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Open Source Science

dataset

Create interoperable and well described data frames in R

https://github.com/ropensci/dataset

Science Score: 39.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ○
    CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ✓
    DOI references
    Found 2 DOI reference(s) in README
  • ○
    Academic publication links
  • ○
    Academic email domains
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (18.4%) to scientific vocabulary

Keywords

dataset metadata-management r rstats
Last synced: 10 months ago · JSON representation

Repository

Create interoperable and well described data frames in R

Basic Info
Statistics
  • Stars: 18
  • Watchers: 1
  • Forks: 8
  • Open Issues: 14
  • Releases: 10
Topics
dataset metadata-management r rstats
Created almost 4 years ago · Last pushed 10 months ago
Metadata Files
Readme Changelog Contributing License Code of conduct Codemeta

README.Rmd 

---
output: github_document
---



```{r setupdefinitions, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)
rlang::check_installed("here")
```

# The dataset R Package 




[![rhub](https://github.com/ropensci/dataset/actions/workflows/rhub.yaml/badge.svg)](https://github.com/ropensci/dataset/actions/workflows/rhub.yaml)
[![devel-version](https://img.shields.io/badge/devel%20version-0.4.0-blue.svg)](https://github.com/ropensci/dataset)
[![Codecov test coverage](https://codecov.io/gh/ropensci/dataset/branch/main/graph/badge.svg)](https://app.codecov.io/gh/ropensci/dataset?branch=main)
[![Project Status: Active](https://www.repostatus.org/badges/latest/active.svg)](https://www.repostatus.org/#active)
[![CRAN_Status_Badge](https://www.r-pkg.org/badges/version/dataset)](https://cran.r-project.org/package=dataset)
[![CRAN_time_from_release](https://www.r-pkg.org/badges/ago/dataset)](https://cran.r-project.org/package=dataset)
[![Status at rOpenSci Software Peer Review](https://badges.ropensci.org/681_status.svg)](https://github.com/ropensci/software-review/issues/681)
[![DOI](https://img.shields.io/badge/DOI-10.32614%2FCRAN.package.dataset-blue)](https://doi.org/10.32614/CRAN.package.dataset)
[![dataobservatory](https://img.shields.io/badge/ecosystem-dataobservatory.eu-3EA135.svg)](https://dataobservatory.eu/)



# Overview

The `dataset` package helps you create **semantically rich**, **machine-readable**, and **interoperable datasets** in R. It introduces S3 classes that extend data frames, vectors, and bibliographic entries with formal metadata structures inspired by:

- **SDMX** (Statistical Data and Metadata eXchange), widely used in official statistics  
- **Dublin Core** and **DataCite**, for FAIR-compliant depositing and reuse in scientific and open data repositories  
- **Open Science publishing practices**, to support transparent and reproducible research  

The goal is to preserve metadata when reusing statistical and repository datasets, improve interoperability, and make it easy to turn tidy data frames into web-ready, publishable datasets that comply with ISO and W3C standards.


## Installation

You can install the latest released version of **`dataset`** from [CRAN](https://cran.r-project.org/package=dataset) with:

```{r, eval=FALSE}
install.packages("dataset")
```

To install the development version from GitHub with `pak` or `remotes`:

```{r, eval=FALSE}
# install.packages("pak")
pak::pak("dataobservatory-eu/dataset")

# install.packages("remotes")
remotes::install_github("dataobservatory-eu/dataset")
```


## Minimal Example

```{r example}
library(dataset)
df <- dataset_df(
  country = defined(
    c("AD", "LI"),
    label = "Country",
    namespace = "https://www.geonames.org/countries/$1/"
  ),
  gdp = defined(c(3897, 7365),
    label = "GDP",
    unit = "million euros"
  ),
  dataset_bibentry = dublincore(
    title = "GDP Dataset",
    creator = person("Jane", "Doe", role = "aut"),
    publisher = "Small Repository"
  )
)
print(df)
```

Export as RDF triples:

```{css, echo=FALSE}
.smaller .table {
  font-size: 11px;
}

.smaller pre,
.smaller code {
  font-size: 11px;
  line-height: 1.2;
}
```

```{r ntriples, eval = FALSE}
dataset_to_triples(df, format = "nt")
```

::: smaller
```{r ntriplessmall, echo=FALSE}
dataset_to_triples(df, format = "nt")
```
:::

Retain automatically recorded provenance: 

```{r provenance, eval=FALSE}
provenance(df)
```

::: smaller
```{r provenancesmall, echo=FALSE}
provenance(df)
```
:::

## Contributing

We welcome contributions and discussion!

-   Please see our [CONTRIBUTING.md](https://github.com/dataobservatory-eu/dataset/blob/main/CONTRIBUTING.md) guide.
-   Ideas, bug reports, and feedback are welcome via [GitHub issues](https://github.com/dataobservatory-eu/dataset/issues).
-  The design principles and ideas for futher development are explained in [Design Principles & Future Work Semantically Enriched, Standards-Aligned Datasets in R](https://dataset.dataobservatory.eu/articles/design.html).

## Code of Conduct

This project follows the [rOpenSci Code of Conduct](https://ropensci.org/code-of-conduct/). By participating, you are expected to uphold these guidelines.

Owner

  • Name: rOpenSci
  • Login: ropensci
  • Kind: organization
  • Email: info@ropensci.org
  • Location: Berkeley, CA

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GitHub Events

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  • Issue comment event: 1
  • Member event: 1
  • Push event: 1
Last Year
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Dependencies

.github/workflows/pkgcheck.yaml actions
  • ropensci-review-tools/pkgcheck-action main composite
.github/workflows/test-coverage.yaml actions
  • actions/checkout v2 composite
  • r-lib/actions/setup-r v2 composite
  • r-lib/actions/setup-r-dependencies v2 composite
DESCRIPTION cran
  • R >= 2.10 depends
  • ISOcodes * imports
  • assertthat * imports
  • stats * imports
  • utils * imports
  • covr * suggests
  • dataspice * suggests
  • declared * suggests
  • dplyr * suggests
  • eurostat * suggests
  • here * suggests
  • kableExtra * suggests
  • knitr * suggests
  • rdflib * suggests
  • readxl * suggests
  • rmarkdown * suggests
  • spelling * suggests
  • statcodelists * suggests
  • testthat >= 3.0.0 suggests
  • tidyr * suggests
.github/workflows/R-CMD-check.yaml actions
  • actions/checkout v3 composite
  • r-lib/actions/check-r-package v2 composite
  • r-lib/actions/setup-pandoc v2 composite
  • r-lib/actions/setup-r v2 composite
  • r-lib/actions/setup-r-dependencies v2 composite