| Abstract Scope |
The digital transformation is revolutionizing materials science and engineering by accelerating development—from manufacturing to component lifetime assessment and recycling—through predictive data models. Central to this transformation is the collaborative creation of materials knowledge graphs based on aligned ontologies and distributed FAIR research data platforms. Unlike traditional text-based knowledge transmission, these graphs semantically interconnect diverse concepts—atomic bonds, chemical composition, grain boundaries, deformation processes, and mechanical properties—in formats accessible to both humans and machines. This approach effectively addresses the challenge of working with scarce materials data in complex contexts. We are establishing an ontology-based, decentralized European materials data infrastructure that captures hierarchical dependencies between processes, microstructure, properties, and material behavior. This framework enables more effective knowledge sharing and accelerates innovation in advanced materials development. |