Fuzzy Spatial Data Queries and What It Means for Government

To be honest, I’d been at a loss for what to say differently about the second Goodchild et. al. article that I didn’t already say in regard to his book chapter. Then I began to think about Cyberinfrastructure’s post and his ideas about how uncertainty in spatial data queries can be determined by different types of scale (query scale, the segmentation scale, the data analysis scale, visualization scale) and how this problem can change with different levels of scale in and differing levels of uncertainty. Yet boiling the concept of this article down just to these abstract concepts didn’t help me in thinking about where this problem really matters – a matter Goodchild is concerned with when he talks about users of these data libraries.

So, I turned to YouTube. Don’t worry about watching the whole video.

As this video shows, users such as the government utilize geospatial data libraries quite frequently with a whole plethora of new uses. This form of uncertainty can really hinder efforts to modernize government and provide new services (impacting users like you and me).

An example from the film, when a dispatcher uses “On-Demand Pick-up” to dispatch a driver to someone who needs a ride, they better be sure their computer is picking up the same neighborhood as the caller is requesting from. If not, then they could be sending a driver from too far away to pick the person up. But how does this dispatcher get the caller to define a concrete place rather than abstract, vernacular-defined place name? It may seem just a simple question of language and communication skills. Perhaps it is.

But take another example from the film, where city administrators are able to provide real-time information to bus riders on the location of buses. How do they know what scale to provide this information to bus riders at? What if the user requires two bus lines to get where they are going? What happens if this data isn’t provided at a large enough scale to understand the placement of buses? A moot point, perhaps, as the bus will come when it comes. But certainly an important question for the people applying these GIS systems which rely on data libraries about the geographic areas where they operate. This becomes even more important when you think about technology such as LIDAR that operates at even larger scales and the methods used to define such scales of operation.

Tags: ,

Comments are closed.