dataone: R interface to the DataONE network of data repositories

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Provides read and write access to data and metadata from the DataONE network of data repositories, including the KNB Data Repository, Dryad, and the NSF Arctic Data Center. Each DataONE repository implements a consistent repository application programming interface. Users call methods in R to access these remote repository functions, such as methods to query the metadata catalog, get access to metadata for particular data packages, and read the data objects from the data repository using the global identifier for each data object. Users can also insert and update data objects on repositories that support these methods. For more details, see the vignettes.

Installation Notes

Version 2.0 of the dataone R package removes the dependency on rJava and significantly changes the base API to correspond to the published DataONE API. Previous methods for accessing DataONE will be maintained, but new methods have been added.

The dataone R package requires the R package redland. If you are installing on Ubuntu then the Redland C libraries must be installed first. If you are installing on Mac OS X or Windows then installing these libraries is not required.

Installing on Mac OS X

On Mac OS X dataone can be installed with the following commands:


The dataone R package should be available for use at this point.

Installing on Ubuntu

For ubuntu, install the required Redland C libraries by entering the following commands in a terminal window:

sudo apt-get update
sudo apt-get install librdf0 librdf0-dev

Then install the R packages from the R console:


The dataone R package should be available for use at this point

Installing on Windows

For windows, the required redland R package is distributed as a binary release, so it is not necessary to install any additional system libraries.

To install the dataone R packages from the R console:


The dataone R package should be available for use at this point.

Quick Start

See the full manual (help(dataone)) for documentation.

To search the DataONE Federation Member Node Knowledge Network for Biocomplexity (KNB) for a dataset:

cn <- CNode("PROD")
mn <- getMNode(cn, "urn:node:KNB")
mySearchTerms <- list(q="abstract:salmon+AND+keywords:spawn+AND+keywords:chinook",
                      fq="dateUploaded:[2017-06-01T00:00:00.000Z TO 2017-07-01T00:00:00.000Z]",
result <- query(mn, solrQuery=mySearchTerms, as="data.frame")
result[1,c("id", "title")]
id <- result[1,'id']

The metadata file that describes the located research can be downloaded and viewed in an XML viewer, text editor after being written to disk, or in R via the commands below:

metadata <- rawToChar(getObject(mn, id))
doc <- xmlRoot(xmlTreeParse(metadata, asText=TRUE, trim = TRUE, ignoreBlanks = TRUE))
tf <- tempfile()
saveXML(doc, tf)

This metadata file describes a data file (CSV) in this data collection (package) that can be obtained using the listed identifier, using the commands:

dataRaw <- getObject(mn, "urn:uuid:49d7a4bc-e4c9-4609-b9a7-9033faf575e0")
dataChar <- rawToChar(dataRaw)
theData <- textConnection(dataChar)
df <- read.csv(theData, stringsAsFactors=FALSE)

Uploading a CSV file to a DataONE Member Node requires user authentication. DataONE user authentication is described in the vignette dataone-federation.

Once the authentication steps have been followed, uploading is done with:

d1c <- D1Client("STAGING", "urn:node:mnStageUCSB2")
id <- paste("urn:uuid:", UUIDgenerate(), sep="")
testdf <- data.frame(x=1:10,y=11:20)
csvfile <- paste(tempfile(), ".csv", sep="")
write.csv(testdf, csvfile, row.names=FALSE)
# Build a DataObject containing the csv, and upload it to the Member Node
d1Object <- new("DataObject", id, format="text/csv", filename=csvfile)
uploadDataObject(d1c, d1Object, public=TRUE)

In addition, a collection of science metadata and data can be downloaded with one command, for example:

d1c <- D1Client("PROD", "urn:node:KNB")
pkg <- getDataPackage(d1c, id="urn:uuid:04cd34fd-25d4-447f-ab6e-73a572c5d383", quiet=FALSE)

See the R vignette dataone R Package for more information.


Work on this package was supported by:

Additional support was provided for working group collaboration by the National Center for Ecological Analysis and Synthesis, a Center funded by the University of California, Santa Barbara, and the State of California.