Astrobiology, the study of life and habitability beyond Earth, draws on an extraordinary diversity of data spanning planetary science, Earth science, astronomy, spacecraft and instrument engineering, bioinformatics, and more.  It also encompasses a breadth of research methods, including field analogs, laboratory experiments, mission observations, and modeling efforts.  The challenges in discovery, generation, and interlinking of these diverse data sources is ever more essential for revealing the broader patterns that shape planetary habitability and the potential for life, especially as artificial intelligence (AI) and machine learning (ML) capabilities continue to expand.

This session focuses on cross-disciplinary data collection, integration, and frameworks in astrobiology. We welcome submissions on the current data ecosystem, relevant data repositories, ontologies and other organizational schemes, metadata standard development, practices for hosting and sharing data, data mining or analysis tools, managing multi-modal datasets, and projects that have made notable or creative use of astrobiology open science resources.

• B - Biogeosciences