EGU General Assembly 2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

DAS Data Management Challenges and Needs

Rob Mellors1, Chad Trabant2, and the DAS RCN Data Management Working Group*
Rob Mellors and Chad Trabant and the DAS RCN Data Management Working Group
  • 1Scripps Institute of Oceanography, University of California, San Diego, USA (
  • 2Incorporated Research Institutions for Seismology, Seattle, Washington, USA, (
  • *A full list of authors appears at the end of the abstract

Distributed Acoustic Sensing (DAS) is a relatively recent technology that has the capability to collect seismic (and other data) time series data using optical fiber as sensors. These optical fibers may be custom deployments or re-purposed telecommunication fibers. The range of applications is increasing rapidly, and recent studies include subsurface monitoring, earthquake hazard, geotechnical engineering, and ice flow. As the number of uses and studies increase, it is expected that the need for archiving of the datasets will also increase. Archiving of DAS faces multiple challenges at present. These include the need for large amounts (100’s TB) of storage, associated data transport and processing, and a standardized metadata format. As part of the DAS Research Coordination Network (RCN), a DAS data management working group is constructing a metadata model for DAS data that will address these needs. The objective is to develop a common metadata standard for archival purposes and guide data collection at experiments. The metadata requirements include: 1) accommodation of most use cases (data collection scenarios); 2) permitting of cloud-based processing; 3) allowing of pre-processing; and 4) reduction of the burden of data transport. Standard metadata principles, such as findability, accessibility, interoperability, reusability (FAIR), and machine-readability, will be adhered to. The purpose of this presentation is to inform potential users of these efforts, encourage adoption of the proposed standard, and invite community input.

DAS RCN Data Management Working Group:

Jerry Carter, Rob Mellors, Chad Trabant, Nicole Taverna, Jonathan Ajo-Franklin, Kent Anderson, Kathleen Hodgkinson, Paul Bodin, Ge Jin, Jon Weers, Ray Willemann, Diane Rivet, Jonathan Schaeffer, Helle Pedersen, Antonio Villaseñor, Sandra Barajas, Arantza Ugalde, Javier Quinteros, Luigia Cristiano, Voon Hui Lai, Meghan Miller, Ben Evans, Lesley Wyborn, Nigel Rees

How to cite: Mellors, R. and Trabant, C. and the DAS RCN Data Management Working Group: DAS Data Management Challenges and Needs, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6573,, 2022.