dataset: Create Data Frames that are Easier to Exchange and Reuse

The aim of the 'dataset' package is to make tidy datasets easier to release, exchange and reuse. It organizes and formats data frame 'R' objects into well-referenced, well-described, interoperable datasets into release and reuse ready form. A subjective interpretation of the W3C DataSet recommendation and the datacube model <https://www.w3.org/TR/vocab-data-cube/>, which is also used in the global Statistical Data and Metadata eXchange standards, the application of the connected Dublin Core <https://www.dublincore.org/specifications/dublin-core/dcmi-terms/> and DataCite <https://support.datacite.org/docs/datacite-metadata-schema-44/> standards preferred by European open science repositories to improve the findability, accessibility, interoperability and reusability of the datasets.

Version: 0.2.0
Depends: R (≥ 2.10)
Imports: assertthat, ISOcodes, stats, utils
Suggests: dataspice, covr, declared, dplyr, eurostat, here, kableExtra, knitr, rdflib, readxl, rmarkdown, spelling, statcodelists, testthat (≥ 3.0.0), tidyr
Published: 2022-12-14
Author: Daniel Antal ORCID iD [aut, cre], Marcelo Perlin ORCID iD [rev]
Maintainer: Daniel Antal <daniel.antal at dataobservatory.eu>
BugReports: https://github.com/dataobservatory-eu/dataset/issues
License: GPL (≥ 3)
URL: https://github.com/dataobservatory-eu/dataset
NeedsCompilation: no
Language: en-US
Citation: dataset citation info
Materials: README NEWS
CRAN checks: dataset results

Documentation:

Reference manual: dataset.pdf
Vignettes: From dataset To RDF
The dataset S3 Class
Use with dataspice
Datasets With FAIR Metadata
Motivation: Make Tidy Datasets Easier to Release Exchange and Reuse
Export And Publish a dataset
Reproducible Datasets
The survey Class

Downloads:

Package source: dataset_0.2.0.tar.gz
Windows binaries: r-devel: dataset_0.2.0.zip, r-release: dataset_0.2.0.zip, r-oldrel: dataset_0.2.0.zip
macOS binaries: r-release (arm64): dataset_0.2.0.tgz, r-oldrel (arm64): dataset_0.2.0.tgz, r-release (x86_64): dataset_0.2.0.tgz, r-oldrel (x86_64): dataset_0.2.0.tgz
Old sources: dataset archive

Linking:

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