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#104: Clarify the interpretation of scalar coordinate variables -----------------------------+---------------------------------------------- Reporter: jonathan | Owner: [email protected] Type: enhancement | Status: new Priority: medium | Milestone: Component: cf-conventions | Version: Resolution: | Keywords: -----------------------------+---------------------------------------------- Comment (by jonathan): Dear John CF 1.6 talks about scalar coordinate variables in section 9.2: If there is only a single feature to be stored in a data variable, there is no need for an instance dimension and it is permitted to omit it. The data will then be one-dimensional, which is a special (degenerate) case of the multidimensional array representation. The instance variables will be scalar coordinate variables; the data variable and other auxiliary coordinate variables will have only an element dimension and not have an instance dimension, e.g. data(o) and t(o) for a single timeSeries. Your first example, with `data(sample)`, `lat(sample)`, `lon(sample)` and `time(sample)`, could be a collection of point data, with `sample`, which is (much!) greater than one, being the instance dimension (i.e. the number of points). No scalar coordinate variables are involved in that case. Alternatively, it could be a single trajectory feature, in which `sample` is the element dimension (the number of points along the trajectory). Again, there are no scalar coordinates. Your second example, with `data(sample)`, `lat`, `lon` and `time(sample)`, could be a single timeseries feature, in which `sample` is the element dimension (the number of times in the timeseries). This has two scalar coordinate variables. Following this ticket, they would be regarded as logically equivalent to `lat(lat)` and `lon(lon)`, as though the data were dimensioned `data(sample,lat,lon)` with `lat=1` and `lon=1`. This is a valid and logically equivalent way of representing a single timeseries. If it's actually not a timeseries, but still a collection of points which happen to be coincident (?), you have to dimension `lat` and `lon` with `sample`, in order to agree with Table 9.1. Thus, this ticket doesn't appear to cause a problem for DSGs, but I expect we will have to do some more thinking about the logical data model. With that caveat, is the ticket OK as it stands? Best wishes and thanks Jonathan -- Ticket URL: <https://cf-pcmdi.llnl.gov/trac/ticket/104#comment:42> CF Metadata <http://cf-pcmdi.llnl.gov/> CF Metadata This message came from the CF Trac system. To unsubscribe, without unsubscribing to the regular cf-metadata list, send a message to "[email protected]" with "unsubscribe cf-metadata" in the body of your message.
