Applying tephra stratigraphy best practices through integration of field collection forms, database archives, and open-source data visualization tools

Building interoperable data systems requires coordinated effort across the scientific community to establish common terms, definitions, and data structures. Within the diverse disciplines of the tephra community, more than a of decade of work has gone into standardizing field data collection, metadata, and terminology.  This effort culminated in the release of a formal best practices publication in 2022 (Wallace et al., 2022, Scientific Data). To put these principles into practice, we have adopted a three-pronged implementation.

We have developed a dedicated tephra module within the StraboField app to streamline tephra data collection in the field. This module includes predefined fields and picklists designed to capture the core tephra layer metadata outlined in community best practices. The tephra module is part of the StraboSpot ecosystem—a suite of interconnected data collection applications built to support FAIR data principles across the geosciences. Because of this integration, the module works seamlessly with field projects beyond tephra stratigraphy, including mapping or structural geology.

At the same time, we built a data structure within the Alaska Volcano Observatory’s geologic database, “GeoDIVA,” to archive essential tephra metadata in a relational format.  A key enhancement is the addition of a “layer data” component, which captures key attributes such as thickness, type, grainsize, and other aspects of stratigraphic layers in order to capture the full context and complete assembled of a measured section. This layer data is also linked to an integrated framework for samples, stations, source volcanoes, eruptions, field projects, and publications.

Finally, we have released an open-source R package, avstrat, that enables data processing and visualization of data collected with the StraboField application or stored in the database structure. This package produces graphical outputs comparable to tools such as SedLog or SDAR, but allows for more flexible data inputs, including describing stratigraphy by layer thickness and relative order or by absolute depths within a section. Avstrat integrates easily with age-depth models like rbacon and Bchron, and its source code will be freely available on GitLab for user modification.