Bringing Agentic Search to Earth Observation Data Discovery
NASA and its data centers hold thousands of geoscience datasets and tools like Worldview, Giovanni, the Science Discovery Engine, and Harmony. Finding the right one is hard even for domain experts. We present an agentic search framework for geoscience data discovery that takes a natural-language research query and returns matching datasets and tools. We demonstrate that, in the era of large language models, the latent value of knowledge graphs (KGs) can be substantially amplified through agentic search. From the NASA Earth Observation Knowledge Graph (NASA EO-KG) we derive NASA-EO-Bench, an open benchmark of 47k query-dataset pairs (21k task-based queries). A neural scorer fine-tuned on N...
| Authors | Minghan Yu, Youran Sun, Chugang Yi et al. |
|---|---|
| Primary category | cs.IR |
| Published | 2 July 2026 |
| Last updated at source | 24 September 2026 |
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