Overview
This project combines diverse data in varied formats to unify discovery, retrieval, and analysis of integrated data and systems. It also links data analysis to strengths in ocean data assimilation and artificial intelligence to contribute novel data streams and data management approaches. Researchers are combining data from multiple sources, including the Canadian Integrated Ocean Observing System, ocean carbon atlases, and industry partners, to advance deep learning to inform climate models and targets.
Research benefits
- Fill in modeling gaps to reduce uncertainty in climate change prediction;
- Train complex real-world models to accommodate data quality issues;
- Develop new systems for continuous automated monitoring and prediction of the impact of climate action on ocean biodiversity;
- Improve environmental DNA analysis through the development of new algorithms;
- Develop and apply sustainable approaches to AI models.
