The next phase in making data a first class scholarly output | Dimensions

Ingestion of datasets into Dimensions demonstrates Digital Science’s commitment to the elevation of data to a first class output, a first step on what we see to be a long and complex, but worthwhile endeavour. Dimensions aims to pull in high quality metadata about datasets, linked out through DOIs and potential other PIDs in future. The approach thus far has been to target the low-hanging fruit. This will be done via Figshare and DataCite APIs. Figshare metadata has been pulled for the first release, to be topped up with DataCite metadata for repositories that are known to have high quality, clean metadata. This will be an ongoing process and like Dimensions other indexing, will be curated by humans and machines and extended over time. The first tranche contains nearly 1.5 million datasets and includes datasets associated with publications from publisher data repositories including Springer Nature, PLOS, Frontiers and the American Chemical Society, amongst others. Also included is Figshare, Zenodo, Dryad and Pangaea. Content in these repositories that is not labelled as a dataset does not get indexed. By pulling metadata from DataCite, Dimensions will be able to add another large corpus of metadata about datasets, including those from University Data Repositories.