Characterization data model

[Anita Richards]

Dear Francois, Mireille, Jonathan et al.,

Notes on Characterisation

I have been looking at the ALMA data model as well as other
interferometry models and general data access issues arising from
AstroGrid use cases.

I am being very pedantic because I think that this model will be very
useful and we need to make sure that there are no ambiguities which
will confuse data providers or software.

v 0.1
1.1

Axes
What is 'cinematic' - is this the temporal+spatial analogy of a
spectral+spatial data cube?

Glad to see polarimetric.

I tried to introduce velocity earlier, has it been deliberately
dropped or just deferred? It is not the same as frequency, if you have
data on a single object in multiple spectral transitions, each of
which has a velocity structure which overlaps; you make line
assignments based on position, relative intensity etc, and you might
publish a velocity spectrum or data cubes whilst the frequency data
were only available in visibility data form.  No need to add it yet if
it complicates things but I hope it hasn't been dismissed.

Tables 1 and 2

I am not sure if these are meant to contain generic terms or to be
specific examples, can this be stated?  I guess that they are just
examples but in some cases this isn't very clear - what is Quantum
Efficiency in Sensitivity - Spatial? Is  vignetting another (maybe
more widely understood) example?

One of the most important things many users (and data providers) want
to know is, what is the faintest detectable emission - commonly called
sensitivity or noise.  I think that many people will be confused that
it is not the Sensitivity of the Observable.  In many cases this will
be the Resolution of the Observable, in which case can we explicitly
call it e.g. statistical error or noise. I guess that it is actually
meant to come in as Bounds of the Observable, in which case can we
explicitly call that Max Flux, Min Flux please?

When describing a potential image/spectrum from a visibility data set,
it is useful to be able to express the fact that the input data may
have multiple spectral channels in each (sub)band. In this case
Sampling - Spectral would be the smallest spectral scale available, so
in Table 1 this is the channel width which is pixel-like - not a FWHM
(determining the Field of View, inter alia!).  The Resolution may be
different and can be a channel FWHM if spectral smoothing has been
applied without rebinning.  Not important, but I mention this in case
someone thinks that the Resolution-Spectral and Sampling-Spectral are
always the same and uses one element.

Similarly, in the Temporal domain, I suggest that Resolution and
Sampling are allowed to be different since for interferometry
the min. temporal resolution to make synthesis images is usually
considerably longer than the sampling or integration time but it is
useful to know the latter not only if you want a light curve but
because it also determins the FoV.  Whilst the user should not need to
know that Bounds-Spatial is actually a function of sampling, it will
be useful to have the information in the model since it is not
inconceivable that interferometry data providers would provide
functions to use this information.

Sensitivity - Spectral
For interferometry data, we usually provide a bandpass correction
function which is applied to data before imaging, extraction of
spectra etc.  Should an entry for Sensitivity - Spectral describe the
state of the data after applying the correction, or should it describe
the uncorrected data? I think that it should describe the state of the
data as supplied, but that will need to be made clear.

Can all the quantities be expressed as ranges (eventually functions
but never mind that now)? Most of the characterisation slots are
non-unique for potential images.  The trickiest one is how to
characterise the maximum spatial scale present as well as the minimum
(i.e. resolution). It could be done by giving a range of resolution
and relying on people knowing that larger scales are actually going to
be missing; I think that anyone who hasn't grasped that is not going
to understand a description of the visibility data in terms of uv
distances either.

Filling factor and
2.1 - bottom para on p.6 - can we drop this? I am not sure what it is
adding to the model. Systematic small gaps in coverage arise in other
situations than the ones described and are dealt with in different
ways, e.g. visibility data for an imaging field containing a pulsar
where only on-pulse data have been recorded;

3.1

We need to be careful with regard to Data Retrieval; we already have a
Registry standard. There are many differences between describing a
data archive - which may contain very heterogenous data - and
describing a single image or a collection of images (or spectra
etc. etc.) in enough detail for extraction and processing.  As far as
I can see some of the top layers of the Characterisation model could
map to the Registry model but I would like to see this done explicitly
with cut-offs.  If some aspects of the Registry model (e.g. using the
7 or so band names - radio, mm, IR...) don;t fit comfortably because
they are too coarse that isn't a problem as long as the
Characterisation and Registry models don't pretend that they are
describing the _same_ thing in different ways.

I also think that we should see VOs in general and Characterisation in
particular as being mainly aimed at providing data which will be
passed between other VO tools.  Thus 'Characterisation ... is necesary
.. but not sufficient .. also requires details of observing...'
worries me.  In many cases I hope that the Characterisation model will
be sufficient because we should be encouraging data providers to
supply data with instrumetal signatures already removed, so that other
VO tools can tackle the images etc.  Observational details should be
provided as part of giving the data a history, and we do already have
that in the Observation DM, but they are only directly relevant to
Characterisation if we have tools to use them (e.g. a special tool to
convert Chandra counts or 2MASS magnitudes to physical units).

Fig. 2

I was amused to see Observatory Location under Coverage_SPATIAL - is
this so that you at least know what hemisphere the image is in?  I
think that level of coarseness is OK for the Registry but
Characterisation should be describing specific data a bit better than
that (unless it is an all-sky map...)

best wishes

Anita





- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 
Dr. Anita M. S. Richards, AstroGrid Astronomer
MERLIN/VLBI National Facility, University of Manchester, 
Jodrell Bank Observatory, Macclesfield, Cheshire SK11 9DL, U.K. 
tel +44 (0)1477 572683 (direct); 571321 (switchboard); 571618 (fax).