Some of those examples are in the slides/talk, but many are new; I was asked at COMBINE to come up with some more examples, and they're there.
What happens next depends on you! I need to know:
Is this approach worth pursuing further?
If you don't have an answer to that, then I have a different question instead:
What additional information do you need to make that decision?
For the purpose of these questions, 'this approach' is:
Moving to a procedural/script based way of storing the simulation experiment.
Keeping a lot of the trappings of existing SED-ML.
Storing information in a way that could remain as XML, or could be switched to Yaml or a database like JSON: this proposal is agnostic on that front.
If you think the approach in general is OK, but disagree/have opinions about some of the specifics, I definitely want to hear that, too, but those discussion are moot if we don't want to go this direction in general.
So! At COMBINE, I presented a proposal of what SED-ML Level 2 could look like. If you weren't there, or if you want a recap, we have:
Some of those examples are in the slides/talk, but many are new; I was asked at COMBINE to come up with some more examples, and they're there.
What happens next depends on you! I need to know:
Is this approach worth pursuing further?
If you don't have an answer to that, then I have a different question instead:
What additional information do you need to make that decision?
For the purpose of these questions, 'this approach' is:
If you think the approach in general is OK, but disagree/have opinions about some of the specifics, I definitely want to hear that, too, but those discussion are moot if we don't want to go this direction in general.
(Note: also posted to https://groups.google.com/g/sed-ml-discuss/c/dEDKpG7Nb34)