Speakers
Keynote

Fordham University
Speakers


University of Chicago, Argonne National Lab
A FAIR Approach Towards Fully Realizing the Impact of AI and Machine Learning in Materials Science

St. Olaf College
Progress in the development of an IUPAC FAIR Data model for spectroscopic data.


NFDI4Chem, University of Jena (CN), TIB Leibniz (PS)
NFDI4Chem Terminology Service: Enabling semantic research data interoperability, discovery and exploitation in chemistry


Berkeley Lab
LinkML: a developer-friendly semantic data modeling framework, with applications in the chemical sciences


Lawrence Berkeley National Laboratory
Python Notebooks for X-ray Spectroscopy Simulation and Analysis



Karlsruhe Institute of Technology, Helmholtz Institute Ulm
Laboratory APIs as the foundation for autonomous laboratories



Karlsruher Institut für Technologie (KIT)
Kadi4Mat : research data infrastructure for material science and beyond

Deltablot, eLabFTW


Unversity of Southampton
Understanding infrastructure requirements to support FAIR physical sciences data