TREMORS: An Agentic Assistant for Multi-Datacenter Seismic Data Acquisition
Abstract
Seismology increasingly depends upon large data retrieval across multi-datacenter platforms. Yet, data procurement often demands domain expertise, user burden, and is difficult to reproduce. As archives continue to grow, translating scientific intent into structured workflows that operate across multiple repositories and produce high quality, AI ready data is becoming an increasingly urgent challenge. We present TREMORS (Text Referenced Event Mapping and Output Renderer for Seismographs), an agentic framework that uses large language model reasoning within a constrained execution graph to automate seismic data retrieval. TREMORS translates natural language queries into a structured intermediate schema, which drives execution through a constrained LangGraph workflow. Example workflows demonstrate support for both event-based and continuous waveform acquisition. The framework is designed to extend across heterogeneous multi-datacenter systems through a portable schema and modular workflow components. This work positions agentic workflows as the catalyst that will connect scientific intent with distributed seismic data systems, enabling a future of reproducible, data-driven inquiry while reducing the burden of routine acquisition tasks.
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BibTeX
@misc{hill2026tremors,
title = {{TREMORS: An Agentic Assistant for Multi-Datacenter Seismic Data Acquisition}},
author = {Ryley G. Hill and Richard Alfaro-Diaz and Jonathan MacCarthy and Jonas A. Kintner and Christopher W. Johnson},
howpublished = {arXiv},
year = {2026},
month = sep,
doi = {10.48550/arxiv.2609.01777},
eprint = {2609.01777},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2609.01777},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - TREMORS: An Agentic Assistant for Multi-Datacenter Seismic Data Acquisition
AU - Ryley G. Hill
AU - Richard Alfaro-Diaz
AU - Jonathan MacCarthy
AU - Jonas A. Kintner
AU - Christopher W. Johnson
PY - 2026
DA - 2026/09/01
PB - arXiv
DO - 10.48550/arxiv.2609.01777
UR - https://arxiv.org/abs/2609.01777
AB - Seismology increasingly depends upon large data retrieval across multi-datacenter platforms. Yet, data procurement often demands domain expertise, user burden, and is difficult to reproduce. As archives continue to grow, translating scientific intent into structured workflows that operate across multiple repositories and produce high quality, AI ready data is becoming an increasingly urgent challenge. We present TREMORS (Text Referenced Event Mapping and Output Renderer for Seismographs), an agentic framework that uses large language model reasoning within a constrained execution graph to automate seismic data retrieval. TREMORS translates natural language queries into a structured intermediate schema, which drives execution through a constrained LangGraph workflow. Example workflows demonstrate support for both event-based and continuous waveform acquisition. The framework is designed to extend across heterogeneous multi-datacenter systems through a portable schema and modular workflow components. This work positions agentic workflows as the catalyst that will connect scientific intent with distributed seismic data systems, enabling a future of reproducible, data-driven inquiry while reducing the burden of routine acquisition tasks.
ER -