A new CRAN release with much improved unit testing and documentation to meet the rOpenSci standards and better methods for the main s3 classes of the package.
dataset_df
and defined
.bibrecord
.dataset_to_triples
and xsd_convert
for better serialisation.var_labels()
now similar to labelled::var_lables()
behavior, generally
haven_labelled_defined as an s3 class works better in the tidyverse.dataset_format()
and contributor()
.subject()
bibrecord()
class is handles is the superclass of the dublincore
and
datacite()
classes; these classes have a new print method and they are conforming
the current library standard DCTERMS and current repository standard DataCite;
unlike utils::bibentry()
, they handle contributors and their roles, identifiers,
and many other attributes.definition
metadata field in the defined()
class is
changed to the more understandable concept
name.defined()
vectors print nicely, and the dataset_df()
class is more
readable, too.orange_df
example dataset.iris_df
to orange_df
in all examples.xsd_convert()
handles difftime classes and edge cases.master
branch is renamed to main
.length()
, head()
, tail()
, as.vector()
, as.list()
, and subsetting ([
, [[
).==
, <
, >
, etc.) that operate on the underlying data while maintaining semantic integrity.print()
and format()
methods that summarise metadata (label, unit, definition) in a concise and human-readable manner.summary()
method for defined
vectors to display variable metadata and integrate seamlessly with base R statistics.c()
method to validate compatibility across all semantic attributes (label
, unit
, definition
, namespace
) before concatenation.compare_creators()
internal function to add all creators to joined datasets.This update significantly improves the usability and robustness of semantically enriched vectors in both interactive and programmatic workflows.
definition
attributes is renamed to concept
.defined
and dataset_df
classes.bibrecord
class for extending utils::person
and utils::bibentry
classes for more modern and cleaner bibliographic references.dataset_ttl_write()
: write datasets to turtle format;get_prefix()
, get_resource_identifier()
, xsd_convert()
, and dataset_to_triples()
.New vignettes on
The devel branch contains new code that is not is validated, but as a whole the package is not working consistently.
datacite()
has a new interface and an as_datacite()
retrieval version. See the Working with DataCite Metadata
vignette.dublincore()
has a new interface and an as_dublincore()
version. See the Working with Dublin Core Metadata
vignette.All tests are passing but documentation is not rewritten yet.
new subject class for recording subjects
New s3 classes for DataCite and Dublin Core bibliographic entries.
A minor correction to avoid vignettes downloading data from the Eurostat data warehouse on CRAN. Small readability improvements in the vignette articles.
dataset()
s3 class: print.dataset()
, summary.dataset()
, subset.dataset
, [.dataset
, as.data.frame()
.dataset_local_id()
and dataset_uri()
to the dataset functions. Development version available on Zenodo.
dataset_export()
is implemented with filetype = 'csv'.identifier()
, publisher()
, publication_year()
, language()
, description()
, datasource_get()
and datasource_set()
[to avoid confusion with the base R source() function], geolocation()
, rights()
, version()
.dataset_title()
, subject()
, subject_create()
.download_dataset()
, datacite()
, and the dataset()
constructor.dataset()
class, an improved data.frame (tibble, DT) R object with standardized structure and metadata. First development version release.
Motivation of the dataset package
vignette article, which is later
replaced with Design Principles & Future Work Semantically Enriched, Standards-Aligned Datasets in R.