Type A Proposal
Jerry Carter
We are pleased to submit this type A proposal for consideration
regarding a proposal to adopt a published DAS metadata standard as an FDSN standard.
Distributed Acoustic Sensing (DAS) is a transformative technology and its applications in geosciences and engineering are numerous and growing. To move this frontier technology forward, it is important to compare and integrate measurements across deployments and make the data reusable by others following Findable, Accessible, Interoperable, and Reusable (FAIR) data principles (Wilkinson et al., 2016). Long-standing metadata standards such as the Standard for the Exchange of Earthquake Data (SEED) (Ahern et al., 2009) developed for seismic data do not adapt well for DAS due to fundamental differences in sensor and data acquisition parameters. Existing formats for seismic metadata developed in the early days of digital seismic recording, such as dataless SEED and SEG-Y headers, cannot accommodate all the acquisition parameters, cable environment, and channel location information needed for proper characterization. To address the needs of the DAS research community Lai et al. (2024) proposed a Distributed Acoustic Sensing (DAS) metadata standard through the DAS-RCN Data Management group, with community input gathered from conferences, online discussions, and a whitepaper between 2020 and 2023. We propose that this standard be accepted (with recent updates and small modifications) as an FDSN standard for DAS metadata.
The reason that such a standard is necessary and a brief description of the standard are provided in the abstract for the paper:
“With increasing geophysical applications using distributed acoustic sensing (DAS) technology, there is a need to implement a metadata standard specifically for DAS to facilitate the integration of DAS measurements across experiments and increase reusability. We propose a metadata standard intended primarily for the DAS research community, which fully describes the five key components of a DAS experiment: (1) interrogator; (2) data acquisition; (3) channels; (4) cable; and (5) fiber. The proposed metadata schema, which is the overall structure of the metadata, is hierarchical based, with a parent “overview” metadata block describing the experiment, and two main child branches describing the instrument (i.e., interrogator, photonics setup, and acquisition parameters) and the sensor locations (i.e., cable installation and fiber properties). The metadata schema is designed to be independent of the time-series data so that corrections and updates can be applied to the metadata without having to manipulate large volumes of time-series data. Unique identifiers are used as pointers that map different components within the metadata schema; they also provide a natural basis for the naming convention (i.e., source identifier) of the time-series data in which the time series can be described using identifiers defined by the metadata standard. We advocate for the metadata to be stored in a separate structure from the data itself. The metadata standard is successfully applied to four common scenarios: horizontal direct buried cable, dark fiber, borehole cable, and active survey, and two hypothetical scenarios: multiple interrogators to a single cable, and a single interrogator to multiple cables. Finally, we use GitHub to implement version control for the metadata standard, to enable community collaboration and facilitate sustainable development of the metadata standard, as the DAS technology and application continue to evolve.”
(Lai et al., 2024)
The original version of the standard is Version 1.1 in the GitHub repo for easy reference to the original work (https://github.com/FDSN/DAS-metadata). Version 2 is the proposed FDSN standard, which adheres closely to FDSN norms and is optimized for JSON schema. The draft FDSN schema has been modified in the following ways:
Add a required schema version number, this value must be “2”.
Add a FDSN schema identifier ($id).
The network_code field is now specifically limited to characters allowed by the FDSN Source Identifier specification to ensure compatibility.
The principal_investigator field is expanded to a list of possible name, email, address fields.
The redundant channel_group_id, interrogator_id, acquisition_id, and cable_id fields were removed as they are not needed in this hierarchical structure where those values are unambiguous via context.
Change the recommendation for “open” end dates to be represented by omitting the end_date field, instead of using a far future date.
This first step of proposing an FDSN standard for Distributed Acoustic Sensing (DAS) metadata is part of a larger set of changes expected for the FDSN in the coming decade, as data centers work towards modern cloud-based storage systems, versatile formats for data and metadata, asynchronous data access, and on-cloud processing. The general concept, initially conceived by the EarthScope and ORFEUS data centers in 2023, is described in Trabant et al. 2024, and the path to its realization is to be coordinated here within the FDSN. This is also a call for wider participation in shaping this vision for FDSN members through expertises on the various topics at the upcoming IASPEI/FDSN meetings in Lisbon this summer.
References:
Ahern T. Casey R. Barnes D. Benson R. Knight T., and Trabant C. 2009. SEED Reference Manual, version 2.4, available at http://www.fdsn.org/seed_manual/SEEDManual_V2.4.pdf (last assessed October 2023).
Lai, V., K. M. Hodgkinson, R. W. Porritt, and R. Mellors (2024). Toward a Metadata Standard for Distributed Acoustic Sensing (DAS) Data Collection, Seismol. Res. Lett. 95, 1986–1999, doi: 10.1785/0220230325.
Trabant, C, A. Strollo, J. Quinteros, A. Heinloo, P. L. Evans, G. Sharer, J. Carter, C. Cauzzi, J. Clinton, F. Massin, P. Kästli, P. Danecek, R. Sleeman, C. P. Evangelidis, N. Horn, J. Schaefer, and H. A. Pedersen (2024). Towards the next generation of federated seismological data services, S33C-3327, AGU24. Poster
Wilkinson, M., Dumontier, M., Aalbersberg, I. et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data 3, 160018 (2016). https://doi.org/10.1038/sdata.2016.18
Jerry Carter
Voon Hui Lai, Australian National University
Chad Trabant, EarthScope Consortium
Kathleen Hodgkinson, Sandia National Laboratories
Rob Porrit, Sandia National Laboratories
Rob Mellors, University of California, San Diego
Angelo Strollo, GFZ Helmholtz Centre for Geosciences
Jerry Carter, EarthScope Consortium
Gizem Karslioglu, EarthScope Consortium
David Mencin, EarthScope Consortium