betydata R data package with BETYdb public data export

[divine7022]

Summary

Initial release of betydata, an R data package providing offline access to
public data from BETYdb

• 16 datasets: traitsview (43,532 rows) + 15 reference tables
• Multiple formats: .rda (lazy-loaded), Parquet, Frictionless datapackage.json
• Filtered to public data only (access_level = 4, checked >= 0)
• Complete roxygen2 documentation for all datasets
• Package-level documentation with BETYdb context
• Data quality policy in README (checked column, access levels)

Vignettes

• orientation: Package overview and data relationships
• sql-analogs: Migrate BETYdb SQL queries to dplyr
• pfts-priors: Working with PFTs and Bayesian priors
• manuscript: Reproduce LeBauer et al. (2018) analyses

Datasets

Dataset	Description
traitsview	Primary trait/yield observations (43,532 × 36)
species	Plant taxonomy
sites	Research site locations
variables	Trait definitions and units
citations	Literature references
pfts	Plant functional types
priors	Bayesian prior distributions
+ 9 more	Support and relationship tables

implements #1, #2, #3, #4, #5, #6, #7, #8, #9, #10, #11

[Copilot]

Pull request overview

This PR delivers the initial release (v0.1.0) of betydata, an R data package providing offline access to public data from the BETYdb (Biofuel Ecophysiological Traits and Yields) database. The package enables reproducible analyses of plant traits and crop yields without requiring database connectivity.

Changes:

• Complete R package structure with 16 datasets (traitsview + 15 support tables) totaling 43,532+ trait and yield records
• Multiple data formats: lazy-loaded .rda files, Parquet alternatives, and Frictionless metadata (datapackage.json)
• Comprehensive documentation: roxygen2 docs for all datasets, 4 vignettes (orientation, sql-analogs, pfts-priors, manuscript), and GitHub issue templates
• Quality controls: excludes checked=-1 records, public data only (access_level >= 4), full test coverage
• CI/CD infrastructure: GitHub Actions R-CMD-check workflow, testthat 3.0 test suite

Reviewed changes

Copilot reviewed 38 out of 71 changed files in this pull request and generated 6 comments.

Show a summary per file

File	Description
DESCRIPTION	Package metadata and dependencies; minor email format issue
CITATION.cff	Citation metadata; email and missing preferred-citation issues
LICENSE	BSD-3-Clause license file
README.md	Comprehensive package documentation; table formatting issue
NEWS.md	Release notes documenting v0.1.0
R/betydata-package.R	Package-level documentation
R/data.R	Roxygen2 documentation for all 16 datasets
man/*.Rd	Generated documentation files for datasets
vignettes/*.Rmd	Four tutorial vignettes; minor issues in manuscript.Rmd and pfts-priors.Rmd
tests/testthat/*.R	Test suite for data and metadata validation; deprecated context() calls
data-raw/make-data.R	Data build script for generating .rda and Parquet files
inst/metadata/datapackage.json	Frictionless Data package metadata
inst/extdata/parquet/*.parquet	Sample Parquet data files
data/*.rda	Binary R data files (compressed with xz)
.github/workflows/*.yaml	GitHub Actions CI configuration
.github/ISSUE_TEMPLATE/*.md	Issue templates for data corrections and verifications
.gitignore, .Rbuildignore	Build and version control configuration; CSV exclusion concern

Comments suppressed due to low confidence (2)

tests/testthat/test-metadata.R:3

• The context() function on line 3 is deprecated in testthat 3.0.0 and later. According to the DESCRIPTION file, this package uses testthat (>= 3.0.0) and has Config/testthat/edition: 3. The context() calls should be removed as they are no longer needed and will generate warnings.
  tests/testthat/test-data.R:3
• The context() function on line 3 is deprecated in testthat 3.0.0 and later. According to the DESCRIPTION file, this package uses testthat (>= 3.0.0) and has Config/testthat/edition: 3. The context() calls should be removed as they are no longer needed and will generate warnings.

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[dlebauer]

I've done a quick first review. On a future review I will go through all of the vignettes and explore the tables as they exist.

I am now wondering if we should 1) store the data in CSV files to allow text-based version control and 2) if we can reconstruct traitsview on the fly from the component datasets (i.e. traitsview should not be in data_raw)

[Copilot]

Pull request overview

Copilot reviewed 43 out of 76 changed files in this pull request and generated 7 comments.

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[dlebauer]

• Ensure that all traitsview foreign keys (site_id, citation_id, treatment_id, specie_id, cultivar_id, pft_id, and prior_id etc) references match rows in respective tables. It may be time to ask @robkooper for the complete dump.
• document that traitsview unique id is (result_type, id), not id
• write tests for joins, but defer more comprehensive constraints to #14

[dlebauer]

does maps also need to be here for maps::borders('world', ...)?