Dataspice makes it easier for researchers to create basic, lightweight, and concise metadata files for their datasets by editing the kind of files they’re probably most familiar with: CSVs.
These csv files can be directly modified, or they can be edited using either associated helper function and/or deploying dataspice shiny apps which help guide through metadata collection.
These metadata csv files can then be used to:
- Make useful information available during analysis.
- Create a helpful dataset README webpage for data.
- Produce more complex metadata formats for richer description of datasets and to aid dataset discovery.
Metadata fields are based on Schema.org/Dataset and other metadata standards and represent a lowest common denominator which means converting between formats should be relatively straightforward.
Typical Dataspice workflow
This project was a team effort developed as part of rOpenSci unconf 2018 and is now available on CRAN. I’ve also developed a number of training materials using it, to teach data producers to develop accompanying minimal metadata in R.
