Greatest Benefit/Danger of GIS
The single greatest potential benefit of GIS is its ability to combine several kinds of data and for the user to view it visually. Data that could be temporal, photographic and real-time could be brought together and seen together. There is a kind of synergy that comes from combining data is this visual way that is difficult to narrow down on, otherwise. You can make queries using other kinds of databases but you need to use your imagination to understand its results, which can have limitations. Indeed, as Anne Seidl demonstrated, linking different sets of data provide you with new data that you did not have in the first place. With a GIS, you can see the changes happen in front of your eyes—and this can be a powerful tool for many “aha” moments. This combining of data also allows you to link data across several databases. In class, we saw how we combined textual/numerical data with physical shapes or polygons, pictures, addresses and so forth. GIS allows you to standardize data across several different kinds of data, as long as you have a way to link it.
The single greatest danger of GIS actually hinges on several things Greg spoke about in his lecture today, including things like ecological fallacy and spatial autocorrelation. And the danger lies forgetting that what lies before you are an approximation of some sort, of a larger and true universe. In other words, pictures, graphs, shapes, polygons, etc are a representation of some “thing” and in order to be able to adequately digest that thing, either alone or in combination with adjacent “things,” we make some judgements (for example, leave out something, like a the river line), or we make aggregations that do not hold true for a significant part of the universe (today’s income example). All these “short-cuts,” if not carefully documented could add up quickly and obscure in a wholesale fashion the data behind your GIS and thus any interpretations and actions you take from the GIS could be based on false or incorrect assumptions.
Some things I take away from GIS are:
You representation is only as good as your data (garbage in, garbage out). For example, measurement data using aerial photography is not accurate without adequate ground truthing.
Remember its qualifiers (We left out single males out of our database, why did we do that?) and what they might add up or take away from the GIS. Showing your methods reveal the data's strengths and limitations and give us a way to figure out the resulting GIS's usefulness.
Remember it is a graphic representation of a universe, not the actual universe (so, curves on a map may be simplified or exaggerated. This may not matter if you are looking a large-scale view, but if you are working on a small piece of it, that curve might make a difference, so scale plays a large role on maps.