tidytlg
A tables-listings-graphs package that reached CRAN and then went quiet.
A side-by-side editorial comparison of cffr and datasetjson — release velocity, themes, recent moves, and the top alternatives to consider.
cffr keeps CITATION.cff generation in step with the standard and its R sources.
The package generates and validates CITATION.cff files from R package metadata. Recent work is validation and parsing accuracy rather than new outputs: cff_validate() moved onto the ajv engine through jsonvalidate for clearer errors, ROR identifiers act as a website fallback for people and entities, and DOIs are now detected in inst/CITATION url fields including dx.doi.org forms.
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.
The package generates and validates CITATION.cff files from R package metadata. Recent work is validation and parsing accuracy rather than new outputs: cff_validate() moved onto the ajv engine through jsonvalidate for clearer errors, ROR identifiers act as a website fallback for people and entities, and DOIs are now detected in inst/CITATION url fields including dx.doi.org forms.
The package tracks two moving targets — the Citation File Format schema and R's own person and citation handling, which has broken extraction twice in recent releases. Between those, releases pick up ecosystem details: Codeberg recognised as a repository host, CRAN-to-SPDX licence mappings refreshed, GitHub Action defaults changed to save quota. The most recent release is an internal refactor carried out with AI assistance, with no user-facing change.
With validation migrated and the R 4.5 person changes absorbed, the next release most likely follows a Citation File Format schema update rather than adding capability.
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.
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 cffr or datasetjson.
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 weather-data client that keeps rewriting its HTTP layer while slowly tightening its API.
See all cffr alternatives → · See all datasetjson alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. cffr and datasetjson 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. cffr and datasetjson 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 cffr alternatives in Analytics are ranked by recent ship velocity. Browse the "cffr alternatives" section above for the current picks, or visit /alternatives/cffr for the full list with editorial commentary on each.
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.