DASstore: an object storage for Distributed Acoustic Sensing

Overview

This work introduce a new storage solution for distributed acoustic sensing (DAS) data. We introduce object storage that has been widely used in commercial cloud storage (AWS S3, Azure Blob, etc.) to a local data server. Instead of hosting data in the HDF5 format, we proposed hosting DAS data in the Zarr format that is optimized for cloud environment.

Data Client

We provide a Python client to conveniently query the data with a Zarr backend. The client supports either anonymous access for public bucket, or private bucket (access key and secret required).

from dasstore.zarr import Client

client = Client(BUCKET, ENDPOINT_URL)

# get 20-minute data from one subarray (channel 500 - 1000)
client.get_data(np.arange(500, 1000),
                starttime = "2021-11-02T00:00:14.000",
                endtime   = "2021-11-03T00:20:14.005")

Metadata

The metadata includes user-defined data for the DAS experiment. Here, we follow the metadata convention proposed by the DAS Research Coordination Network (DAS-RCN). There are five levels of metadata describing an experiment under this convention: Overview, Cable and Fiber, Interrogator, Acquisition, and Channel. These metadata, as key-value-pair attributes, are saved together with the raw data.

# get metadata
client.get_metadata()

# get channel location (calibrated)
client.get_channel()

Data Service and Tutorial

The DASway (https://dasway.ess.washington.edu) is a dedicated object storage server providing data service.

• We are opening one month of SeaDAS-N data (December 2022) through DASway. Check Google Colab notebook how to access through DASstore.
• A notebook to query 2-hour of 2023 Turkey earthquake SeaDAS data is available here on Google Colab.
• Several tutorials about uploading data to the object storage using Zarr or TileDB backend is available at /tutorials.

Data Server Deployment

We use MinIO to deploy the local object storage. MinIO can run as Single-Node Single-Drive (SNSD). See documentation here for more detail. Simple deployment using Docker is shown below.

# pull MinIO image
docker pull minio/minio

# 9000: url endpoint port
# 9001: console port
docker run -p 9000:9000 -p 9001:9001 --name minio \
    -v <PATH/TO/DB> \
    -e MINIO_ROOT_USER= <ADMIN-USER> \
    -e MINIO_ROOT_PASSWORD= <ADMIN-PASSWORD> \
    -d minio/minio server /data --console-address ":9001"

Alternatively, users can deploy MinIO in the Single-Node Multiple-Drive mode (SNMD). Documentation of more advanced deployments can be found here.

Reference

Ni, Y., Denolle, M. A., Fatland, R., Alterman, N., Lipovsky, B. P., & Knuth, F. (2024). An Object Storage for Distributed Acoustic Sensing. Seismological Research Letters, 95(1), 499-511.

BiBTex:

@@article{ni2024object,
    title={An Object Storage for Distributed Acoustic Sensing},
    author={Ni, Yiyu and Denolle, Marine A and Fatland, Rob and Alterman, Naomi and Lipovsky, Bradley P and Knuth, Friedrich},
    journal={Seismological Research Letters},
    volume={95},
    number={1},
    pages={499--511},
    year={2024},
    publisher={Seismological Society of America}
}

Links also below provides useful information about UW-FiberLab, the data, the format and the storage. If you have more questions, feel free to contact us.

• https://fiberlab.uw.edu
• https://zarr.readthedocs.io/en/stable/
• https://min.io
• https://tiledb.com
• https://aws.amazon.com/s3/