Data Publication

The Citation File Format version 1.2.0 doi:10.5281/zenodo.5171937 is a human and machine readable file format which provides citation metadata for software. This package provides core utilities to generate and validate this metadata.

Read and write Frictionless Data Packages. A Data Package (https://specs.frictionlessdata.io/data-package/) is a simple container format and standard to describe and package a collection of (tabular) data. It is typically used to publish FAIR (https://www.go-fair.org/fair-principles/) and open datasets.

Helps store files as GitHub release assets, which is a convenient way for large/binary data files to piggyback onto public and private GitHub repositories. Includes functions for file downloads, uploads, and managing releases via the GitHub API.

1. Boettiger, C. (2018). Managing Larger Data on a GitHub Repository. Journal of Open Source Software, 3(29), 971. https://doi.org/10.21105/joss.00971

The Codemeta Project defines a JSON-LD format for describing software metadata, as detailed at https://codemeta.github.io. This package provides utilities to generate, parse, and modify codemeta.json files automatically for R packages, as well as tools and examples for working with codemeta.json JSON-LD more generally.

A universal client for depositing and accessing research data anywhere. Currently supported services are zenodo and figshare.

A tiny package to generate CRediT author statements (https://credit.niso.org/). It provides three functions: create a template, read it back and generate the CRediT author statement in a text file.

Provides access to phyloinformatic data in NeXML format. The package should add new functionality to R such as the possibility to manipulate NeXML objects in more various and refined way and compatibility with ape objects.

1. Stöver, B. C., Wiechers, S., & Müller, K. F. (2019). JPhyloIO: a Java library for event-based reading and writing of different phylogenetic file formats through a common interface. BMC Bioinformatics, 20(1). https://doi.org/10.1186/s12859-019-2982-3

Work with Ecological Metadata Language (EML) files. EML is a widely used metadata standard in the ecological and environmental sciences, described in Jones et al. (2006), doi:10.1146/annurev.ecolsys.37.091305.110031.

The goal of dataspice is to make it easier for researchers to create basic, lightweight, and concise metadata files for their datasets. These basic files can then be used to make useful information available during analysis, create a helpful dataset “README” webpage, and produce more complex metadata formats to aid dataset discovery. Metadata fields are based on the Schema.org and Ecological Metadata Language standards.