actions in terms of positive or negative benefits of social advancement or privacy violations.

  2. I think you make a good point here about how voluntary VGI is. Many users of the internet are unaware of the geographic information footprint they are leaving on all the location enabled devices they are using. This can have huge implications to geo-privacy. We like the location-enabled services, but how should we regulate the tracking of everyone. Currently we are all being tracked, what should be the rules of regarding this info? These are big debates.

  3. I had never heard of VGI before and thought it was a really interesting concept, but seems to have some kinks to work out in it. It would be cool if they could find a way to make their data less biased and more reliable for those analyzing it.