Lucian's SED-ML Level 2 proposal: worth pursuing?

[luciansmith]

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:

• The talk itself: https://www.youtube.com/watch?v=GvJKdROtILA (the playback speed option is your friend!)
• The slides: https://docs.google.com/presentation/d/1X8bhK8eFxUInoV1tksGaFPmn3NB913-w/edit
• The UML diagrams: https://drive.google.com/drive/folders/1RFAGw6eL5JhSR4XgdQSI6wAap6fplWnv
• Examples: https://docs.google.com/document/d/1jZkaNhM_cOqMWtd4sJZ9b0VGXPTLsDKsRNI5Yvu4nOA/edit

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.

(Note: also posted to https://groups.google.com/g/sed-ml-discuss/c/dEDKpG7Nb34)