Scientific Data launched in May 2014, introducing a new type of content called the Data Descriptor designed to make data more discoverable, interpretable and reusable. Check out our first publications online.
Our Data Descriptors fall broadly into two categories First descriptions of datasets These often describe valuable, unpublished datasets that may be hard to fit into a traditional research article context. See our first publications for clear demonstrations that Scientific Data can help motivate scientists to share valuable datasets that might not have otherwise seen the light day. Follow-up articles These articles provide fuller descriptions and more complete release of datasets analysed in previous publications. In these cases, the value of the underlying datasets is often already well-demonstrated, but for groundbreaking studies, where there are not established standards or data repositories, a substantial amount of additional information is often needed before others can actually reuse the data. Data Descriptors at Scientific Data help motivate the authors to release datasets more fully, and the Data Descriptor manuscripts can provide more detailed descriptions of the data collection methods and the data file formats—essential information for others who may wish to reuse the data.
Visibility for repository Subject specific data is stored with other related data, easier discovery for researchers
A metajournal which encourages the publication of information that encourages the reuse of software. A way of using the current tools and practices to make software better recognised.
I am part of the team running DataCite in the UK. We work with organisations to provide persistent identifiers in the form of DOIs for their research data – although they are applied to other objects as well.
My other role is generally looking at the data activities of the Library. This is important for the Library right now, as one of the key aims of the Library’s current strategy (‘Living Knowledge’) is this: