Product-type as a SKOS vocabulary

[BONNAREL FRANCOIS]

Dear Markus
Thanks for your answer
Le 10/01/2022 à 10:48, Markus Demleitner a écrit :
> Dear François,
>
> On Wed, Jan 05, 2022 at 04:50:59PM +0100, BONNAREL FRANCOIS wrote:
>> If we want to organize dataproducts in a network we have to think what are
>> the properties  able to characterize the dataproducts and see what are the
>> most common cases
> As usual, I'd like to come from use cases; it is certainly valuable
> to have a formal and solid understanding of the full domain, but in
> order to come up with vocabularies (or, perspectively, ontologies)
> that people can work with, I am sure we will need to agree which
> parts of a full mapping ought to enter into a given semantic
> resource -- and which might be dispensable *for that specific*
> semantic resource.
>
> For product-type, I think we have two basic use cases:
>
> (A) discovery of artefacts relevant to a defined research project;
> that's the obscore use case where people would, for instance, look
> for spectrally resolved data and want to filter out images and time
> series that are not spectrally resolved.
>
> (B) routing of some artefact to the proper (SAMP) client; that's the
> datalink use case where a user might simply double-click a datalink
> row, and it'll open in TOPCAT when it's a table, except if it's
> really a spectrum, in which case it would preferably go to Splat, and
> it would go to Aladin if it's an image (or perhaps ds9 or whatever,
> depending on the user session).
>
> Taking François' schema:
>
>>     I see at least 4 type of properties
>>        1 )  What are the independent variables (in the context of  functional
>> dependencies of variables with respect to others)? for example if time is
>> independent we have a TimeSeries , if spectral coordinate is independent we
>> have a spectrum
>>        2 )  What are the dependent variables. In case of TimeSeries If it's a
>> photometric quantity, it could be a lightcurve, if it's radial velocity it
>> is a velocity curve.
>>        3 ) Are the independent variable sparsed or regularly sampled ?
>>        4 ) The organization : is this a table (where the different quantities
>> of a given measurement are explicitly recorded) or a bitmap where the range
>> of a dependent measurement  in the dependent measurement array is a function
>> of the independent variables
> I think (1) and (2) are obviously relevant to both cases.
>
> For (3) I'm less certain.  Use case (A), I would claim, actually
> requires making this ignorable.  If I'm looking for a spectrum of a
> source, I'm happy to find anything spectrally resolved, and I'd
> rather like to avoid having to remember to somehow include both
> sparse and non-sparse datasets.  For use case (B), it is conceivable
> that certain clients can only deal with regularly sampled data (e.g.,
> an image, which I'd like to send to Aladin) and others only with
> sparse data (e.g.  spatially resolved events, which might better be
> dealt with in TOPCAT).  Is this really something we'd want to (be
> able to) automatically handle?  I'm currently leaning towards a
> tentative "no", but I could certainly be convinced I'm wrong here.
>
> Item (4) is I think closely related to (3), though it's perhaps still
> a bit more technical and father removed from scientific content. My
> example here would be IRAF-type spectra (which are 1D bitmaps) versus
> IVOA SDM spectra (which are tabular).  And my conclusion would be
> rather analogous to item (3), also because SAMP doesn't allow to
> tell one from the other at this point.
>
> So, I think what we should come up with are (plausible) stories of
> data usage.  These could guide us whethere (3) and (4) need to be
> reflected in product-type -- and how we don't spoil (A) if we want to
> have them for (B).

I may try two slides on such possible stories on Monday if there is some 
time left in the meetong semantics is organizing.

Otherwise later

Cheers

François

>
>            -- Markus