In the digital transformation of materials science and engineering, existing processes are being closely examined to optimize and extend them using technologies such as the Semantic Web, while adhering to the FAIR principles. The challenge is to identify and adapt these technologies to significantly improve daily operations, covering the entire cycle of data generation, collection, storage to its processing and use. This presentation presents different approaches developed within the Platform MaterialDigital (PMD) and related initiatives, each addressing specific challenges of digitalization and demonstrating their benefits. These will be illustrated by a case study on age-hardenable aluminium alloys in different aging states, based on a comprehensive dataset of microstructural and mechanical properties.

In this context, ontologies are essential for organizing data into interoperable semantic structures, thereby enabling the representation of concepts and their relationships. The PMD Core Ontology (PMDco) serves as a higher semantic layer that connects domain-specific ontologies. The PMDco provides MSE-specific bridging concepts that enhance data mapping and integration capabilities. This approach facilitates the linking of results from natural language processing of a corpus of microscopy abstracts, which supported the development of a microscopy ontology. In addition, the presentation highlights how modular, digital workflows can improve the reproducibility of transmission electron microscopy image processing and analysis. It also shows how freely available mechanical and microstructural datasets are semantically integrated and made searchable through PMDco, facilitating correlation analysis. Looking ahead, the integration of these components has the potential to advance and sustain MSE practices.