tidytlg
A tables-listings-graphs package that reached CRAN and then went quiet.
Comparison · Analytics
datapack vs gigs
A side-by-side editorial comparison of datapack and gigs — release velocity, themes, recent moves, and the top alternatives to consider.
datapack vs gigs: at a glance
What is datapack?
The DataONE bundler learned to edit packages in 2017 and has coasted on that ever since
datapack assembles heterogeneous data files and metadata into a single transportable bundle, serialised as an OAI-ORE resource map and BagIt archive, for deposit into repositories like DataONE. Its functional surface settled with the 1.3.x line, which made assembled packages editable rather than write-once. Since then the releases have been sparse and defensive: SHA-256 as the default checksum in 1.4.0, BagIt spec conformance in 1.4.1, and a 2025 patch that states outright it contains no new features.
What is gigs?
gigs redesigned its whole conversion API for rOpenSci, then spent three releases getting the docs to build.
gigs implements international newborn and infant growth standards — INTERGROWTH-21st, WHO — converting anthropometric measurements to z-scores and centiles and classifying growth outcomes. The 0.5.0 release rewrote the public API around rOpenSci review feedback; the two releases after it change no code at all, existing purely to get the documentation site building.
datapack vs gigs: editorial side-by-side
datapack
0.0ANALYTICS
The DataONE bundler learned to edit packages in 2017 and has coasted on that ever since
◆ Current state
datapack assembles heterogeneous data files and metadata into a single transportable bundle, serialised as an OAI-ORE resource map and BagIt archive, for deposit into repositories like DataONE. Its functional surface settled with the 1.3.x line, which made assembled packages editable rather than write-once. Since then the releases have been sparse and defensive: SHA-256 as the default checksum in 1.4.0, BagIt spec conformance in 1.4.1, and a 2025 patch that states outright it contains no new features.
◆ Where it's heading
The arc runs from assembly to correctness of the resulting archive. Later releases keep tightening the metadata the resource map must carry — dc:creator always present, dcterms:modified always updated, the package correctly flagged as modified after any access-policy change — because a bundle whose provenance record is subtly wrong is worse than one that fails outright. The three-year gap between 1.4.1 and 1.4.2, and the latter's CRAN-note content, place this package firmly in preservation.
◆ Prediction
Expect the next release, if any, to be another CRAN-compliance patch rather than functional work. The 1.4.2 note that it contains no new features is the clearest statement in the feed about where this package sits.
gigs
0.0ANALYTICS
gigs redesigned its whole conversion API for rOpenSci, then spent three releases getting the docs to build.
◆ Current state
gigs implements international newborn and infant growth standards — INTERGROWTH-21st, WHO — converting anthropometric measurements to z-scores and centiles and classifying growth outcomes. The 0.5.0 release rewrote the public API around rOpenSci review feedback; the two releases after it change no code at all, existing purely to get the documentation site building.
◆ Where it's heading
The package has moved from vector-in, vector-out conversion helpers to a data.frame-oriented interface with a single classify_growth() entry point that computes whatever outcomes the supplied columns allow. That is a shift from library to tool — the user describes their data rather than picking the right function. The trailing releases suggest the code is settled and the remaining work is packaging and discoverability.
◆ Prediction
With the API rewrite absorbed and hosting moved to rOpenSci, the next substantive release should add growth standards or outcomes rather than reshape the interface again.
Alternatives to datapack and gigs
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 datapack or gigs.
Tplyr
Tplyr made clinical summary tables explain where every number came from.
rlistings
Clinical listings that keep inheriting their hardest problem — pagination — from the layer below.
hoardr
A cache-directory helper that has shipped nothing but CRAN-triggered patches for seven years.
riem
A weather-data client that keeps rewriting its HTTP layer while slowly tightening its API.
datasetjson
datasetjson rebuilt its object model to track the CDISC Dataset-JSON 1.1 schema.
See all datapack alternatives → · See all gigs alternatives →
Recent activity from datapack and gigs
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 10mo agodatapackCRAN documentation and CI cleanup
- 1y agogigsDocs and Zenodo archiving
- 1y agogigsDocs-only release; nothing changed internally
- 1y agogigsConversion API rewritten around data frames and classify_growth() ⚡
- 2y agogigsDocumentation fixes for autotest compliance
- 2y agogigsINTERGROWTH-21st fetal standards and input validation
- 2y agogigsPatch release with documentation update
- 4y agodatapackBagIt serialisation brought in line with the current spec
- 5y agodatapackSHA-256 becomes the default checksum algorithm
- 6y agodatapackResource map metadata guaranteed; removeRelationships() added
- 8y agodatapackupdateMetadata no longer drops package relationships
- 9y agodatapackAssembled data packages become editable in place ⚡
Frequently asked questions
What is the difference between datapack and gigs?
They serve adjacent needs but don't currently overlap on shipped themes. datapack and gigs 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 datapack better than gigs?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. datapack and gigs 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 datapack?
Top datapack alternatives in Analytics are ranked by recent ship velocity. Browse the "datapack alternatives" section above for the current picks, or visit /alternatives/datapack for the full list with editorial commentary on each.
What are the best alternatives to gigs?
Top gigs alternatives in Analytics are ranked by recent ship velocity. Browse the "gigs alternatives" section above for the current picks, or visit /alternatives/gigs for the full list with editorial commentary on each.