Mennis & Guo put together a brief, somewhat easy to read literature review on spatial data mining, a good starting place for those with only nominal knowledge of the topic (like me). They go over spatial data mining methods and processes as an intro and follow it up with recent (as of 2009) developments in the field and connect the methods to the reviewed articles. They end with the growing area of spatial data mining and its expanding “frontier”.
With the exception of the first bit of Section 2.2, I found the paper pretty easy to follow. I was never good at statistics but I remember enough to get through it, and the examples included in each short paragraph were helpful. The most intuitive parts to me were the mentions of remote sensing, which is not something that I would have immediately associated with spatial data mining or Big Data, but once the connections were there it made more sense and helped clarify some other things mentioned.
In the conclusion, Mennis & Guo say “Data mining is data-driven but also, more importantly, human-centered”. This is basically the foundation of Critical GIS, that GIS isn’t a set of tools to be used in a vacuum but to incorporate human knowledge/social theory, and that products of GIS and their interpretation are always influenced by some personal epistemology or ontology. It isn’t surprising that they made this conclusion, but it is an interesting inclusion in an otherwise very technical and by-the-book type of article.