Re: [SED-ML-discuss] Subset of MathML to use in SED-ML

[Frank B. <fbergman@u.washington.edu>]

 
> > - In SBML we only deal with singular values, however in order for us
> > to calculate aggregates such as the minimum or maximum of a value we
> > need access to more. The specification needs to tell us how to do it
> > ... it could be as simple as referring to the id of a datagenerator
> > and saying this means all values currently computed of the
> > datagenerator. Alternatively, it could also be meant to be calculated
> > only once at the end of all scheduled simulations.
> 
> That is an important point, that we discuss in Bangalore when talking
about
> gluing different representations for multi-scale models (and we talked
about
> SED-ML allowing an integration at the simulation level). One of the
original
> wishes for SED-ML was the ability to re-use simulation descriptions with
> different models. The variables are determined by the model. I would be in
> favor of a variable overload. A symbol can represent a scalar, an array (a
set)
> or a distribution (a function). It depends on the model used by the
simulation
> description.
> 

I'd like to hear a bit more as to what exactly was discussed about this. The
variable overloading sounds a bit scary at first. For me all model variables
represent scalar values.  That's why I suggested to use the data-generators
as the place holders for the only variables to be involved in aggregate
expressions, (like min, max, sum ... ). Implementers of SED-ML will have to
write additional logic for the calculation of data-generators anyway and
thus it would not be a burden on them and we could expect a swift adoption. 

But I'm definitely eager to hear more ... 

Frank

> 
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> Nicolas LE NOVERE, Computational Neurobiology, EMBL-EBI, Wellcome-Trust
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> 
> 
>
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