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Saturday, October 11, 2008

Mapping Center : I remember making this feature class...I wonder why?


I remember making this feature class...I wonder why?

Have you ever wondered where a feature class came from as you've browsed over one of your geodatabases in ArcCatalog? I think most of us have, and probably more often than we'd like to admit. In the example shown here to the left, I made these datasets a few weeks ago, and I have no idea what "GN" means, and if or how I selected, simplified, or dissolved the data.

There are a couple of things we can do to avoid that puzzled feeling: standardize your feature class naming convention; standardize your geoprocessing.  With the naming convention, I started doing the right thing here, but failed to follow through and leave myself the necessary clues. The data in the image above was also the result of a complex workflow, so rather than start with that, let's cover the basics. 

Use Standard Feature Class Names

My example here fell apart because I was using the framework for a standard naming convention, but my naming convention  wasn't entirely standard. The framework that I was using creates feature class names based on who first published the data, and then what the data represents.  So, NHD_Flowlines means I got the data from NHD (USGS National Hydrography Dataset), and the data represent stream flow lines.

Second, while my example started off with a good name, I had not developed a standard convention for any of the processes that I ended up doing to my NHD_FlowlinesPlus dataset to produce my cryptically named datasets.  Before I explain what I should have done, I'll share the standard naming conventions I use:

  • Scale: _24K, 100K, 250K, 1M, 2M:  The first example means the data are either captured or generalized to be at a resolution appropriate for 1:24,000 scale maps.  The 1M means 1:1,000,000.  This is a relatively good convention; I say relatively, because the meaning is map product and data-production specific.  The product in this case is an on-screen map, and I use different data production methods from that which I would use for a printed map.
  • Mapping Purpose: _lab _sym, _master:  This refers to how I use these data in a map. If it is for labeling only (_lab),  for symbology only (_sym), or a dataset that I use to derive cartographic data, (_master). The context I have found most useful to use these abbreviations is ArcGIS Server, my goal there is to optimize the data to the greatest extent possible to improve drawing performance.  I covered how to set that data up in a recent blog entry on tips for improving drawing performance.
  • Vintage: _03, _07, Mar_08, Jun_06, etc.:  This is just a two-digit year so I can tell when data are captured. For imagery, it's useful to add at least the month or even the capture date to the name as seasonality often carries significant meaning.

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