How to start with FAIR data in #Chemistry?
Take a quick look at our infographics
They say „The first step is always the hardest“, but they also say “Rome wasn’t built in a day”.
Take it step by step.
We cordially invite you to our
Community #Workshop “The 🚀 Future of Research Data Management in ⚗️ #Chemistry”
at 26th Feb 2024
It aims to discuss hot topics in chemistry and determine key aspects of the future work of NFDI4Chem. This will also be a partnering event to prepare proposals.
This workshop explicitly also includes researchers who are not part of the consortium, so please forward!
Of course.
Modern chemistry produces vast amounts of data. And this data has to be processed somehow.
FAIR data, i.e. Findable-Accessible-Interoperable-Reusable, helps us all. Because other researchers can continue to work with FAIR data. Therefore , a lot of preparatory work has to be done, e.g. making terminologies available.
🧠INCF’s Principles of FAIR data management for neuroscience is
for students, researchers, data professionals (stewards, curators, librarians, etc), funders, & research administrators interested in maintaining scientific rigor & reproducibility.
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...