The Digital Divide

Today I’m heading out west again to do some scouting work for our summer field season(s) in the Bakken. One of the kinks that we’re still working out is how to get as many of our research team to use our project’s Geographic Information System database. Our GIS maps allow us to identify the camp where we’re working and ties together our photographs, interviews, and descriptions.


I’m pretty comfortable with various GIS environments ranging from ESRI’s ArcGIS to QGIS and even Google Earth. It is easy enough to run our GIS on my iPhone using Google Earth, ESRI’s little iPhone Application, or any number of other spatial data viewers available generally for free. My collaborators are not.

This introduces an interesting challenge. This May there will be a study season that my co-director will supervise. It will focus on collection some quantitative data based on a survey. He’ll be accompanied by some students, an interviewer, and one of our collaborating photographers Kyle Cassidy. What do we do if the director and the team are not comfortable with our basic GIS applications? We can use paper maps, of course,  so there is a low tech solution, but this involves a separate step in producing media for the May field team and we’ll have to reintegrate their paper map data into the team GIS. None of this is insurmountable, but it definitely caught me off guard.

There is a tendency to imagine that scholars have largely bridged the digital divide in the research world. Because basic digital research tools are easily accessible, developers have produced straightforward interfaces for even relatively complex software, and free, open source, or low cost options are available for most commercial software, we tend to imagine a kind of techno-democracy where almost everyone can do basic digital work.

The realities are more complex and remind me that people are at least as important as technology in making a project work.

One Comment

  1. Hi Bill,

    I follow your blog with great interest, and this post finally triggered me to respond.

    I am working for some time on a project in which we aim to improve fieldwork on various levels with modern mobile technology. I encountered problems in getting skeptical/unexperienced people to work with digital mobile applications. These always kind of come back to the same issue: if it works and there is a gain in efficiency, people will use it, otherwise they will not. Since there likely is a gain in efficiency in what you want to deploy, I would persist, since using high- and low-tech solutions at the same time for the same purpose carries a high risk of becoming the opposite of efficient.

    As for a succesful deployment, through my modest experience I learnt three things:

    – Make sure deploying the application is really simple, without hickups and doesn’t distract from the fieldwork (but I suppose your choice of deploying the tool already means these criteria are met)

    – Give it half a day of training and explain every bit of it so people are prepared (usually, it is easy to run the application at a device with a large screen in a computer lab, as to avoid five people staring at a small screen in the field)

    – Show that there is a considerable gain in processing time and precision, which increases the opportunity for actual analysis and other jobs after a day of fieldwork (no fieldwork staff can say no to such advantages)

    Just my two cents!



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