PERSPECTIVE article
Front. Artif. Intell.
Sec. Natural Language Processing
Volume 8 - 2025 | doi: 10.3389/frai.2025.1674927
Accelerating Earth Science Discovery via Multi-Agent LLM Systems
Provisionally accepted
- Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research (AWI), Bremerhaven, Germany
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This Perspective explores the transformative potential of Multi-Agent Systems (MAS) powered by Large Language Models (LLMs) in the geosciences. Users of geoscientific data repositories face challenges due to the complexity and diversity of data formats, inconsistent metadata practices, and a considerable number of unprocessed datasets. MAS possesses transformative potential for improving scientists' interaction with geoscientific data by enabling intelligent data processing, natural language interfaces, and collaborative problem-solving capabilities. We illustrate this approach with "PANGAEA GPT", a specialized MAS pipeline integrated with the diverse PANGAEA database for Earth & Environmental Science, demonstrating how MAS-driven workflows can effectively manage complex datasets and accelerate scientific discovery. We discuss how MAS can address current data challenges in geosciences, highlight advancements in other scientific fields, and propose future directions for integrating MAS into geoscientific data processing pipelines. In this Perspective, we show how MAS can fundamentally improve data accessibility, promote cross-disciplinary collaboration, and accelerate geoscientific discoveries.
Keywords: multi-agent systems, Large language models, geoscience data management, Pangaea, Retrieval-Augmented Generation, Earth Science Informatics, scientific data discovery, autonomous AI agents
Received: 28 Jul 2025; Accepted: 13 Oct 2025.
Copyright: © 2025 Pantiukhin, Shapkin, Jost, Kuznetsov and Koldunov. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Dmitrii Pantiukhin, dmitrii.pantiukhin@awi.de
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