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#113: Review of CF feature types
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Reporter: mgschultz | Owner: cf-conventions@…
Type: | Status: new
enhancement | Milestone:
Priority: medium | Version:
Component: cf- | Keywords: featureType, Grid, Point,
conventions | TimeSeries, Profile
Resolution: |
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Comment (by graybeal):
Replying to [comment:17 mgschultz]:
> I admit that I had to read this twice to see the value of your comments
;-)
Yeah, uh oh, my bad. :-) It's always hard for me to come back into this
material and understand even my own details.
> I am not really willing to exchange the figure for now, though - maybe
some imagination should be left to the reader?
Depends on whether the emphasis is narrative or precision. Because these
are subtle and important distinctions, I lean toward complete and
consistent materials, so the user can easily create a mental model that
exactly matches the one you want them to have.
> What has been in CF so far has been rather incomplete I would argue (and
this was the starting point of this track ticket).
Yes, completeness has been a problem with many of these models, IMHO. I
found the increase in set size helpful.
> I would even go as far as to suggest that the current CF types should be
renamed according to this new scheme -- in this context one should of
course attempt a mapping.
Possible yes to renaming, though I'd want to review the names attentively
with the mappings in hand.
As an example of my naming views, I concur that reusing 'rectified' with
different meaning is '''not''' OK; this contributed to my confusion with
the drawings. I agree rectilinear is not perfect, but it's OK for me. I
think 'aligned' is much better but still carries a hint of linearity (more
so if 'aligned grid'). Other possibilities could be explored (oriented,
parallel, …).
Finally, re meta usefulness for CF, I think the key question is: Do the
enhancements in your model address the goal of the CF section 9, or go
beyond? (And if the latter, should the goal of the section be expanded?)
The mapping would help me assess that. The fact that CF is storage-
oriented, perhaps downplays the value of the semantically richer
descriptions in your model. That is, if two feature models have different
conceptual origin, but are stored exactly the same way, how much does CF
care, and how much should it care?
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Ticket URL: <http://kitt.llnl.gov/trac/ticket/113#comment:22>
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