Feature

Metadata are essential for finding, accessing, and reusing scholarly content, i.e. to increase the FAIRness [Wilkinson et al. (2016)] of datasets and other scholarly resources. A rich and standardized metadata schema that is widely used is the first step, encouraging users to register these metadata (as many of these

In May, the Make Data Count team announced that we have received additional funding from the Alfred P. Sloan Foundation for work on the Make Data Count (MDC) initiative. This will enable DataCite to do additional work in two important areas: * Implement a bibliometrics dashboard that enables bibliometricians – funded by

In a blog post four weeks ago DataCite Executive Director Matt Buys talked about the DataCite strategic priorities for 2020 (Buys, 2020). In this post we want to talk a bit more about the strategic priorities for this year we have regarding services and infrastructure work: a) consolidation of our

DOI content negotiation is one of the oldest DataCite services, launched in 2012. Content negotiation makes it easy to fetch DataCite metadata in other metadata formats, for example BibTeX or schema.org, or as formatted citation in one of more than 5,000 citation styles. For example: curl -LH "

The connections between scholarly resources generated by persistent identifiers (PIDs) and associated metadata form a graph: the PID Graph [Fenner & Aryani (2019)]. We developed this PID Graph concept in the EC-funded FREYA project, and have identified important use cases and technical requirements. In May, DataCite introduced a GraphQL API

Two weeks ago DataCite announced the pre-release version of a GraphQL API [Fenner (2019)]. GraphQL simplifies complex queries that for example want to retrieve information about the authors, funding and data citations for a dataset with a DataCite DOI. These connections together form the PID Graph [Fenner & Aryani (2019)