Speaker
Description
High-throughput materials research generates large volumes of heterogeneous experimental data that must be integrated to support reproducible analysis and data-driven discovery. We present a Research Software Engineering approach implemented in the MatInf Research Data Management System (RDMS) for integrating multimodal screening data obtained from thin-film materials libraries. The methodology is based on a shared measurement grid, user-defined types and relational data representation with oriented graph support, and automated ingestion of experimental results into a unified information space. Measurement-area–resolved data objects serve as integration points for composition, phase, thickness, and functional-property data. Flexible API-based querying enables the generation of customized multimodal datasets, facilitating downstream machine-learning workflows and reproducible materials informatics research.