To advance the digitalization of materials research and improve data continuity in wire-based additive manufacturing, the DiMad project developed a semantic and FAIR-oriented data infrastructure. Its goal is to integrate heterogeneous process, characterization, and simulation data within a consistent semantic framework and to reduce manual effort through automated ingestion based on standardized project data sheets.

A web-based interface provides structured access, visualization, and interaction with both ontology-based information and linked large-scale simulation datasets. To further support scientists in daily work, the system includes a natural-language assistant whose schema-guided reasoning ensures reliable, non-speculative responses aligned with the underlying data model.

The resulting prototype demonstrates a PMD-compatible approach for creating robust, extensible, and user-oriented materials data infrastructures, contributing to improved digital workflows in additive manufacturing.