FUTURE MODES OF COLLABORATION TOWARDS A MULTI-SCALE MACROSTRAT

Macrostrat is a platform for deep-time crustal research that integrates stratigraphic columns and geologic maps into a digital description of the rock record in spatial and temporal context. The database and supporting software power models of continental evolution and provide location-based geological information (e.g., through the Rockd app).

Macrostrat supports multiple working scales of mapping and stratigraphy, from continent-level summaries to single quadrangles and measured sections. Currently, Macrostrat’s core datasets are regional stratigraphic summaries, and its spatial footprint is weighted heavily to North America. While this data is of sufficient scale and resolution to generate insights about the continents’ evolution through Earth history, increasing resolution and spatial coverage will support new modeling efforts.

Aligning Macrostrat’s stratigraphic archives with proxy datasets (e.g., geochronology, taxa first appearances, and stable-isotope geochemistry) is important to answering key science questions. The Macrostrat lab has taken a community-driven approach to developing data integrations in this domain: we are a partner in PaleobioDB and a leader of the EarthCube Geochronology Sparrow effort, which empower domain researchers to manage, harmonize, and share digital research data.

Similar collaborative approaches will be required to drive the continued enhancement of Macrostrat’s core data holdings. Macrostrat’s “project” infrastructure allows new datasets to be developed separately from the canonical dataset; this system is being used to organize ocean-drilling cores and “mesoscale” compilations targeting Ediacaran and Mesozoic basins in North America. Atop this scaffold, we are building new web-based tools to assemble and visualize regional stratigraphic datasets, refine multiple working age models, and incorporate the underlying, full-resolution measured sections.

To support collaboration, these technical tools must be augmented with processes for submission, review, coordination, and assimilation of community-contributed datasets. Digital compilation of geological maps and columns requires substantial effort, and well-designed systems for organizing the work may allow crediting as a scientific product.