Automated integration of metrological metadata into oceanographic datasets

Abstract

This work presents a software tool that automates the integration of metrological calibration data with oceanographic datasets, ensuring consistent correction and robust uncertainty quantification with minimal human intervention. The tool processes datasets in NetCDF or CSV formats alongside calibration certificates in SensorML format, applying calibration coefficients and propagating uncertainties using rigorous metrological principles. The output is an enriched dataset with corrected values, uncertainty estimates, and detailed metadata for transparency and reproducibility. This approach bridges the gap between calibration certificates and data analysis, supporting better-informed scientific research and decision-making in oceanography and beyond.