From the data engineering side, the data integration process often involves the comparison of metadata from two or more sets of measurements or calculations, which require that the data formats are interoperable. Systematic documentation of metadata is crucial for successful data integration projects, which now lie at the center stage of the FAIR principle . For materials optimization platforms that depend on streaming data, the development of automated (meta)data logging systems that include anomaly and distribution shift detection is essential for the quality control of data acquisition. It will also pave the way for efficient data integration and enable online search and process optimization.