Primary Convener:
Forrest Hoffman, Oak Ridge National Laboratory

Convener:
Maxwell Grover, Argonne National Laboratory
Charuleka Varadharajan, Lawrence Berkeley National Laboratory
Justin Hnilo, U.S. Department of Energy, Germantown, MD

Early Career Convener:
Maxwell Grover, Argonne National Laboratory

Chair:
Forrest Hoffman, Oak Ridge National Laboratory
Maxwell Grover, Argonne National Laboratory
Justin Hnilo, U.S. Department of Energy, Germantown, MD

The volume, velocity, variety, veracity, and value of Earth and environmental data are increasing rapidly. Data from observational networks, remote sensing and modeling platforms are expanding with ever increasing spatial resolution and temporal sampling. To realize the promise of new scientific discoveries in Earth system science, new analysis paradigms, novel hardware and software infrastructure, efficient and scalable data discovery, access, and management tools are required. This session solicits abstracts that describe high performance storage and computing infrastructure; data access and analytics platforms; strategies for fostering or ensuring FAIR (findability, accessibility, interoperability, and reusability) data principles; unique methods for data fusion, synthesis, and analysis of open data; standards for AI-ready training and benchmarking data; methods for building and using ML foundational models from Big Data archives; advances in research data platforms and technologies; and reports on scientific discoveries or research results employing large and/or complex Earth system science data.

Index Terms
1912 Data management, preservation, rescue
1916 Data and information discovery
1932 High-performance computing
1942 Machine learning

Suggested Itineraries:
Machine Learning and AI
Open Science and Open Data

Cross-Listed:
A - Atmospheric Sciences
B - Biogeosciences
H - Hydrology
OS - Ocean Sciences

Neighborhoods:
1. Science Nexus