fillpattern
Pattern fills for ggplot2, hardened against the ways users write sizes
A side-by-side editorial comparison of r-owidapi and robma — release velocity, themes, recent moves, and the top alternatives to consider.
The R client for Our World in Data found its search had been reading a tenth of the catalog.
owidapi is a small R client for Our World in Data, covering chart data retrieval, metadata, the full chart catalog, and search over it, with experimental Shiny output helpers. It is three releases old and the most recent one is almost entirely repair: the catalog function was silently truncating at 1000 rows because of a Datasette row cap, which meant search had been operating on a fraction of what exists.
RoBMA 4.0 tears out its own constructor surface and rebuilds on one class hierarchy
RoBMA fits robust Bayesian model-averaged meta-analyses that adjust for publication bias. The 3.x line grew by accretion: separate constructors for each model family (RoBMA.reg, NoBMA, BiBMA and their .reg variants), a spike-and-slab algorithm in 3.3.0 that made estimation fast enough to matter, then a steady stream of post-estimation tooling gated on that algorithm — heterogeneity summaries, residuals, funnel plots, z-curve conversion, predict, extract, pooled and adjusted effects. Version 4.0.0 in May 2026 collapses all of it into a unified brma class hierarchy.
owidapi is a small R client for Our World in Data, covering chart data retrieval, metadata, the full chart catalog, and search over it, with experimental Shiny output helpers. It is three releases old and the most recent one is almost entirely repair: the catalog function was silently truncating at 1000 rows because of a Datasette row cap, which meant search had been operating on a fraction of what exists.
Development is about making a thin wrapper trustworthy against an upstream that moves without notice. The truncation fix pages through the catalog properly; a separate fix stops the function breaking when Our World in Data dropped a column, by parsing typed columns only when present. Tests moved to mocked responses, with a small live suite retained purely to detect schema drift and skipped on CRAN — a sensible design for a package whose main risk is that the API changes shape rather than that the code is wrong. The user-facing surface has not grown since the initial release; the work is in defending it.
On this pattern the next release is likelier to be another upstream-compatibility fix than new functionality, with the schema-drift tests the mechanism that surfaces it.
RoBMA fits robust Bayesian model-averaged meta-analyses that adjust for publication bias. The 3.x line grew by accretion: separate constructors for each model family (RoBMA.reg, NoBMA, BiBMA and their .reg variants), a spike-and-slab algorithm in 3.3.0 that made estimation fast enough to matter, then a steady stream of post-estimation tooling gated on that algorithm — heterogeneity summaries, residuals, funnel plots, z-curve conversion, predict, extract, pooled and adjusted effects. Version 4.0.0 in May 2026 collapses all of it into a unified brma class hierarchy.
The 3.x series solved the modeling problem and left an interface problem behind: a caller had to know which of six constructors matched their data type, and argument names differed across them. 4.0.0 resolves that by making the model family a set of arguments rather than a function name, and by standardizing input naming on metafor-style conventions. It shipped one day after BayesTools 0.3.0, the author's own upstream infrastructure package, whose new standardization and prior-transformation machinery this rewrite depends on.
A rewrite this wide usually needs a follow-up, so expect 4.0.x patches addressing migration gaps as users hit the removed constructors and renamed arguments.
Other Analytics products tracked by Sparkpulse, ranked by recent ship velocity. Each card links to a full editorial trajectory and lets you pivot into a head-to-head comparison with either r-owidapi or robma.
Pattern fills for ggplot2, hardened against the ways users write sizes
gcube's recent releases are all packaging metadata, not simulation code
The R port of Quinlan's Cubist gets reproducibility fixes, not new modelling
ggstats keeps widening what a coefficient or Likert plot can be
ecodive rebuilt itself into a broad diversity-metric library, breaking as it went
State-space data simulation for R, filled in one function at a time
See all r-owidapi alternatives → · See all robma alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. r-owidapi is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. r-owidapi is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.
Top r-owidapi alternatives in Analytics are ranked by recent ship velocity. Browse the "r-owidapi alternatives" section above for the current picks, or visit /alternatives/r-owidapi for the full list with editorial commentary on each.
Top robma alternatives in Analytics are ranked by recent ship velocity. Browse the "robma alternatives" section above for the current picks, or visit /alternatives/robma for the full list with editorial commentary on each.