Monthly FAIR-DI – FAIRmat Colloquium
Leading FAIR data specialist Barend Mons opens our first Colloquium on October 7!
We are very excited to welcome Barend Mons to our first FAIR-DI - FAIRmat Colloquium!
Barend Mons is the Scientific Director of the GO FAIR Foundation, President of CODATA, and key person behind the renowned paper The FAIR Guiding Principles for Scientific Data Management and Stewardship.
Barend Mons will talk about How to materialise FAIR.
First, he will share with us the experiences of the early implementation phase of the FAIR guiding principles: He will give a brief historical review, address how FAIR became a hype term (already more than 5000 citations in the 2016 article) and how this also distracted FAIR from its core at some points.
He then will zoom in on lessons learned, and how to make FAIR ‘materialise’. Finally, he will make a plea for proper and well-budgeted data stewardship plans, compliant with the FAIR guiding principles for each and every research project we may contemplate (yes already when we contemplate, not in hindsight!).
We are very much looking forward to his talk since it will set the stage for fruitful discussions in many sessions. So come ready to ask questions!
The FAIR-DI – FAIRmat Colloquium series is dedicated to topics in the broad field of building, operating, enhancing, and using a FAIR data infrastructure for condensed-matter and chemical physics of materials.
The colloquium will take place as a hybrid event, online participation and on-site participation in Berlin Adlershof are possible. Registration for on-site participation is mandatory!
About FAIRmat and FAIR-DI e.V.
FAIRmat is a consortium of the German Research-Data Infrastructure (NFDI), which was selected for funding in 2021. You can read the press release of the funding decision by the Joint Science Conference (GWK) here: https://www.gwk-bonn.de/presseaktuelles/pressemitteilungen.
FAIRmat is the materials-science component of the association FAIR-DI e.V. (FAIR Data Infrastructure for Physics, Chemistry, Materials Science, and Astronomy e.V.), which started more than 2 years ago as a German-Dutch initative. For the fields of computational and experimental materials science, chemistry, and astronomy, FAIR-DI e.V. sets out to build a FAIR data infrastructure that enables extensive data sharing and collaborations in data-driven sciences, including artificial intelligence, and it expands basic science and engineering. FAIR-DI engages with scientists across generations to promote innovations and further careers, and it reaches out to industry and society.