The ingredients are existing data that may or may not have a spatial component, your understanding of said data at your disposal and finally PostGIS and the bevvy of functions that it ships with.
No need to venture into the kitchen or even ignite your stove; 'Cooking' here refers to the practice of using select bits of data from an experiment to get results that you should be getting, even if your experiment is going awry.
There are times when you need spatial data for a given purpose, but sending a team out into the field is not practical given existing constraints. In cases where accuracy need not be sub decameter then there are ways and means to generate spatial data for visualization purposes that can be just good enough.
PostGIS has a plethora of functions to help you get to that point of having spatial data that is just good enough, especially for visualization.
In this talk, I will show how, for real instances, PostGIS was used to generate the data needed and how in some cases, the data was spatially accurate to within 10 meters.
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