PubDAS: a PUBlic Distributed Acoustic Sensing datasets repository for geosciences

Zack J. Spica, Jonathan Ajo-Franklin, Greg Beroza, Biondo Biondi, Feng Cheng, Beatriz Gaite, Bin Luo, Eileen Martin, Junzhu Shen, ...  more

Zack J. Spica, Jonathan Ajo-Franklin, Greg Beroza, Biondo Biondi, Feng Cheng, Beatriz Gaite, Bin Luo, Eileen Martin, Junzhu Shen, Clifford Thurber, Loïc Viens, Herbert Wang, Andreas Wuestefeld, Han Xiao, Tieyuan Zhu

During the past few years, Distributing Acoustic Sensing (DAS) has become an invaluable tool for recording high-fidelity seismic wavefields with great spatiotemporal resolutions. However, the considerable amount of data generated during DAS experiments limits their distribution with the broader scientific community. Such a bottleneck inherently slows down the pursuit of new scientific discoveries in geosciences. Here, we introduce PubDAS, the first large-scale open-source repository where several DAS datasets from multiple experiments are publicly shared. PubDAS currently hosts eight datasets covering a variety of geological settings (e.g., u...  more

During the past few years, Distributing Acoustic Sensing (DAS) has become an invaluable tool for recording high-fidelity seismic wavefields with great spatiotemporal resolutions. However, the considerable amount of data generated during DAS experiments limits their distribution with the broader scientific community. Such a bottleneck inherently slows down the pursuit of new scientific discoveries in geosciences. Here, we introduce PubDAS, the first large-scale open-source repository where several DAS datasets from multiple experiments are publicly shared. PubDAS currently hosts eight datasets covering a variety of geological settings (e.g., urban centers, underground mine, seafloor), spanning from several days to several years, offering both continuous and triggered active source recordings, and totalling up to ~90 Tb of data. This manuscript describes these datasets, their metadata, and how to access and download them. Some of these datasets have only been shallowly explored, leaving the door open for new discoveries in Earth sciences and beyond.