AI-Ready Data in Biogeosciences: From Data Preparation to Scientific Discovery
AI-Ready Data in Biogeosciences: From Data Preparation to Scientific Discovery
Session ID#: 280765
Session Description:
Rapidly advancing artificial intelligence (AI) capabilities offer opportunities for accelerated and novel scientific discovery, but require data optimized for AI and machine learning (ML) applications. This cross-disciplinary session focuses on open AI-ready biogeosciences datasets and their subsequent use in scientific applications. We seek contributions demonstrating best practices, creative approaches, and cutting-edge tools enabling datasets to be structured for AI/ML analysis. Presentations should address both the processes of making data AI-ready (preprocessing, harmonization, quality control, metadata, etc) and showcase the resulting scientific applications and discoveries. This session aims to demonstrate how curated AI-ready datasets accelerate scientific discovery for complex biogeoscience systems by uniting domain scientists, computational scientists, and data stewards.
Co-Sponsor(s):
- B - Biogeosciences
Index Terms:
0430 Computational methods and data processing [BIOGEOSCIENCES]
0434 Data sets [BIOGEOSCIENCES]
1910 Data assimilation, integration and fusion [INFORMATICS]
1942 Machine learning [INFORMATICS]
Primary Convener: Brieanne K. Forbes, Pacific Northwest National Laboratory, Richland, WA, United States
Conveners: Amy E Goldman, Pacific Northwest National Laboratory, Biological Sciences, Richland, WA, United States, Stephanie C Pennington, Pacific Northwest National Laboratory, Joint Global Change Research Institute, College Park, United States and Ben P Bond-Lamberty, Pacific Northwest National Laboratory, College Park, United States
Student/Early Career Convener: Stephanie J Wilson, Smithsonian Environmental Research Center, Biogeochemistry Lab, Edgewater, United States
See more of: Informatics