[timeDomain: model for Time series] discussion on Timeseries Data model Note / ND-point .... or not ??? !!!

François Bonnarel francois.bonnarel at astro.unistra.fr
Mon Jul 17 09:56:43 CEST 2017


Thanks, Jiri


Again let's clarify what we think. see in text


Le 13/07/2017 à 16:03, Jiří Nádvorník a écrit :
>
> Hi all,
>
> Thank you for nice summary, Francois.
>
> My comments inline.
>
> Cheers,
>
> Jiri
>
> *From:*dm-bounces at ivoa.net [mailto:dm-bounces at ivoa.net] *On Behalf Of 
> *François Bonnarel
> *Sent:* Wednesday, July 12, 2017 6:11 PM
> *To:* mireille.louys at unistra.fr; dm at ivoa.net; voevent at ivoa.net; 
> dal at ivoa.net
> *Subject:* [timeDomain: model for Time series] discussion on 
> Timeseries Data model Note / ND-point .... or not ??? !!!
>
> Dear all,
>
> This is a follow-up of these two emails
>
> http://mail.ivoa.net/pipermail/dm/2017-July/005583.html
>
> and
>
> http://mail.ivoa.net/pipermail/dm/2017-July/005594.html
>
> which are discussing chapter 4 of TimeSeries Data Model IVOA note 
> within the scope of the TimeDomain effort summarized by Ada there:
>
> http://mail.ivoa.net/pipermail/dm/2017-July/005581.html
>
> Discussed issue:  do we need ND-points or not ?
>
> Reference : Laurent's diagram in email 
> (http://mail.ivoa.net/pipermail/dm/2017-July/005581.html) and CubeDM 
> draft  from 
> http://volute.g-vo.org/svn/trunk/projects/dm/CubeDM-1.0/doc/WD-CubeDM-1.0-20170203.pdf 
> (last version)
>
> 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.
>
> */[[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./*
>
/*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... */
>
>
> 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.
>
> */[[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?/*
>
/*Yes ND-point gather 1 value from each DataAxis*/
>
>
> 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.
>
> */[[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)?/*
>
/*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*/
>
>
> So I am wondering if we should not reintroduce the ND-point feature 
> between "SparseCube" and "CubeAxis" or "DataAxis". What do you think ?
>
> */[[Jiri Nadvornik]] My suggestion would be to have the Cube DM hold 
> metadata for axis statistical distribution/*
>
/*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

Cheers
François
*/
>
> */(see Quantity class in TimeSeriesCube UML - 
> https://volute.g-vo.org/viewvc/volute/trunk/projects/time-domain/time-series/time-series-cube/ivoa-note-1.0/ 
> )  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./*
>
>
>
> François (after discussions with Laurent, Mireille and Ada on this topic)
>
>   
>   
>   
>
>
>
> Le 12/07/2017 à 10:57, Mireille Louys a écrit :
>
>     Dear DM and Time Domain followers,
>
>     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.
>
>     Here is a graph proposed by Laurent Michel to clarify the links in
>     3 main parts :
>
>       * /DataSetMetadata DM/, which has the main ObsDataset Class ,
>       * /ND-CubeDM/, which defines a SparseCubedataset
>       * /TimeSerieCubeDM/, which highlights the special properties of
>         a Cube depending on a Time axis
>
>     I think this is essential to highlight the inheritance path
>     between these 3 DM building blocks:
>     a TimeSeriesCube  <is a > NDCubeDM::SparseCubeDataset
>     a NDCubeDM::SparseCubeDataset <is a > DatasetMetadaDM::ObsDataset
>
>     ObsDataset has a /dataproduct_type/ attribute which allows to
>     discover all dataproducts of type ' timeseries'.
>     this provides the container object for time-dependent data.
>
>     If we need to select /timeseries dataproducts/ according to some
>     properties extracted from their data we can:
>      - reuse what Obscore DM provides to explain general axes properties
>     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
>
>      - provide a richer description of the TimeAxis and ObservableAxis.
>     For that , extracting  a statistical profile from the data
>     contained in the Cube could do the job.
>     this means to access and analyse the Data part in ND-Cube , i. e
>     the ND-Points gathered in a SparseCube Object
>
>     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
>     CharacterisationDM::ObservableAxis, STC2.0::CoordMeasurement (??)
>     and TimeSerieCubeDM::CubeAxis.
>
>     This would be great if we could sort this out,
>     but currently , I would appreciate your feedback on the attached
>     diagram , in order to proceed on the data model structure.
>
>     Cheers, Mireille ( after discussions together with Laurent,
>     François, Ada)
>
>
>     -- 
>
>     --
>
>     Mireille Louys
>
>     CDS                                            Laboratoire Icube
>
>     Observatoire de Strasbourg     Telecom Physique Strasbourg
>
>     11 rue de l'Université         300, Bd Sebastien Brandt CS 10413
>
>     F- 67000-STRASBOURG                    F-67412 ILLKIRCH Cedex
>
>     tel: +33 3 68 85 24 34
>

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