A CYBER WORKFLOW FOR COLLECTION, MANAGEMENT, AND EXPLORATION OF 40AR/39AR AND U-PB GEOCHRONOLOGY DATA

The grand challenge of developing a fully integrated 4-D digital Earth model has prompted geochronologists to implement cyberinformatics systems to collect, manage, and share data. New workflows at the WiscAr Lab and the Boise State Isotope Geology Laboratory (IGL) feature pipelines for linking ⁴⁰Ar/³⁹Ar and U-Pb data directly into synthetic databases. The WiscAr lab workflow now features the PyChron data-collection and analysis software, which links location and stratigraphic metadata with samples upon receipt; these metadata are automatically retained throughout the process of sample preparation, irradiation, analysis, and data reduction. Each lab operates its own instance of the Sparrow data management system. Analytical and metadata are ingested by Sparrow through a customizable schema-based importing tool that can be adapted for any type of geochronologic data. Sparrow then connects lab-level data to synthetic databases including Macrostrat, Neotoma, and the Paleobiology Database (PBDB), as well as to individual consumers, who can search, navigate, and visualize radioisotopic age data and metadata through the WiscAr Lab (http://wiscar-sparrow.geoscience.wisc.edu/) and IGL (https://sparrow.boisestate.edu) Sparrow portals. These pipelines produce data which can be reassessed in the context of future refinements to decay constants and standard mineral ages, and which conform to FAIR (findable, accessible, interoperable, and reusable) data principles.

We demonstrate how the PyChron-Sparrow and IGL-Sparrow pipelines generate and represent geochronologic data from several tuffs spanning deposition of the Wilkins Peak Member of the Green River Formation, WY. We use these data to prototype an integration between the lab workflows and Macrostrat: measured ages are aligned with Macrostat’s stratigraphic age model and used to refine the existing Eocene age model in the context of our new U-Pb and ⁴⁰Ar/³⁹Ar analyses. This process is enabled by efficient, streamlined connections between lab-level analysis systems and Sparrow. As age and metadata are tracked in each lab’s Sparrow implementation, this and other model comparisons can be replicated by anyone with access to the Sparrow and Macrostrat public APIs, and for any dataset tracked by a Sparrow-enabled lab.