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<p>This email was sent yesterday in another thread.</p>
<p>Following Markus' recommendation I open now a new thread for this
discussion of the "astronomical source observation results" use
cases.</p>
<p>Cheers</p>
<p>François<br>
</p>
<p>Dear all,<br>
</p>
<ul>
<li>When I proposed VEP0001 immediately after Groningen Interop I
could not imagine that such a controversy discussion would
occur. <br>
</li>
<ul>
<li>Before considering the use case we have I would like to go
back to the current usages of DataLink I know.</li>
<li>Then go back to the "new" use case</li>
<li>And then check some of the proposed solutions on this list</li>
<li>And then argue for my preference</li>
</ul>
<li>According to DataLink 1.0 <br>
</li>
<ul>
<li>the semantics field contains a "Term from a controlled
vocabulary describing the link" as stated in Table 1 and </li>
<li>section 3.2.6 reads :</li>
<li>"The semantics column contains a single term from an
external RDF vocabulary that describes the meaning of this
linked resource relative to the identified dataset. The
semantics column is intended to be machine-readable and assist
automating data retrieval and processing."</li>
<li>Let's call the initial thing we are starting from and to
which we want to link resources "Main" and the various linked
resources "Target".</li>
<ul>
<li>Two remarks :</li>
<ul>
<li>The text in section 3.2.6, consistently with the use
cases described in the introduction considers that the
"Main" is a dataset</li>
<li>The semantics field describes globally what the target
is "with respect to the main"</li>
</ul>
<li>More classical is the group of columns access_URL ,
content_type, content_length which references and describes
the "Target" itself (independently from the "Main")</li>
<li>Now I tried to look a little bit at the current usage of
DataLink using Aladin DeskTop as a client and the three
following SIAP2 servers </li>
<ul>
<li>CADC : <br>
</li>
<ul>
<li>In the example I found The DataLink service had "this"
in semantics for the full retrieval of the dataset,</li>
<li> "cutout" for a SODA service <br>
</li>
<li>and a couple of "auxiliary" Rows for additional data
such as PSF images, etc...</li>
<li> cutout is related to the fact that it is a service,
described as "service descriptor". Aladin opens a
specific menu in that case while it downloads the
datasets in the other cases according to the fact its
"content_type" is application/fits</li>
</ul>
<li>GAVO : <br>
</li>
<ul>
<li>In the example I found The DataLink service had "this"
in semantics, and also "preview", "proc" and "science".</li>
<li> "this" and "preview" are self-explanatory. <br>
</li>
<li>"proc" is actually related to a SODA service (should
be "cutout" maybe ?) <br>
</li>
<li>and science is a new term proposed by Markus to take
into account that it is related science data </li>
</ul>
<li>CASDA : <br>
</li>
<ul>
<li> In the example I found, "Main" was a cube. It had in
semantics several "this", a "cutout and a "proc".</li>
<li> Each "this" row allowed the retrieval of the full
dataset from different servers sometimes in synchronous
mode and sometimes in asynchronous mode.</li>
<li> The "cutout" row is related to a SODA service. <br>
</li>
<li>The "proc" row links to a SODA-like service extracting
a single integrated spectrum from the data cube.</li>
</ul>
</ul>
<li>This shows that semantics is not only there in DataLink
for selection among rows in the {links} response table but
also helps the client to figure out what to do with the
target in combination with content-type, content_length and
service descriptor (if any is defined). </li>
<li>This also shows that semantics terms work like a flat
vocabulary despite their tree presentation in the rdf
document. </li>
<ul>
<li>Auxiliary is a head term for bias, dark, flat but can
also be used on its own for non registered cases.</li>
<li>Same for proc and cutout. </li>
<li>The tree structure of the vocabulary is actually only
descriptive. It's not functional at the time of writing. </li>
</ul>
</ul>
</ul>
<li>New Uses cases:</li>
<ul>
<li>Short after DataLink became an official IVOA recommendation,
some data providers were interested in using the DataLink
functionalities for use cases where the "Main" was a source in
a catalogue.</li>
<li> This can work, of course, and proposal are currently
discussed to integrate these use cases within the scope of
DataLink-1.1, but no adapted semantics terms describing this
kind of relationship between the "Main" and the "Target" were
available in the previous vocabulary.</li>
<li>Often the "Target" related to the source "Main" is the
result of an observation of the source, actually a dataset
(image, spectrum, lightcurve, etc..)</li>
<ul>
<li> In vizieR we had a similar situation for what we call
"associated data" to catalogue "rows". </li>
<li>these "associated data" can indeed be images, TimeSeries,
cubes, spectra...</li>
</ul>
<li> Hence the VEP0001 proposal as it was presented in October
the 15th<br>
</li>
<ul>
<li>An associated_image is actually "an image of main" which
is a source.</li>
<li> An associated_lightcurve is similarly " a light curve of
Main" which is a source.</li>
</ul>
<li> It is to be en-lighted that this term informs the client
that it is an image or a light curve and that it is an
Observation result of the source. </li>
<li>The proposal to define an item in the associated branch for
each value of dataproduct_type and even more for each subtype
of TimeSeries introduced the idea to combine associated_data
with the ObsCore vocabulary.</li>
<ul>
<li> It was pointed out (By Markus) that other head terms such
has "progenitor" or "derived" could need this too and this
could lead to a combinatory explosion. </li>
</ul>
<li>By the way the term "associated_data" itself has been
criticized to describe the concept of observation result of a
source.</li>
</ul>
<li>The 4 concepts proposal</li>
<ul>
<li>Ada proposed to separate the description of the links in 4
different concepts</li>
<ul>
<li>"4 independent levels or categories: </li>
<li>Level 0 - Data-format (fits, VOTable, PDF, png, …)</li>
<li>Level 1 - Data-type (tabular, image, spectrum, cube, text,
…)</li>
<li>Level 2 - Data-information (Documentation, Calibration,
Log, Preview, …)</li>
<li>Level 3 - Data-relation (Derived from, Progenitor of,
Sibling of, ...)"</li>
</ul>
<li>I think this introduces an effort for a real data modelling
of DataLink. It would be obviously a major improvement in the
way we link resources. But it may take sometimes to achieve.</li>
<li>At the moment I don't see a clear distinction between level
2 and level 3 because the "information" we have in the
"Target" is always "relative" to a "Main" so not that far
from level 3. At least it may be sometimes difficult to know
in which "level" falls a given category value </li>
<li>On the other side for links to dynamical services I am not
sure to which category their characterization belongs. Is
that a fifth level to add ? Data-type in the context of
DataLink should have a much wider scope than ObsCore
"dataproduct_type" because there are targets which are not
data products. Various metadata, auxiliary data, texts, plots,
etc... If data_product_type is standardized, what about the
other stuff ? <br>
</li>
<li>To me It looks like the levels proposed by ada (an maybe a
few others) are more like matrix description tant a flat one.
<br>
</li>
<li>Account taken of all the above, I think the levelling of the
categories can be a project for DataLink 2 which will be
really interesting. if we want to have a quick solution I
think we have to consider more modest solutions.</li>
</ul>
<li>Among different Proposals :</li>
<ul>
<li>I see two possible simple solutions to tackle the use case</li>
<ul>
<li>go back to a simplified version of VEP001. </li>
<ul>
<li>Instead to reproduce the full ObsCore "dataproduct_type"
variability we only define the terms we currently need
and we will see in the future if we need more.</li>
<li>At the same time I get rid both of "associated_data" and
"sibling" head term and choose to use
"Observation_Result_of_source"</li>
<li>ESO and SVO use cases : "image_of_source"",
"Spectrum_of_source"</li>
<li>TimeDomain/Gaia use cases : "LightCurve_Of_Source",
"RadialVelocityCurve_Of_Source", "Movie_Of_Source",
"SpectroChronogram_Of_Source"</li>
<ul>
<li>"TimeSeries_Of_Source" may be used as a head term for
the four above, or when we don't know exactly what is
varying in time.</li>
</ul>
</ul>
<li>adopt proposal made by Pat Dowler. Use the media type in
content_type to give the type or product type using the
parameter "content="</li>
<ul>
<li>application/fits;content=image</li>
<li>application/fits;content=spectrum</li>
<li> application/fits;content=lightcurve or
application/fits;content=timeseries;subtype=lightcurve</li>
<li>application/fits;content=movie or
applicaton/fits;content=timeseries;subtype=movie</li>
<li>etc ...</li>
</ul>
<ul>
<li>the standard structure of media types allows to reuse
the current "dataproduct_type" vocabularu as a vlaue of
the content parameter and then to use an additional
"subtype" parameter, or alternatively to directly use the
timseries subtype in "content=".</li>
<li>a variant would be to create a new dataproduct_type
parameter in the media type when appropriate<br>
</li>
<li> If we adopt that, semantics will only be
"Observation_Result_of_source" in parallel for all these
possibilities<br>
</li>
</ul>
<li> In the first solution we directly introduce some kind of
datatype in the "meaning of target relative to the main"
semantics field which I think it's fine except that it
doesn't explicitely reuse ObsCore dataproducttype.</li>
<li>In the second solution clients will have to parse the
media type to discover not only the format of the target but
also its content. We still have to decide how to do subtype.
<br>
</li>
<ul>
<li>This has probably to be explicitly explained in the next
DataLink-1.1 version</li>
</ul>
</ul>
<li>What do implementers / service providers prefer ?</li>
</ul>
</ul>
<p><br>
</p>
<p>I wish you all happy holidays for the coming days</p>
<p>Cheers</p>
<p>François<br>
</p>
<p><br>
</p>
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