Sebastian is a seasoned expert in materials science and research data
management. He earned his PhD in Physics from Humboldt University Berlin and
brings over 16 years of experience in areas including opto-electronics and
semiconductor technologies. His career features collaborations with several
renowned research institutes in Germany. Motivated by the growing volume of
experimental data and the rise of data science, he has developed a keen
interest in advancing research data management practices. As Data Science
Team Leader at the Leibniz Institute für Kristallzüchtung, he oversees the
digitalization of research data management. In his role as the coordinator
of the FAIRmat Area for Synthesis Data, he is actively contributing to the
development of the NOMAD platform to better serve the needs of
experimentalists in the synthesis and characterization of materials.
Recently, he founded Glaide Data GmbH, a company dedicated to offering
advanced research data management solutions.
NOMAD, developed by the FAIRmat project, is an open-source platform connecting experimental and computational materials science. Originally designed for DFT simulation data, NOMAD now emphasizes capturing experimental metadata and ensures FAIR-compliant, AI-ready data storage. In this talk, we highlight key developments supporting experimental workflows: NOMAD Oasis (customizable on-premise deployment), NOMAD Plugins (enabling flexible data schemas, ELN integration, automated processing, and custom analytics apps), NOMAD CAMELS for laboratory automation, and seamless integration of third-party ELNs. Combining comprehensive experimental data models with integrated ML and AI analytics, NOMAD facilitates powerful, data-driven research accessible via intuitive interfaces and APIs.
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