rnaturalearth
rnaturalearth finished its sp exit and is now optimising how the data actually arrives.
Comparison · Analytics
modelbased vs osmdata
A side-by-side editorial comparison of modelbased and osmdata — release velocity, themes, recent moves, and the top alternatives to consider.
modelbased vs osmdata: at a glance
What is modelbased?
modelbased is turning marginal effects into a full contrast grammar
modelbased computes marginal means, contrasts, and slopes from fitted models, and it ships every one to two months with a consistent shape: new comparison types, broader model support, and steady renaming toward clearer vocabulary. The recent arc runs from marginal effects inequality measures through inequality ratios to an omnibus global test and a post_process argument for multi-step comparisons. Argument names have been settled along the way, with trend becoming slope and an alias left behind.
What is osmdata?
osmdata keeps tightening its Overpass query surface, breaking small things to get types right.
The last two releases are the substantive ones. 0.4.0 lets `getbb()` resolve OSM relations via Wikidata ids, adds `filter_osm_user()` to Overpass query objects, and corrects metadata typing so timestamps are POSIXct rather than locale-dependent strings. 0.3.0 dropped the re-exported magrittr pipe, raised the R floor to 4.1 for the base pipe, and fixed polygon output to follow the OGC simple-features model instead of treating every ring as an independent polygon. Earlier entries are CRAN repairs and query-construction fixes.
modelbased vs osmdata: editorial side-by-side
modelbased
0.0ANALYTICS
modelbased is turning marginal effects into a full contrast grammar
◆ Current state
modelbased computes marginal means, contrasts, and slopes from fitted models, and it ships every one to two months with a consistent shape: new comparison types, broader model support, and steady renaming toward clearer vocabulary. The recent arc runs from marginal effects inequality measures through inequality ratios to an omnibus global test and a post_process argument for multi-step comparisons. Argument names have been settled along the way, with trend becoming slope and an alias left behind.
◆ Where it's heading
The package is building a compositional vocabulary rather than a fixed menu — contrasts of average slopes, contrasts across two numeric predictors, inequality summaries across all outcome categories, and now user-supplied post-processing of comparisons. Support quietly widens underneath, covering nestedLogit, brms finite mixtures, and offsets under population and average estimation. Plotting gets attention in proportion to how often these results are presented rather than tabulated, including collapse_by_group() for showing averaged raw data under mixed-model fits.
◆ Prediction
With post_process and omnibus tests both landed, the likely next step is making these composed comparisons easier to report — formatting or plotting methods for the multi-step results rather than new comparison types.
osmdata
0.0ANALYTICS
osmdata keeps tightening its Overpass query surface, breaking small things to get types right.
◆ Current state
The last two releases are the substantive ones. 0.4.0 lets `getbb()` resolve OSM relations via Wikidata ids, adds `filter_osm_user()` to Overpass query objects, and corrects metadata typing so timestamps are POSIXct rather than locale-dependent strings. 0.3.0 dropped the re-exported magrittr pipe, raised the R floor to 4.1 for the base pipe, and fixed polygon output to follow the OGC simple-features model instead of treating every ring as an independent polygon. Earlier entries are CRAN repairs and query-construction fixes.
◆ Where it's heading
The pattern is deliberate correctness work: each release accepts a small breaking change to make returned objects match the standard they claim to follow, whether that is OGC polygon structure, POSIXct timestamps, or UTF-8 metadata columns. Alongside it, the Overpass query builder keeps gaining filters — by area, by out type, by osm_types, now by user and via Wikidata. The package is maturing rather than expanding.
◆ Prediction
More Overpass filter and query-object composition helpers are the likeliest next additions, since that is where both recent releases put their new surface.
Alternatives to modelbased and osmdata
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 modelbased or osmdata.
writexl
writexl spent nine years refusing to do formatting, then shipped all of it in 2.0.0.
rgbif
rgbif is steadily pushing users off paged searching and onto real downloads.
rstanarm
rstanarm is community-maintained now, tracking Stan and lme4 rather than adding models.
taxa
taxa started a ground-up rewrite in 2021 and has published almost nothing since.
rotl
rotl's whole release history is keeping name matching honest against a moving taxonomy.
See all modelbased alternatives → · See all osmdata alternatives →
Recent activity from modelbased and osmdata
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1mo agomodelbasedmodelbased 0.16.0 adds post-processing and omnibus contrast tests
- 1mo agoosmdataosmdata 0.4.0
- 3mo agomodelbasedmodelbased 0.15.0 contrasts average slopes across numeric predictors
- 5mo agomodelbasedmodelbased 0.14.0 renames trend to slope and adds collapse_by_group()
- 8mo agomodelbasedmodelbased 0.13.1 adds marginal group-level estimates and as.data.frame()
- 11mo agomodelbasedmodelbased 0.13.0 adds inequality ratios and slope marginalization
- 11mo agoosmdataosmdata 0.3.0
- 1y agomodelbasedmodelbased 0.12.0 introduces marginal effects inequality measures
- 2y agoosmdataosmdata 0.2.5 resubmitted after CRAN removal
- 3y agoosmdataosmdata 0.2.3 fixes test broken by sp deprecation
- 3y agoosmdataosmdata 0.2.2 adds out:csv queries and centre coordinates
- 3y agoosmdataosmdata 0.2.1 deprecates nodes_only, fixes memory leaks
Frequently asked questions
What is the difference between modelbased and osmdata?
They serve adjacent needs but don't currently overlap on shipped themes. modelbased and osmdata 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.
Is modelbased better than osmdata?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. modelbased and osmdata 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 Analytics products to evaluate alongside.
What are the best alternatives to modelbased?
Top modelbased alternatives in Analytics are ranked by recent ship velocity. Browse the "modelbased alternatives" section above for the current picks, or visit /alternatives/modelbased for the full list with editorial commentary on each.
What are the best alternatives to osmdata?
Top osmdata alternatives in Analytics are ranked by recent ship velocity. Browse the "osmdata alternatives" section above for the current picks, or visit /alternatives/osmdata for the full list with editorial commentary on each.