Experimental materials research uses a wide range of techniques and instruments, producing diverse and often complex data that can be difficult to combine, analyze, and reuse.

FAIRmat Area B develops common data models and tools that make experimental data interoperable across methods. By extending these approaches to multidimensional, time-resolved, and multi-technique experiments, Area B enables integrated data analysis and prepares experimental workflows for AI applications and autonomous laboratories.

Objectives

• Make experimental data interoperable across instruments, techniques, and data sources.
• Enable integrated analysis and reuse of multidimensional and time-resolved experimental data.
• Connect data from multiple techniques in multimodal, in-situ, and operando experiments.
• Prepare experimental data and workflows for AI-assisted analysis and autonomous laboratories.