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Actually I think the issue is that the domain scientists, quite reasonably, are used to working with some domain-assumptions. For example, when you are an atmospheric scientist talking to other atmospheric scientists, the subject of your studies and observations is the atmosphere. Doesn't need to be stated explicitly, or maybe is just inferred from the fact that elevation component of the location is >0. I'm comfortable with this. That's really why the SamplingFeature is useful. It allows you to work with a feature that is primarily defined by its shape for everyday purposes, without totally abandoning a rigorous model that recognises the fact that there is a domain feature underneath, and it is really the domain feature that has the properties. To help with this, here's some "convenience" features, that you can use as the "feature of interest" of an observation, of the "sampled feature" of a sampling-feature ;-) <https://www.seegrid.csiro.au/twiki/bin/view/CGIModel/CGIFeatureRegister#Register_content> ______ Simon.Cox@xxxxxxxx CSIRO Exploration & Mining 26 Dick Perry Avenue, Kensington WA 6151 PO Box 1130, Bentley WA 6102 AUSTRALIA T: +61 (0)8 6436 8639 Cell: +61 (0) 403 302 672 Polycom PVX: 130.116.146.28 <http://www.csiro.au> ABN: 41 687 119 230
-----Original Message----- From: Gerry Creager [mailto:gerry.creager@xxxxxxxx] Sent: Friday, 14 March 2008 10:40 AM To: Cox, Simon (E&M, Kensington) Cc: galeon@xxxxxxxxxxxxxxxx Subject: Re: [galeon] Fwd: CDM feature and point types docs I'll revisit O&M Part 2, and admit now that I gave it, at best, a cursory review last time. However, I continue to suggest that part of the problem is that the domain scientists don't all speak "geospatial" as well as they could, and make inference based less on strict definitions than preference and bias. The result is that the potential for interoperability is reduced until we can resolve the semantic issues, and these will likely not be readily resolved with an RDF document or two because of mis-communication. gerry
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