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Hi Keiran: Keiran Millard wrote:
Catching up on the discussions after a week's holiday so I may be going over old ground In my opinion there seems to be a merging of issues that would benefit from a bit of separation. Firstly is the separation between the spatial position of the instrument/ship and the spatial position of the phenomena being measured, particularly wrt the Z coordinate. In some cases they may bethe same but, not all.
I think I was trying to cover the case where you want to factor out the ship position, and have the sounding be reletive to it. If you dont care about that (or it differs at each point), you could store the ship position with each sounding observation.
The other separation is to treat Point, Profile, Section and Trajectories as distinct feature types and not to collapse them. I'm taking definitions here from work of CSML (see http://ndg.nerc.ac.uk/csml/ - particularly the user manual and summarised below). In this was you can be more specialised about a given 'thing', e.g. a PointFeature doesn't require a Z attribute for measurements, whereas a ProfileFeature, by its definition does. PointFeature Single point measurement. PointSeriesFeature Time-series of single datum measurements at a fixed location in space. TrajectoryFeature Measurement along a discrete path in time and space. PointCollectionFeature Collection of distributed single datum measurements at a particular time ProfileFeature Single 'profile' of some parameter along a vertical line in space. ProfileSeriesFeature Time-series of profiles on fixed vertical levels at a fixed location RaggedProfileSeriesFeature Time-series of unequal-length profiles, but on fixed vertical levels, at a fixed location SectionFeature Series of profiles from positions along a trajectory in time and space. RaggedSectionFeature Series of profiles of unequal length along a trajectory in time and space
We've been talking about comparing with CSML, perhaps we should go through that exercise now?
Incidentally I should add that I've been using the current ObsConvention for storing fluvial data. There are lots of similarities with marine data, but the distribution of gauging stations are a bit like having a collection met stations. In my use case I have 'n' gauging stations along a river network (=> different heights) measuring river flow (at different depths), river depth, river temperature and various chemicalmeasurements.
Interesting. This does sound like a station collection. is there a z dimension to the sampling, or just a z coordinate at each guage station?
Best regards Keiran
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