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</o:shapelayout></xml><![endif]--></head><body bgcolor=white lang=CS link=blue vlink=purple><div class=WordSection1><p class=MsoNormal><span style='color:windowtext;mso-fareast-language:EN-US'>Hi,<o:p></o:p></span></p><p class=MsoNormal><span style='color:windowtext;mso-fareast-language:EN-US'><o:p> </o:p></span></p><p class=MsoNormal><span style='color:windowtext;mso-fareast-language:EN-US'>Inline.<o:p></o:p></span></p><p class=MsoNormal><span style='color:windowtext;mso-fareast-language:EN-US'><o:p> </o:p></span></p><p class=MsoNormal><span style='color:windowtext;mso-fareast-language:EN-US'>Cheers,<o:p></o:p></span></p><p class=MsoNormal><span style='color:windowtext;mso-fareast-language:EN-US'><o:p> </o:p></span></p><p class=MsoNormal><span style='color:windowtext;mso-fareast-language:EN-US'>Jiri<o:p></o:p></span></p><p class=MsoNormal><span style='color:windowtext;mso-fareast-language:EN-US'><o:p> </o:p></span></p><div style='border:none;border-left:solid blue 1.5pt;padding:0cm 0cm 0cm 4.0pt'><div><div style='border:none;border-top:solid #E1E1E1 1.0pt;padding:3.0pt 0cm 0cm 0cm'><p class=MsoNormal><b><span style='color:windowtext'>From:</span></b><span style='color:windowtext'> François Bonnarel [mailto:francois.bonnarel@astro.unistra.fr] <br><b>Sent:</b> Monday, July 17, 2017 9:57 AM<br><b>To:</b> Jiří Nádvorník <nadvornik.ji@gmail.com>; mireille.louys@unistra.fr; dm@ivoa.net; voevent@ivoa.net; dal@ivoa.net<br><b>Subject:</b> Re: [timeDomain: model for Time series] discussion on Timeseries Data model Note / ND-point .... or not ??? !!!<o:p></o:p></span></p></div></div><p class=MsoNormal><o:p> </o:p></p><p>Thanks, Jiri<o:p></o:p></p><p><o:p> </o:p></p><p>Again let's clarify what we think. see in text<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><div><p class=MsoNormal>Le 13/07/2017 à 16:03, Jiří Nádvorník a écrit :<o:p></o:p></p></div><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><div><p class=MsoNormal style='mso-margin-top-alt:auto;mso-margin-bottom-alt:auto'>Hi all,<o:p></o:p></p><p class=MsoNormal style='mso-margin-top-alt:auto;mso-margin-bottom-alt:auto'> <o:p></o:p></p><p class=MsoNormal style='mso-margin-top-alt:auto;mso-margin-bottom-alt:auto'>Thank you for nice summary, Francois.<o:p></o:p></p><p class=MsoNormal style='mso-margin-top-alt:auto;mso-margin-bottom-alt:auto'> <o:p></o:p></p><p class=MsoNormal style='mso-margin-top-alt:auto;mso-margin-bottom-alt:auto'>My comments inline.<o:p></o:p></p><p class=MsoNormal style='mso-margin-top-alt:auto;mso-margin-bottom-alt:auto'> <o:p></o:p></p><p class=MsoNormal style='mso-margin-top-alt:auto;mso-margin-bottom-alt:auto'>Cheers,<o:p></o:p></p><p class=MsoNormal style='mso-margin-top-alt:auto;mso-margin-bottom-alt:auto'> <o:p></o:p></p><p class=MsoNormal style='mso-margin-top-alt:auto;mso-margin-bottom-alt:auto'>Jiri <o:p></o:p></p><p class=MsoNormal style='mso-margin-top-alt:auto;mso-margin-bottom-alt:auto'> <o:p></o:p></p><p class=MsoNormal style='mso-margin-top-alt:auto;mso-margin-bottom-alt:auto'> <o:p></o:p></p><div><div><div><p class=MsoNormal style='mso-margin-top-alt:auto;mso-margin-bottom-alt:auto'><b>From:</b> <a href="mailto:dm-bounces@ivoa.net">dm-bounces@ivoa.net</a> [<a href="mailto:dm-bounces@ivoa.net">mailto:dm-bounces@ivoa.net</a>] <b>On Behalf Of </b>François Bonnarel<br><b>Sent:</b> Wednesday, July 12, 2017 6:11 PM<br><b>To:</b> <a href="mailto:mireille.louys@unistra.fr">mireille.louys@unistra.fr</a>; <a href="mailto:dm@ivoa.net">dm@ivoa.net</a>; <a href="mailto:voevent@ivoa.net">voevent@ivoa.net</a>; <a href="mailto:dal@ivoa.net">dal@ivoa.net</a><br><b>Subject:</b> [timeDomain: model for Time series] discussion on Timeseries Data model Note / ND-point .... or not ??? !!!<o:p></o:p></p></div></div><p class=MsoNormal style='mso-margin-top-alt:auto;mso-margin-bottom-alt:auto'> <o:p></o:p></p><p>Dear all,<o:p></o:p></p><p>This is a follow-up of these two emails<o:p></o:p></p><p><a href="http://mail.ivoa.net/pipermail/dm/2017-July/005583.html">http://mail.ivoa.net/pipermail/dm/2017-July/005583.html</a><o:p></o:p></p><p>and<o:p></o:p></p><p><a href="http://mail.ivoa.net/pipermail/dm/2017-July/005594.html">http://mail.ivoa.net/pipermail/dm/2017-July/005594.html</a><o:p></o:p></p><p>which are discussing chapter 4 of TimeSeries Data Model IVOA note within the scope of the TimeDomain effort summarized by Ada there:<o:p></o:p></p><p><a href="http://mail.ivoa.net/pipermail/dm/2017-July/005581.html">http://mail.ivoa.net/pipermail/dm/2017-July/005581.html</a><o:p></o:p></p><p class=MsoNormal style='mso-margin-top-alt:auto;mso-margin-bottom-alt:auto'>Discussed issue: do we need ND-points or not ?<br><br>Reference : Laurent's diagram in email (<a href="http://mail.ivoa.net/pipermail/dm/2017-July/005581.html">http://mail.ivoa.net/pipermail/dm/2017-July/005581.html</a>) and CubeDM draft from <a href="http://volute.g-vo.org/svn/trunk/projects/dm/CubeDM-1.0/doc/WD-CubeDM-1.0-20170203.pdf">http://volute.g-vo.org/svn/trunk/projects/dm/CubeDM-1.0/doc/WD-CubeDM-1.0-20170203.pdf</a> (last version)<br><br>In figure 4 of Jiri's note, SparseCube doesn't relate to the ND-point class as it is the case in the IVOA sparse cube data model project.<o:p></o:p></p><p class=MsoNormal style='mso-margin-top-alt:auto;mso-margin-bottom-alt:auto'><b><i>[[Jiri Nadvornik]] The problem we had with the ND-point is that it holds complete metadata for each individual point of the time series, so also the statistical distribution would need to go here (which is not really related to a point, but rather to an axis). And the metadata about spectral points or photometry points can be kept in the Spectral DM or Photometry DM metadata, so in the end we realized that the ND-point class was empty.</i></b><o:p></o:p></p></div></div></blockquote><p class=MsoNormal><b><i>Again, I'm trying to start from what is in the CubeDM draft. In my understanding ND-point doesn't seem to contain any axis metadata and is only gathering a set of individual values contained in the DataAxis instances. If we have a "tabular vision" of our TimeSeries ND-point is modeling the content of a row. In an ND-Point instnace we will have the Time DataAxis value and any other corresponding DataAxis values : Flux, magnitude , Position + velocity, etc... </i></b><b><i><span style='color:windowtext'><o:p></o:p></span></i></b></p><p class=MsoNormal><b><i><span style='color:windowtext'>[[Jiri Nadvornik]] I have cut the part of TimeSeriesCube DM that copes with this – attached TimeSeriesCube DM detail. To put the „tabular vision“ to the context there – the columnRef is representing table columns (1 column is 1 axis) and the TimeSeriesCube class is collecting these axes while knowing whether they are dependent or independent on the time axis. So while not keeping relationships between each individual axis, we are keeping the information about their dependency.</span></i></b><o:p></o:p></p><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><div><div><p class=MsoNormal style='mso-margin-top-alt:auto;mso-margin-bottom-alt:auto'><br>The ND-point class gathers several DataAxis (or Observable) containers for measurements on a given data Axis to represent a "point" or "event" in the data space.<o:p></o:p></p><p class=MsoNormal style='mso-margin-top-alt:auto;mso-margin-bottom-alt:auto'><b><i>[[Jiri Nadvornik]] My understanding here was that it gathers several one ND-point gathers 1 *point* from each DataAxis, not the whole DataAxis – can somebody please verify one or the other?</i></b><o:p></o:p></p></div></div></blockquote><p class=MsoNormal><b><i>Yes ND-point gather 1 value from each DataAxis</i></b><br><br><o:p></o:p></p><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><div><div><p class=MsoNormal style='mso-margin-top-alt:auto;mso-margin-bottom-alt:auto'><br>On Jiri's figure a set of "CubeAxis" is directly related to "SparseCube". This doesn't imply explicitly a relationship between each of these "CubeAxis" instances and doesn't even imply that each of these "CubeAxis" will have the same number of instances.<o:p></o:p></p><p class=MsoNormal style='mso-margin-top-alt:auto;mso-margin-bottom-alt:auto'><b><i>[[Jiri Nadvornik]] Correct. We did not consider relationships between individual axes. While photometry axis will usually have the same amout of points as the time axis, we will have only several bands on the spectral axis. Can also the spatial axis have fewer elements than the time axis (I don’t have different spatial coordinates for every point of the light curve)?</i></b><o:p></o:p></p></div></div></blockquote><p class=MsoNormal><b><i>Yes you may not have for coordinates. But at least one the other DataAxis than time should be sampled and dependant from time. Actually ND-point is modeling this dependance</i></b><b><i><span style='color:windowtext'><o:p></o:p></span></i></b></p><p class=MsoNormal><b><i><span style='color:windowtext'>[[Jiri Nadvornik]] If the ND-point is holding just points and doesn’t know about axes and their metadata, it does not know about any dependency – that should be for the Cube to decide, because it knows the context.. As you described it, the ND-point seems to me just a data structure that I use for the serialization inside a table (the row, putting it somewhere below the ColumnRef in the attached image), but the question is whether this should still be part of the data model or it’s putting too much restriction..<o:p></o:p></span></i></b></p><p class=MsoNormal><b><i><span style='color:windowtext'><o:p> </o:p></span></i></b></p><p class=MsoNormal><b><i><span style='color:windowtext'>E.g., the spectral axis can have rather complex points (min, max, midpoint wavelength, band_name to start with) – so should all of these be part of the ND-point or just a reference (band_name) while storing the rest of the information elsewhere in the serialization (to not store duplicate data in the ND-points)? If we say that the ND-point is mandatory, we kill these better data structures right away..<o:p></o:p></span></i></b></p><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><div><div><p class=MsoNormal style='mso-margin-top-alt:auto;mso-margin-bottom-alt:auto'><br>So I am wondering if we should not reintroduce the ND-point feature between "SparseCube" and "CubeAxis" or "DataAxis". What do you think ?<o:p></o:p></p><p class=MsoNormal style='mso-margin-top-alt:auto;mso-margin-bottom-alt:auto'><b><i>[[Jiri Nadvornik]] My suggestion would be to have the Cube DM hold metadata for axis statistical distribution</i></b><o:p></o:p></p></div></div></blockquote><p class=MsoNormal><b><i>ObsDataSet and SparseCubeDataset allready have a lot of general metadata (for example the characterisation is part of ObsDataSet, and the cordinate Mapping and System is in SparseCubeDataSet. If we need per axis statistics it should be added somewhere there, I guess</i></b><b><i><span style='color:windowtext'><o:p></o:p></span></i></b></p><p class=MsoNormal><b><i><span style='color:windowtext'>[[Jiri Nadvornik]] Well, modelling a generic statistical distribution won’t be an easy task and the resulting data model might become pretty complex. Why not start it as a separate effort so we don’t need to wait and synchronize it with such a huge model as ObsDataSet?<o:p></o:p></span></i></b></p><p class=MsoNormal><b><i><br><br>Cheers<br>François<br><br></i></b><o:p></o:p></p><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><div><div><p class=MsoNormal style='mso-margin-top-alt:auto;mso-margin-bottom-alt:auto'><b><i>(see Quantity class in TimeSeriesCube UML - <a href="https://volute.g-vo.org/viewvc/volute/trunk/projects/time-domain/time-series/time-series-cube/ivoa-note-1.0/">https://volute.g-vo.org/viewvc/volute/trunk/projects/time-domain/time-series/time-series-cube/ivoa-note-1.0/</a> ) and the metadata about the measurements in what we already have – Photometry DM, spatial and time in STC, Spectral DM… but both types of metadata separately for each axis, not for one ND-Point class.</i></b><o:p></o:p></p><p class=MsoNormal style='mso-margin-top-alt:auto;margin-bottom:12.0pt'><br><br>François (after discussions with Laurent, Mireille and Ada on this topic)<o:p></o:p></p><pre> <o:p></o:p></pre><pre> <o:p></o:p></pre><pre> <o:p></o:p></pre><p class=MsoNormal style='mso-margin-top-alt:auto;margin-bottom:12.0pt'><o:p> </o:p></p><div><p class=MsoNormal style='mso-margin-top-alt:auto;mso-margin-bottom-alt:auto'>Le 12/07/2017 à 10:57, Mireille Louys a écrit :<o:p></o:p></p></div><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><p class=MsoNormal style='mso-margin-top-alt:auto;mso-margin-bottom-alt:auto'>Dear DM and Time Domain followers, <br><br>I am trying, together with my CDS colleagues, to recap on the various DMs available in the IVOA and understand the possible links between the future Time Series Model ( as sketched in Jiris's Note) and existing DMs like ND-Cube and STC 2.<br><br>Here is a graph proposed by Laurent Michel to clarify the links in 3 main parts : <o:p></o:p></p><ul type=disc><li class=MsoNormal style='mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;margin-left:0cm;mso-list:l0 level1 lfo1'><i>DataSetMetadata DM</i>, which has the main ObsDataset Class ,<o:p></o:p></li><li class=MsoNormal style='mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;margin-left:0cm;mso-list:l0 level1 lfo1'><i>ND-CubeDM</i>, which defines a SparseCubedataset<o:p></o:p></li><li class=MsoNormal style='mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;margin-left:0cm;mso-list:l0 level1 lfo1'><i>TimeSerieCubeDM</i>, which highlights the special properties of a Cube depending on a Time axis<o:p></o:p></li></ul><p class=MsoNormal style='mso-margin-top-alt:auto;margin-bottom:12.0pt'>I think this is essential to highlight the inheritance path between these 3 DM building blocks: <br>a TimeSeriesCube <is a > NDCubeDM::SparseCubeDataset<br>a NDCubeDM::SparseCubeDataset <is a > DatasetMetadaDM::ObsDataset<br><br>ObsDataset has a <i>dataproduct_type</i> attribute which allows to discover all dataproducts of type ' timeseries'. <br>this provides the container object for time-dependent data.<br><br>If we need to select <i>timeseries dataproducts</i> according to some properties extracted from their data we can:<br> - reuse what Obscore DM provides to explain general axes properties<br>target_name, s_region, s_resol, t_min, t_max, t_resol, em_min, em_max, em_resol, etc. are the basic properties for discovery<br><br> - provide a richer description of the TimeAxis and ObservableAxis. <br>For that , extracting a statistical profile from the data contained in the Cube could do the job. <br>this means to access and analyse the Data part in ND-Cube , i. e the ND-Points gathered in a SparseCube Object<br><br>I guess more properties can be exposed to qualify the axes present in the Timeseries dataset , but for the moment , I see some overlap of notions between <br>CharacterisationDM::ObservableAxis, STC2.0::CoordMeasurement (??) and TimeSerieCubeDM::CubeAxis.<br><br>This would be great if we could sort this out, <br>but currently , I would appreciate your feedback on the attached diagram , in order to proceed on the data model structure. <br><br>Cheers, Mireille ( after discussions together with Laurent, François, Ada) <br><br><o:p></o:p></p><pre>-- <o:p></o:p></pre><pre>--<o:p></o:p></pre><pre>Mireille Louys<o:p></o:p></pre><pre>CDS Laboratoire Icube <o:p></o:p></pre><pre>Observatoire de Strasbourg Telecom Physique Strasbourg<o:p></o:p></pre><pre>11 rue de l'Université 300, Bd Sebastien Brandt CS 10413 <o:p></o:p></pre><pre>F- 67000-STRASBOURG F-67412 ILLKIRCH Cedex<o:p></o:p></pre><pre>tel: +33 3 68 85 24 34<o:p></o:p></pre></blockquote><p class=MsoNormal style='mso-margin-top-alt:auto;mso-margin-bottom-alt:auto'> <o:p></o:p></p></div></div></blockquote><p class=MsoNormal><o:p> </o:p></p></div></div></body></html>