NOMAD: Enabling FAIR Research Data Management in Experimental Materials Science

Advancing materials science through data-driven approaches necessitates high-quality data enriched with comprehensive metadata, particularly in experimental synthesis and characterization. However, this potential is hindered by the absence of robust research data management practices, limiting data-driven innovation within the field. 
The FAIRmat project [1] aims to overcome these barriers by promoting the FAIR (Findable, Accessible, Interoperable, and Reusable) principles in materials science data. Our solution, the NOMAD platform [2], bridges critical gaps with a suite of tools that streamline data management and foster collaborative research. NOMAD provides FAIR-structured data, Electronic Lab Notebooks (ELNs), advanced search applications, data analysis tools, and capabilities for data sharing and publication, creating a comprehensive solution tailored to the materials science community [3].
In this contribution, we showcase NOMAD’s capabilities for materials synthesis and characterization, highlighting how the platform offers user-friendly tools that support scientists in achieving FAIR data standards. NOMAD’s versatile data model, along with standardized plugins for material processing, measurements, and analysis, forms a scalable foundation for experimental materials science. Key resources—including ontologies, ELNs, file parsers, data science, machine learning tools, and extensive tutorials and documentation—collectively promote a collaborative, standardized approach to research data management in materials science, driving forward interoperability, reproducibility and innovation.
[1] www.fairmat-nfdi.eu
[2] www.nomad-lab.eu
[3] M..Scheidgen et al., Journal of Open Source Software 8, 5388 (2023) Fundamentals 2 and III-Phosphides

This work is funded by the NFDI consortium FAIRmat - Deutsche Forschungsgemeinschaft (DFG) - Project 460197019