FAIR data enables next-generation materials discovery.

The focus of the latest FAIRmat User Meeting was all about using artificial intelligence (AI) and machine learning (ML) approaches for next-generation materials discovery. Highlighting that applying the FAIR principles can lead to AI-ready data and thus enables these new methods of discovery. Recordings of four talks from the meeting will soon be published on the YouTube channel of FAIRmat, and I will provide additional information as soon as they are available. Read more about the meeting on the website of FAIRmat. 

What is your take on FAIR data and AI? Is treating data according to the FAIR principles enough to get to AI-ready data?

Link to article on the FAIRmat news-webpage

Improvement through community

RSpace held its third open-source hours with three different community contributions which have the goal to improve data and metadata documentation. There is no recording, but you can check out the meeting notes to get an idea of what was discussed, as well as topics in RSpace developments.

Link to a LinkedIn post about the meeting

Link to the meeting notes

Outro

That’s it for today. Each week, I work on improving the News Digest to provide short updates to you. What would you like to see more (or less) in these weekly overviews? Any wishes for the future? Let me know in the comments.

Thanks for reading, and see you next week.