In the recent newsletter from @IHI, the spotlight is on the results of two IMI projects that SIB is involved in:
🔴 FAIRplus - which is delivering a wealth of resources to ensure data is FAIR
🔴 Rhapsody - which has identified biomarkers associated with #diabetes development and progression
And one for the #OpenScience community. 11 training strategies to make open reproducible #Science the norm..
I have to think hard about this to, because when it comes to #FAIRdata, the road to hell is paved with good intentions. At a recent ESA event I was challenged: how many #ClimateModels are fully #OA#OpenSource?
It's a good question. I have no idea. But it needs to be the way we do things. Worth a look...
⭐️ IMI project result ⭐️ Our awesome FAIRplus project produced a wealth of resources to help researchers ensure their #ResearchData is #FAIRdata - findable, accessible, interoperable, reusable.
➡️ Find out more and get links to the FAIR resources: http://europa.eu/!jmtW9b
Computer people I have a very big question... is there something comparable to SDTM/ADAM specs for data science? What I mean to ask is... is there a standardized way data is structured in AI/Data/Number Crunching compsci industry?
It might be easier to look for practices/standards within a smaller research community, as seen in the wild on some open repository or some #OpenAccess journal focused on reproducibility (like the venerable https://www.ipol.im/ ).
A starting point for other fields might be #re3data.