Calling for Earth Science Machine Learning Data Submissions for EGU

The EGU General Assembly 2021 is fast approaching, and IMPACT is convening the session Addressing Training Data Challenges to Accelerate Earth Science Machine Learning. Progress in artificial intelligence (AI) and machine learning (ML) is driven by data. Data, specifically, large-scale and openly-accessible training data are critical to the adoption and acceleration of ML.

Access to high-quality labeled training data is required to enable ML practitioners to tackle supervised learning problems in Earth science. However, creating labeled data that scales is still a bottleneck, and new strategies to increase the size and diversity of training datasets need to be explored. Additionally, solutions are needed to better enable discovery and open sharing of existing training data and corresponding models to enable reproducibility of research and minimize duplication.

The session is open for submissions from ML practitioners and data curators that present innovative approaches to creating labeled training data, cataloging training data and models, and providing search, discovery, and distribution of training data and models. The deadline for session submissions is January 13th.

This is the unofficial blog of the Interagency Implementation and Advanced Concepts Team.

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