I'm learning about techniques to ensure GIS data quality. Googling around, I've found a few papers about theory and best practices (here and here), and a couple of short presentations about the topic using ESRI tools (here and here)

For example, the concepts of "tolerance" and "precision" are globally defined in ArcGIS (I didn't know it), and I think Oracle globally manages the concept of "tolerance" too. On the other hand, as far as I know, PostGIS doesn't expose the user-defined precision model supported by GEOS, and simply uses the full precision of floating point numbers.

So, my question is: what PostGIS [topology] provided tools may be used for data quality assurance? Has anyone experience with this topic? Or maybe I'm just selecting the wrong tool for this.

  • Hi. I've changed the title of this thread to the actual question you're asking in the text because I think it's a more suitable question which can be answered objectively. – underdark Dec 1 '13 at 19:40

For vector shifts you can buffer within a radius, anything remaining would need a manual quality assurance. Quality tends to have a manual element unless you are just testing for regression. Address points same operation. Raster look for differences in values tweening pooled versioned data, same with math, any way that is enough for a light overview. Best in conjunction with scripting and metadata of datasets hosting on postgresql with triggers, or Oracle.

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