The advancement of Open Science and the democratization of computing services allow for the discovery and processing of large amounts of information, blurring traditional discipline boundaries. Being data heterogeneous in format and provenance, the ability to combine them and extract new knowledge to address complex challenges relies on standardisation, integration and interoperability.
Thanks to decades of work in this field, Research infrastructures (RI) worldwide, such as EPOS, Europe's RI for solid Earth science, are key enablers of this paradigm. By providing access to quality-vetted, curated open data, they enable scientists to combine data from different disciplines and data sources into innovative research and apply novel approaches such as Large Language Models (LLM) and AI/ML tools to obtain new insights and solve complex scientific and societal questions.
However, while data-driven science creates enormous opportunities to generate groundbreaking inter- and transdisciplinary results, many challenges and barriers remain.
This session aims to foster cross-fertilization by showcasing real-life scientific studies and research experiences in geosphere studies, especially from Early Career Scientists (ECS) worldwide. We also welcome contributions on challenges and user needs when establishing multi-disciplinary studies, including, e.g., need for reliable and trustworthy AI and the availability of training datasets. The session will not only focus on results, but also on challenges and solutions in connection to data availability, collection, processing, and inter-disciplinary methods.
A non-exhaustive list of topics includes:
- multi-disciplinary studies, involving data from different disciplines (e.g. combining seismology, geodesy, and petrology to understand subduction zone dynamics);
- inter-disciplinary research integrating two or more disciplines into new approaches (e.g. merging geophysics and geochemistry to probe mantle plumes);
- activities that advance interdisciplinarity and open science (e.g. enhancing FAIRness of data and services, enriching data provision, enabling cross-domain AI applications, software and workflows, transnational access and capacity building for ECS);
- experiences that cross disciplinary boundaries, integrate paradigms and engage diverse stakeholders (e.g. bringing together geologists, social scientists, civil engineers and urban planners to define risk maps and prevention measures in urban planning).