• John Chambers (Software for Data Analysis: Programming with R)

• Ideally, we can rerun all decision support tools over and over again
• Must be MUCH easier the second, third, etc. time
• If there is an incremental change in input data, then we shouldn't need to redo the same effort as the first time around.

• There is much fanfare about using Rmarkdown as a tool for reproducibility (i.e, Rmarkdown = "code, output, narrative")

• But this allows exact reproducibility

  • Everything will be run exactly as before
• What happens if the goal is to run it again, but with slight changes to the input data?

• The Rmarkdown approach can deal with this to a certain extent, but it will be clunky

• What happens if you want to add something new, but keep it mostly the same
• You have a good vegetation model and a good caribou model, but you want to add a wolf model
• With Rmarkdown, you would have to edit the original file
• With SpaDES, you can use the other modules by calling them… no need to know how they work
• You add your own wolf model, looking at outputs of the vegetation model and caribou model
• Using the model metadata from those other modules

Need the reusable work flow, and reproducible science … but with a GUI

• shine function is a start
• we created a demo version of a generic web interface for models (link)
• A non-scientist can ask questions of a system of modules without knowing which modules are necessary

• For the above to work for, say, a national question, it can't run the model on the fly
• Could have massive data requirements, long simulation times, even on supercomputers
• Caching allows for near instant results from very complex systems

?Cache

wolf model shows a caching use case

• This is the current vision for SpaDES
• We are looking for people who are interested in being part of this adventure