Re: [SED-ML-discuss] Sampling sensitivity analyses in SED-ML when uncertainty described in the model

[Frank T. B. <fbe...@ca...>]

> 
> However, I think this raises an issue of whether it is important that we 
> are performing a sampling sensitivity analysis rather than some other 
> kind of simulation experiment involving repetition.
> 
> If it is only important to describe how to produce the same results in a 
> more compressed form than enumerating the results, then there is no need 
> for SED-ML - we might as well just describe how to reproduce results in 
> an existing imperative language.

I'm afraid I have to disagree. The overarching goal is to be able to reproduce the results, independent of the tool, of the programming language and of the environments they were originally defined in. At the same time it has to be implementable, we will be getting nowhere if we don't find primitives to connect together to describe more complicated experiments. Otherwise it is unimplementable and without tool support the whole standard becomes an exercise. 

However, you should be able to preserve that what you did was a sampling analysis. But that is something better left to ontologies (perhaps KISAO can be used for that), or a MIRIAM annotation block. 

All the best
Frank