Finding associated datasets
Ranger, H. 2022. Finding associated datasets. Zenodo. https://doi.org/10.5281/zenodo.10992343
Ranger, H. 2022. Finding associated datasets. Zenodo. https://doi.org/10.5281/zenodo.10992343
| Title | Finding associated datasets |
|---|---|
| Authors | Ranger, H. |
| Description | There is a growing need to discover, register, and track citations for externally-published datasets associated with the research outputs recorded in our institutional repositories. This need will only increase with the new UKRI mandate to include Data Access Statements for all in-scope articles. We know we can use identifiers and software to find and retrieve the metadata for much of this material. However, there is a skills and resourcing gap, as well as limitations with the various methods (PIDs aren't used consistently, metadata from APIs is of varying quality, and the creation of a data registry still has to be done manually). This document collates and evaluates resources and tools for librarians, research data managers, and information professionals seeking to create an institutional data registry for catalogue for associated datasets. It was presented at a Jisc Digital Research Community monthly event (July 2022), 'Datasets in the Wild', facilitated by Holly Ranger, University of Westminster, Nick Sheppard, University of Leeds and Mick Eadie/Valerie McCutcheon, University of Glasgow. |
| Year | 2022 |
| Publisher | Zenodo |
| Digital Object Identifier (DOI) | https://doi.org/10.5281/zenodo.10992343 |