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.
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.
Details
| Aantal pagina's | 1 |
|---|---|
| Type | Poster |
| Categorie | Onderzoek |
| Taal | Engels |
Bibtex
@misc{79bb8185-1a42-4220-873b-153053031482,
title = "Orchestrating the b3verse: Elevating Research Software through a Modular R Package Ecosystem",
abstract = "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.",
author = "Ward Langeraert and Lissa Breugelmans and Peter Desmet and Shawn Dove and Sabrina Kumschick and Sandra MacFadyen and Damiano Oldoni and Hanno Seebens and Maarten Trekels and Mukhtar Muhammed Yahaya and Toon Van Daele",
year = "2026",
month = jul,
day = "07",
doi = "",
language = "Nederlands",
publisher = "Instituut voor Natuur- en Bosonderzoek",
address = "België,
type = "Other"
}
Auteurs
Ward LangeraertLissa Breugelmans
Peter Desmet
Shawn Dove
Sabrina Kumschick
Sandra MacFadyen
Damiano Oldoni
Hanno Seebens
Maarten Trekels
Mukhtar Muhammed Yahaya
Toon Van Daele
