Data-Driven Materials Science: Reproducibility and Standardization
- Advancing development and digitalization in materials science requires to focus on quality assurance, interoperability, and compliance with FAIR principles. Semantic technologies offer effective solutions for these challenges by enabling the storage, processing, and contextualization of data in machine-actionable and human-readable formats – essential for robust data management.
This presentation highlights the PMD Core Ontology 3.0 (PMDco 3.0), developed specifically for the field of materials science and engineering, and its implementation within generic knowledge representation frameworks. Demonstrators such as standardized mechanical testing, material processing workflows, and the Orowan Demonstrator exemplify the ontology’s practical applications. The use of graph patterns, able to be compiled into rule-based semantic shapes, supports a unified and automated approach to managing heterogeneous experimental data across domains.