When (and how) should a simulation be Fair?
Presentation: pdf (4 MB).
After a reminder about FAIR (Findable, Accessible, Interoperable, Reusable - not Reproducible), I discuss some of the issues about applying these concepts to Simulation Data. Apart from the volume issues, we have to decide just what “Simulation Data” actually means, does it mean the entire workflow, or just the outputs. There are a huge variety of types of simulation, are they all important? Using the ES-DOC vocabularies, I point out that in practice simulations are not meaningfully reproducible - except in trivial cases, and actually it is more important to reproduce experiments - which is of course the heart of model intercomparison. At CEDA we have two decades of experience curating data, and we now use the JASMIN platform to provide a data commons to make data accessible. Lots of simulation data is analysed on JASMIN, alongside the CEDA archive, but for fifteen years we have made decisions about whether to archive simulation data based on (what was then) the BADC Numerical Model Data Policy. The key insight in developing that policy was that it’s relatively easy to decide what’s important, and what’s not important, but there is a lot of middle ground for which value judgements are important. We developed polices to decide on the important and not important data, and to guide the value judgements, and these are summarised here. Underlying all decisions are questions about affordabilty, and whether or not adequate metadata can be (or will be) produced. Without such metadata curation of simulation data becomes pointless. The bottom line is that not all simulation data should be FAIR, but that which needs to be FAIR needs to be well documented. Money matters as simulation data at scale is incredibly expensive.