Machine Learning to Improve and Support Ocean Data Quality Control

Enhancing Ocean Data Quality Control with Machine Learning

The presentation held on 6 July 2023 by Dr. Mohamed Chouai delved into the AWI innovative approach, fusing traditional quality control methods with cutting-edge Machine Learning techniques. He discussed the development of a hybrid system that combines traditional automatic quality control methods with Machine Learning techniques to improve the detection of errors in temperature hydrographic data. His presentation focussed on the UDASH dataset and highlight the system's ability to detect suspect gradient and spike/outlier errors. The multilayer perceptron model achieved remarkable accuracy, surpassing traditional methods in identifying these errors. A  live demonstration using the AWI Virtual Machine was also provided to showcase the effectiveness of the ML NN model in detecting profiles that have been changed from bad to good. The user-friendly AutoQC app, which integrates the ML Neural Network model for enhanced detection of problematic profiles was also presented.

Blue-Cloud EOV Workbenches

In Blue-Cloud 2026, advanced Workbenches (WBs) are being developed to streamline data handling for Essential Ocean Variables (EOV). These tools enhance data harmonisation, validation, and qualification from various sources. These novel Workbenches leverage cloud tech, AI, and advanced analytics for improved data handling. They are set to be adopted by key initiatives, consistently producing validated data collections, enhancing oceanic simulations. The EOV Workbenches cover Physics, Eutrophication, and Ecosystem-level Variables.

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