Orchestrating the b3verse: Elevating Research Software through a Modular R Package Ecosystem

Scaling research software beyond single scripts or standalone packages requires deliberate architectural choices, shared conventions, and robust distribution infrastructure. This poster presents the b3verse, a coordinated ecosystem of twelve interoperable R packages designed to transform large biodiversity occurrence cubes into standardized indicators for research and policy support.
The ecosystem is built around a standardized occurrence cube data structure that serves as an explicit interface between packages. A gatekeeper validation function enforces structural consistency and harmonization of heterogeneous inputs, enabling seamless interoperability across specialized indicator packages such as pdindicatoR and impIndicator. The workflow spans data acquisition using rgbif, cube construction with b3gbi, exploratory analysis through dubicube, and indicator calculation with integrated bootstrap-based uncertainty estimation. Standardized interfaces ensure that alternative methodological implementations remain comparable while allowing independent package evolution.
To support cross-package development and onboarding, the ecosystem includes b3data, a dedicated frictionless data package providing shared, versioned example datasets. By distributing reference cubes and spatial grids in a consistent format, b3data enables reproducible testing, simplifies vignette development, and lowers the barrier for new contributors.

Continuous integration and cross-platform binary distribution are handled through R-Universe, simplifying installation while supporting coordinated releases across repositories. A shared software development guide defines testing practices, documentation standards, and conventions for data structures and function behaviour, providing a governance model for sustaining multi-package research software ecosystems in R.