Watch a Live Demonstration of the Sensing Technique (by Paul-Eric Pottie)
This session will offer a hands-on, immersive experience into the emerging field of distributed and integrated sensing. This session will feature live demonstrations of advanced fiber-optic sensing systems. Participants will witness the functioning of fibre interrogators and gain a practical understanding of key techniques. Demonstrations will be conducted on short fibre cables deployed on-site and, where infrastructure allows, extended to operational fibre networks. This will showcase the integration of sensing within live telecom environments. This unique format will enhance the educational impact of the conference and serve as a platform for dialogue and knowledge exchange among early-career scientists, technology developers and domain experts.
From Raw DAS Data to Scalable Workflows with Xdas (by A. Trabattoni)
Working with DAS data can be challenging due to its size and diversity of formats. This workshop introduces Xdas, a Python library that simplifies data access and enables scalable, high-performance processing. Through practical examples, participants will learn how to manipulate large datasets, build efficient processing pipelines, and explore real-time applications—all within a familiar NumPy/Xarray-like environment.
Introduction to DASCore (by D. Chambers)
A short, hands-on introduction to DASCore, an open-source python library for working with DAS data. Participants will learn how to use DASCore to read files, manage DAS archives, perform processing, and visualize results. The course will also briefly introduce a few other projects in the emerging DAS Data Analysis Ecosystem.
DAS-SPP (by M. Corsaro and M. Allegra)
This session will focus on the application of advanced analysis techniques and modern AI-based technologies for the processing of fibre-optic recordings. Participants will be introduced to state-of-the-art methods for event detection and seismic phase picking, with an emphasis on the role of machine learning in enabling fast and efficient DAS data processing. The master class will also address key practical challenges, including data quality issues and the requirements for real-time processing in DAS-based monitoring systems.