that was more appropriate for the task that they were pursuing. And we really did this seat-of-the-pants; now that I’ve been working in this area a little bit longer, our developer did a pretty good job of thinking about how people work with this information. But I want to take this from a more systematic perspective.

So I’m going to start out talking about: what are geospatial data? They come in a lot of different formats, and they have a lot of issues about them that really affect how we set up our survey data collection systems. And I’ll probably only have time to talk a little about the cognitive aspects; there’s a whole other set of problems that have to do with computing infrastructure, because these data are very voluminous and require some adaptability in how you work with them. If you want to know something more about this research, go to this Web site. This is also funded by NSF, the Digital Government project. And my collaborators are both at Iowa State and [the University of California at Santa Barbara (UCSB)].

So, we’re used to dealing with this sort of thing; we know a lot about how to phrase questions, we have these nice clean coded texts and— even if we’re doing a scientific study—we like to develop protocols to construct precise and definable measurements. When we move into geospatial data, it’s a different ball of wax. There are two general types of spatial information: one is called vector and the other called raster. Vector data are just points; lines are connections between points, and polygons are just a bunch of segments put together to form a polygon. The basic form is what you get out of your GPS unit, which is a single point, or a sequence of points to make a line. This is a road map that is a set of lines or polygons; if you tap on these lines it’ll give you back the street name. So, even though you have this spatial information, there’s sometimes attribute information linked behind it. Raster data we can basically think of as two-dimensional array, where the cells are basically pixels and—in this case—the value is a color that’s provided on the screen. So all the information is visual; there’s no extraction of numeric information or identification of features, so it’s up to the human to figure out what’s going on here. Something like this, which is a soils map, you might be able to—it’s a raster map—you might be able to tap on it, and there is some attribute information connected to it, what kind of soil is there and what are the properties associated with the soil.

More often than not, in our world, we’re going to want to combine a couple of different sources. This is a topo map with a sample unit boundary. And we might even have dynamic data, even in the form of video, which I’m not going to talk today. Or it might be in the form of—I don’t know if you guys in the back can see this, but—getting GPS readings as you’re driving along or walking along a route.

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