SED serialization

[P.Didelon]

Hi,

jumping in the discussion ( ::oups)

Doug Tody wrote:

>Hi Ivo -
>
>Perhaps it is better to look at it the other way around?  A simple
>1D spectrum is a special case of a multi-segment SED with associated
>metadata.  SED is clearly the more general case.  
>
sorry but I feel the reverse...
Spectra seem to me to be the more general case,
SED beeing a "specialised" case of spectrum with absolute (or at least 
self consistent relative) photometric/flux calibration;
spectra could be even normalised in flux with bin values between 0 and 1
or any arbitrary intensity scale.

>With this approach,
>we still have the general case of a SED as described below, plus the
>special case of a 1D spectrum (the Spectrum model), since it is so common.
>The most powerful applications should be able to deal with either, but
>many simpler applications may prefer to work with Spectrum, which also
>covers most spectral survey data.
>
>The SED model being proposed is not merely a multi-segment spectrum,
>as it also needs general metadata describing the Dataset as a whole
>(DataID, Curation, Target, Char, etc.), plus probably a table giving a
>uniform view of the SED as a whole, with each segment reduced to a few
>values with uniform units.  Then follows the multi-segment part as in
>our original SED model, where an individual segment may be essentially
>a complete observation in itself.  Since for SED the segments can come
>from independent observations with different instruments, in the general
>case it really is more than just a mere multi-segment spectrum.
>
an homogenized multi-segment spectrum?

>
>	- Doug
>
>
>On Tue, 13 Feb 2007, Ivo Busko wrote:
>
>  
>
>>Doug Tody wrote:
>>
>><snip>
>>
>>    
>>
>>>Not greatly different, but the main point is that a SED may be worth
>>>considering as a new type of astronomical data (a primary type) and not
>>>just a fancy Spectrum.  That is, a SED could be a top level Dataset type
>>>(like Image Spectrum, TimeSeries) which is multi-segment, with an overall
>>>Characterization and Identification, and homogeneous units to summarize
>>>all the segments.  The individual segments can be instances of Spectrum,
>>>TimeSeries, or individual photometry points.  Auxiliary metadata might
>>>be required to describe how the SED was computed, especially in the case
>>>of dynamically computed SEDs, where one might want to include images
>>>cutouts for photometry from multiband imagers and so forth.
>>>
>>>Spectral associations are slightly different, being informal
>>>associations of primary datasets rather than a single physical dataset.
>>>A multi-segment Spectrum could be considered an Association or a special
>>>case of a SED; both could be valid.
>>>
>>>	- Doug
>>>      
>>>
>>Doug,
>>
>>I still see a benefit in having a SED to be a special case of Spectrum.
>>Being a subclass of Spectrum means that any application code that can
>>handle a Spectrum instance, will be able to handle a SED instance
>>transparently. It might not be able to provide everything that a
>>SED-aware application is, but it won't crash or refuse to handle the SED
>>data.
>>
>>Maybe I am influenced by the design choices we made when writing the
>>Specview application, but the "SED as a special type of Spectrum" design
>>paradigm showed to be very useful in that case.
>>
>>-Ivo
>>
>>
>>
>>    
>>

-- 
Pierre
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