On Tuesday the journal PLOS ONE celebrated its 10th anniversary (see blog post by PLOS ONE Editor-in-Chief Jörg Heber and blog post by PLOS ONE Managing Editor Iratxe Puebla and PLOS Advocacy Director Catriona MacCallum). PLOS ONE (and PLOS) have changed scholarly publishing in many ways, from a DataCite perspective probably most importantly via the data policy updated in February 2014 that states that PLOS ONE was not the first journal with a

Eating your own dog food is a slang term to describe that an organization should itself use the products and services it provides. For DataCite this means that we should use DOIs with appropriate metadata and strategies for long-term preservation for the scholarly outputs we produce.

Geoff Bilder from CrossRef likes to show the following slide at scholarly conferences, and then asks the audience what they see: Most of us probably immediately recognize this document as a scholarly article.

In 1998 Tim Berners-Lee coined the term cool URIs (1998), that is URIs that don’t change. We know that URLs referenced in the scholarly literature are often not cool, leading to link rot (Klein et al., 2014) and making it hard or impossible to find the referenced resource.

Today we are launching a new version of the DataCite API at http://api.datacite.org. This new version includes numerous bug fixes and now includes related resources (e.g. data centers, members or contributors) according to the JSONAPI spec. The changelog can be found here. Current users of the API should watch out for breaking changes in the meta object used for faceting.

The scholarly research community has come to depend on a series of open identifier and metadata infrastructure systems to great success. Content identifiers (through DataCite and Crossref) and contributor identifiers (through ORCID) have become foundational infrastructure for the community.

On July 12, 2016, DataCite invited Andreas Rauber to present the recommendations for dynamic data citation of the RDA Data Citation Working Group in a webinar. Andreas is one of the co-chairs of the RDA working group, and he gave a throughout overview of the recommendations, and the thinking that went into them. The final recommendations are available since last fall, and the current focus of the working group is to help with implementations.

This week we relaunched DataCite Search, providing a more user-friendly search interface for DataCite metadata. We also added functionality that was not available before. The new search uses a single entry box for queries, and filters by resource type, publication year and data center. A new Cite button will generate a citation in several popular citation styles, and in BibTeX and RIS import formats.

CSV in many ways is for data what Markdown is for text documents: a very simple format that is both human- and machine-readable, and that – despite a number of shortcomings - is widely used. Given the popularity of Markdown for writing blog posts, using CSV to publish blog posts with tabular data should be an obvious thing to do, and we have just published our first blog post using CSV data.

Data citation is core to DataCite's mission and DataCite is involved in several projects that try to facilitate data citation, including THOR, Data Citation Implementation Pilot (DCIP), Research Data Alliance (RDA), and COPDESS. The biggest roadblock for wider data citation adoption might be insufficient incentives for individual researchers, but another major challenge is that implementing data citation is still too complicated.

This week some of us from DataCite are attending CSVconf in Berlin, and we are a conference sponsor and co-organizer. One important reason we are at CSVconf is that providing persistent identifiers and starndard metadata for research data, which in most cases are stored in tabular data formats such as CSV, is central to what DataCite is doing.