The GAIA Data Platform for Fiber Optic Distributed Acoustic Sensing Data Discovery and Processing

Massive Fiber-Optic Distributed Acoustic Sensing (FO-DAS) data streams pose major challenges in archiving, dissemination, and exploitation due to their enormous volumes and high spatio-temporal resolution. Efficient storage is constrained by bandwidth, cost, and metadata standardization, while dissemination is limited by network capacity, data discoverability and data format diversity. Scientific exploitation is further hindered by the need for scalable preprocessing, real-time analytics, and robust noise characterization to extract actionable signals from petabyte-scale, heterogeneous datasets.

This contribution showcases the DATA TERRA (FormaTerre, Odatis, THEIA) approach to describe, store, disseminate and exploit massive FO-DAS datasets, through the GAIA-Data distributed data and computing infrastructure. Key infrastructure aspects are presented allowing to construct a national/european and analysis-ready FO-DAS dataspace. This infrastructure allows easy and interactive discovery and exploitation of massive FO-DAS data for various applications in all domains of the Earth exploration (e.g. seismological source identification, event characterization and seismic parameter estimation generalizing across volcanoes, glaciers, fault zones, landslides, and urban areas).

Examples of resource-intensive processing on HPC infra and AI-ready workspaces are presented. FO-DAS bottlenecks are addressed via AI-driven compression (e.g. variational autoencoders), selective archiving, and data augmentation to ensure scalable monitoring. Integration of the dataspace in the DATA TERRA EOSC node will ensure interoperability with other national (NFDI4DEarth) and European research infrastructures (EPOS, EMSO, eLTER).