Maybe the most challenging aspect of the paper–aside from the technical jargon–was trying to connect cyberinfrastructure concepts with my own experiences using GIS. Wang and Armstrong describe an approach to GIScience topics that I have never properly confronted. For instance, if someone were to ask me about the “crux” of inverse distance weighting, I would probably mention the definition of the relationship between interpolated values and surrounding points, or the selection of an appropriate output resolution. Increasing the near neighbour search efficiency is not immediately called to mind. If this paper had been my introduction to the study of GIScience, I would have likely begun with a different opinion about it’s place in the field of geography over computer science. Anyway, I can appreciate the appeal to the authors’ target audience through the conceptualization of “spatial computation domains” as spectral bands.
It’s true that some of the finer points may have been beyond my understanding. Still, the question on my mind as I read was whether or not my understanding was really necessary. As an end user, is my comprehension of the underlying cyberinfrastructure critical for me to evaluate the suitability of an algorithm? If it adds no additional source of bias or uncertainty, maybe not. Of course this is a big “if” as I am not confident in my ability to identify any such sources should they exist. In any case, it’s conceivable that in the age of big data GIS practitioners will need increasingly sophisticated tools to accommodate unprecedented data volume and reduce processing time.