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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 all,<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'>Thank you for nice summary, Francois.<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'>My comments 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><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'> dm-bounces@ivoa.net [mailto:dm-bounces@ivoa.net] <b>On Behalf Of </b>François Bonnarel<br><b>Sent:</b> Wednesday, July 12, 2017 6:11 PM<br><b>To:</b> mireille.louys@unistra.fr; dm@ivoa.net; voevent@ivoa.net; dal@ivoa.net<br><b>Subject:</b> [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>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>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.<span style='color:windowtext'><o:p></o:p></span></p><p class=MsoNormal><b><i><span style='color:windowtext'>[[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.</span></i></b><br><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.<span style='color:windowtext'><o:p></o:p></span></p><p class=MsoNormal><b><i><span style='color:windowtext'>[[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?</span></i></b><br><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.<span style='color:windowtext'><o:p></o:p></span></p><p class=MsoNormal><b><i><span style='color:windowtext'>[[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)?</span></i></b><br><br>So I am wondering if we should not reintroduce the ND-point feature between "SparseCube" and "CubeAxis" or "DataAxis". What do you think ?<span style='color:windowtext'><o:p></o:p></span></p><p class=MsoNormal><b><i><span style='color:windowtext'>[[Jiri Nadvornik]] My suggestion would be to have the Cube DM hold metadata for axis statistical distribution (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/"><span style='font-weight:normal;font-style:normal'>https://volute.g-vo.org/viewvc/volute/trunk/projects/time-domain/time-series/time-series-cube/ivoa-note-1.0/</span></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.<o:p></o:p></span></i></b></p><p class=MsoNormal><br><br>François (after discussions with Laurent, Mireille and Ada on this topic)<br><br><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='margin-bottom:12.0pt'><br><br><o:p></o:p></p><div><p class=MsoNormal>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><span style='font-family:"Times New Roman",serif'>Dear DM and Time Domain followers,</span> <br><br><span style='font-family:"Times New Roman",serif'>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 : </span><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><span style='font-family:"Times New Roman",serif'>DataSetMetadata DM</span></i><span style='font-family:"Times New Roman",serif'>, which has the main ObsDataset Class ,</span><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><span style='font-family:"Times New Roman",serif'>ND-CubeDM</span></i><span style='font-family:"Times New Roman",serif'>, which defines a SparseCubedataset</span><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><span style='font-family:"Times New Roman",serif'>TimeSerieCubeDM</span></i><span style='font-family:"Times New Roman",serif'>, which highlights the special properties of a Cube depending on a Time axis</span><o:p></o:p></li></ul><p class=MsoNormal><span style='font-family:"Times New Roman",serif'>I think this is essential to highlight the inheritance path between these 3 DM building blocks: <br>a TimeSeriesCube <is a > NDCubeDM::SparseCubeDataset<br></span>a <span style='font-family:"Times New Roman",serif'>NDCubeDM::SparseCubeDataset <is a > DatasetMetadaDM::ObsDataset<br></span><br><span style='font-family:"Times New Roman",serif'>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><br></span><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><o:p> </o:p></p></div></div></body></html>