Package: metajam 0.3.2

Julien Brun

metajam: Easily Download Data and Metadata from 'DataONE'

A set of tools to foster the development of reproducible analytical workflow by simplifying the download of data and metadata from 'DataONE' (<https://www.dataone.org>) and easily importing this information into R.

Authors:Julien Brun [cre, aut], Irene Steves [aut], Mitchell Maier [aut], Kristen Peach [aut], Nicholas Lyon [aut], Nathan Hwangbo [ctb], Derek Strong [ctb], Colin Smith [ctb], Regents of the University of California [cph]

metajam_0.3.2.tar.gz
metajam_0.3.2.zip(r-4.7-any)metajam_0.3.2.zip(r-4.6-any)metajam_0.3.2.zip(r-4.5-any)
metajam_0.3.2.tgz(r-4.6-any)metajam_0.3.2.tgz(r-4.5-any)
metajam_0.3.2.tar.gz(r-4.7-any)metajam_0.3.2.tar.gz(r-4.6-any)
metajam_0.3.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
metajam/json (API)

# Install 'metajam' in R:
install.packages('metajam', repos = c('https://nceas.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/nceas/metajam/issues

Pkgdown/docs site:https://nceas.github.io

On CRAN:

Conda:

datadata-analysismetadatarepositories

6.76 score 16 stars 89 scripts 42 downloads 5 exports 85 dependencies

Last updated from:41c6947950. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK174
source / vignettesOK226
linux-release-x86_64OK169
macos-release-arm64OK156
macos-oldrel-arm64OK99
windows-develOK108
windows-releaseOK104
windows-oldrelOK105
wasm-releaseOK155

Exports:check_versiondownload_d1_datadownload_d1_data_pkgread_d1_filestabularize_eml

Dependencies:askpassbase64encbitbit64brewbslibcachemcallrclicliprcommonmarkcpp11crayoncurldataonedatapackdescdigestdplyrEMLemldevaluatefastmapfontawesomefsgenericsgluehighrhmshtmltoolshttrjqrjquerylibjsonldjsonliteknitrlazyevallifecyclelubridatemagrittrmemoisemimeopensslotelparsedatepillarpkgbuildpkgconfigpkgloadplyrprettyunitsprocessxprogresspspurrrR6rappdirsRcppreadrredlandrlangrmarkdownroxygen2rprojrootsassstringistringrsystibbletidyrtidyselecttimechangetinytextzdbutf8uuidV8vctrsvroomwithrxfunXMLxml2yamlzip

Use Case 1 - Processing a Single Dataset from Arctic Data Center
Summary | Libraries and constants | Download the dataset | Read the data and metadata in your R environment | Structure of the named list object
Rendered fromuse01_dataset-single-arctic.Rmdusingknitr::rmarkdown

Last update: 2026-06-30
Started: 2024-04-16

Use Case 2 - Processing a Single Dataset from DataOne
Summary | Note on data url provenance when using download_d1_data.R | Metadata format dictates metajam output | Example 1: eml | Libraries and constants | Download the dataset | Read the data and metadata in your R environment | Structure of the named list object | Example 2: iso
Rendered fromuse02_dataset-single-dataone.Rmdusingknitr::rmarkdown

Last update: 2026-06-23
Started: 2024-04-16

Use Case 4 - Processing a Raster Dataset
Summary | Libraries and constants | Download the raster dataset | Read the raster file and metadata in your R environment | Investigate the metadata
Rendered fromuse04_reading-raster.Rmdusingknitr::rmarkdown

Last update: 2026-06-23
Started: 2024-04-16

Use Case 3 - Processing Several Datasets
Summary | Libraries | Constants | Download the datasets | Read the data and metadata in your R environment | Perform checks on data structure | Conclusion | Perform checks on the units | Fixing units discrepancies | Append all the sampling sites into one master dataset | General Conclusion
Rendered fromuse03_dataset-batch-processing.Rmdusingknitr::rmarkdown

Last update: 2024-07-02
Started: 2024-04-16

Use Case 5 - Downloading Entire Data Packages Using DOIs
Summary | Libraries and constants | Download all the datasets from data packages using DOIs
Rendered fromuse05_package-download.Rmdusingknitr::rmarkdown

Last update: 2024-04-16
Started: 2024-04-16