pr2database
The protist reference database keeps widening past the rRNA gene it was built on.
A side-by-side editorial comparison of bcdata and mice — release velocity, themes, recent moves, and the top alternatives to consider.
The R gateway to B.C.'s data catalogue, mostly busy keeping pace with the servers behind it.
bcdata searches the British Columbia Data Catalogue and pulls records from it, including spatial layers retrieved through WMS and WFS with dplyr-style filtering translated into CQL queries sent to the server. The recent releases are small and corrective: 0.5.3 fixes malformed CQL generated by geometry predicates such as INTERSECTS, which the server had been rejecting outright, and 0.5.2 drops a leaflet extension dependency in favour of a base leaflet call. Cadence is a few releases a year.
mice can finally predict, not just estimate, from multiply imputed data.
mice is the reference implementation of multiple imputation by chained equations, and the default answer to missing data in R. The releases here follow a consistent shape: one or two substantive additions per version, most contributed by outside authors, plus fixes to methods that have been in the package for years. The current 3.19.0 adds predict_mi(), which pools predictions across imputations under Rubin's rules and can return prediction intervals.
bcdata searches the British Columbia Data Catalogue and pulls records from it, including spatial layers retrieved through WMS and WFS with dplyr-style filtering translated into CQL queries sent to the server. The recent releases are small and corrective: 0.5.3 fixes malformed CQL generated by geometry predicates such as INTERSECTS, which the server had been rejecting outright, and 0.5.2 drops a leaflet extension dependency in favour of a base leaflet call. Cadence is a few releases a year.
Almost everything in this window is a response to something changing on the other side of the connection: a CKAN 2.9 upgrade that stopped search and listing functions returning complete results, WMS and WFS capability requests that cannot be relied on, dbplyr tightening the rules for local evaluation, and general catalogue-side churn. The package's own interface has been stable since the 0.4.0 change that required local() around locally-evaluated filter calls, and the work since has gone into keeping that stable interface working rather than extending it.
Expect the same pattern: targeted fixes as the catalogue and its CKAN, WMS and WFS layers change, with occasional dependency pruning of the kind 0.5.2 did. Nothing in these entries points toward a 0.6 or a change in what the package covers.
mice is the reference implementation of multiple imputation by chained equations, and the default answer to missing data in R. The releases here follow a consistent shape: one or two substantive additions per version, most contributed by outside authors, plus fixes to methods that have been in the package for years. The current 3.19.0 adds predict_mi(), which pools predictions across imputations under Rubin's rules and can return prediction intervals.
Two things are happening. The imputation method catalogue keeps widening — lasso variants, multivariate PMM, categorical PMM via canonical correlation — while the pooling side is being extended past its original purpose, first to synthetic data, now to predictions on held-out sets. That second thread points at predictive modelling workflows rather than the inferential ones mice was built for. Meanwhile the maintainers keep finding consequential old bugs: the augment() ordered-factor defect in 3.18.0 had been silently degrading ordinal imputations for years.
predict_mi() is framed around evaluating predictive performance on test sets, and the ignore argument added in 3.12.0 already exists to hold out rows from the imputation model. Expect the next work to join those up into a fuller train/test story for imputed data, since the pieces are now in place but not yet connected.
Other Infra & APIs 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 bcdata or mice.
The protist reference database keeps widening past the rRNA gene it was built on.
Composable aligned layouts, rebuilt on S7 while ggplot2 4.0 lands underneath.
Conservation planning absorbs the literature's target-setting rules as code.
Joint species distribution models in Gibbs-sampled C++, quiet since 2023.
An ecosystem model starts tracking carbon isotopes and land-use change.
Ten years in, US mapping splits its data out and finally adds Puerto Rico.
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Infra & APIs. bcdata and mice are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). 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. bcdata and mice are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). For your specific use case, the alternatives sections above list other Infra & APIs products to evaluate alongside.
Top bcdata alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "bcdata alternatives" section above for the current picks, or visit /alternatives/bcdata for the full list with editorial commentary on each.
Top mice alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "mice alternatives" section above for the current picks, or visit /alternatives/mice for the full list with editorial commentary on each.