tidytlg
A tables-listings-graphs package that reached CRAN and then went quiet.
A side-by-side editorial comparison of datasetjson and riem — release velocity, themes, recent moves, and the top alternatives to consider.
datasetjson rebuilt its object model to track the CDISC Dataset-JSON 1.1 schema.
datasetjson reads and writes CDISC Dataset-JSON, the JSON replacement for SAS transport files in clinical-trial submissions. The package went from a thin reader in 2023 to a redesigned interface in 0.3.0 that targets the 1.1.0 schema, uses yyjsonr as its JSON backend, and exposes column metadata as first-class arguments. Development is contributor-driven inside the Atorus and pharmaverse orbit.
A weather-data client that keeps rewriting its HTTP layer while slowly tightening its API.
riem pulls observations from the Iowa Environmental Mesonet's weather-station network. Its release history is two threads: successive rewrites of the HTTP and test-mocking stack, and a gradual tightening of function arguments that culminated in 1.0.0 removing convenient-but-dangerous defaults. Contributions come partly from IEM's own maintainer.
datasetjson reads and writes CDISC Dataset-JSON, the JSON replacement for SAS transport files in clinical-trial submissions. The package went from a thin reader in 2023 to a redesigned interface in 0.3.0 that targets the 1.1.0 schema, uses yyjsonr as its JSON backend, and exposes column metadata as first-class arguments. Development is contributor-driven inside the Atorus and pharmaverse orbit.
The package's roadmap is not its own — it tracks a CDISC standard that is still moving, and 0.3.0 is what happens when the standard revises: object model, read and write paths, and JSON backend all changed together. Performance was addressed in the same pass, which matters because submission datasets are large enough that a slow serialiser is a real constraint.
The next significant release will most likely follow the next Dataset-JSON schema revision rather than an internal roadmap, given that 0.3.0 was driven entirely by the 1.1.0 update.
riem pulls observations from the Iowa Environmental Mesonet's weather-station network. Its release history is two threads: successive rewrites of the HTTP and test-mocking stack, and a gradual tightening of function arguments that culminated in 1.0.0 removing convenient-but-dangerous defaults. Contributions come partly from IEM's own maintainer.
The HTTP thread has moved through httr to httr2, and mocking from vcr to httptest2 — following the broader rOpenSci HTTP-stack reorganisation rather than any need of its own. The API thread runs the other way: 1.0.0 removed defaults for date_start and station and flipped latlon to FALSE, trading convenience for callers being explicit about what they request. New arguments in the same release widened what a query can ask for.
With the API stabilised at 1.0.0 and the HTTP stack settled on httr2, the next release is more likely to expose additional IEM query parameters than to change plumbing again.
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 datasetjson or riem.
A tables-listings-graphs package that reached CRAN and then went quiet.
Tplyr made clinical summary tables explain where every number came from.
Clinical listings that keep inheriting their hardest problem — pagination — from the layer below.
A cache-directory helper that has shipped nothing but CRAN-triggered patches for seven years.
gigs redesigned its whole conversion API for rOpenSci, then spent three releases getting the docs to build.
A TIFF reader for scientific imaging that spent its recent releases shedding weight and fixing memory bugs.
See all datasetjson alternatives → · See all riem alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. datasetjson and riem 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. datasetjson and riem 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.
Top datasetjson alternatives in Analytics are ranked by recent ship velocity. Browse the "datasetjson alternatives" section above for the current picks, or visit /alternatives/datasetjson for the full list with editorial commentary on each.
Top riem alternatives in Analytics are ranked by recent ship velocity. Browse the "riem alternatives" section above for the current picks, or visit /alternatives/riem for the full list with editorial commentary on each.