Last week Jennifer Lin shared information on the Making Data Count (MDC) project on this blog. MDC is a project funded by the U.S. National Science Foundation (NSF) to design and develop metrics that track and measure data use – data-level metrics (DLM). Funding for the 12 month project ends October 1st, with a no-cost extension until March 1st.

CSV (comma-separated values) is a popular file format for data. It is popular because it is very simple: CSV is text-based and any application that can open text files can read or write CSV. This makes it a good fit for digital preservation. We don't know how many of the datasets in DataCite use CSV because the format metadata attribute is not used much (this query gives you some examples), but we know that the number is big.

In the first post of this new blog a few weeks ago I talked about Data-Driven Development, and that service monitoring is an important aspect of this. The main service DataCite is providing is registration of digital object identifiers (DOIs) for scholarly content, in particular research data. Monitoring this service should include the following:number of DOIs registeredmetadata associated with these DOIsare the DOIs working as expected, e.g.

Today I am pleased to announce the launch of a new service, DataCite Labs Search – the service is available immediately at https://search.datacite.org/. This is one of THOR’s first services and is based on work in the earlier EC-funded ODIN Project. The ODIN project launched the DataCite/ORCID claiming tool in June 2013. The DataCite/ORCID claiming tool allows users to add works from the DataCite Metadata Store (MDS) to their ORCID profile.

Today DataCite received an email from a user alerting us that there are some small inconsistencies with our recommended data citation format:Creator (PublicationYear): Title. Publisher. Identifier at https://www.datacite.org/services/cite-your-data.htmlCreator; (PublicationYear): Title; Publisher.

This week I start as the new DataCite Technical Director. While I get up to speed with existing DataCite services and infrastructure, and we start to launch new services (e.g. this blog), this is also a good time to communicate the overall approach I am taking.

Starting next week I will work as the DataCite Technical Director, and I am excited about this new opportunity. But this is material for another post, here I want to reflect on the last three years working as Technical Lead for the PLOS Article-Level Metrics project.

Four years ago I wrote a blog post about component DOIs. It is time to revisit the topic, in particular since our approach to citing data associated with a publication has changed since 2011. Component DOIs are explained in the CrossRef Help System: Component DOIs are DOIs, i.e. persistent identifiers that link directly to the resource in question, e.g. a figure in a publication.

At the SciFoo Camp this weekend Erin McKiernan and I moderated an unconference session on the topic Why should we work where we live? This was a spontaneous idea after we had talked about this topic on Friday (Erin lives in Mexico with a job in Canada, I live in Germany and work for an organization in San Francisco). We quickly realized that this situation is far from uncommon in the space we work in (science and science

Just like the rest of the internet, much of our scholarly infrastructure is built around the Hypertext Transfer Protocol (HTTP), increasingly HTTPS for security, and soon HTTP/2 for better performance. In this infrastructure Universal Resource Locators (URLs) are essential to locate resources (sic) such as scholarly articles, datasets, researchers, organizations, or grants.

Yesterday Julie McMurry and co-authors published a preprint 10 Simple rules for design, provision, and reuse of persistent identifiers for life science data . This is an important paper trying to address a fundamental problem: how can we make persistent identifiers both human-readable and machine-readable?