We’ve mentioned why data citation is important to the research community. Now it’s time to roll up our sleeves and get into the ‘how’. This part is important, as citing data in a standard way helps those citations be recognised, tracked, and used in a host of different services.
Matching (or resolving) bibliographic references to target records in the collection is a crucial algorithm in the Crossref ecosystem. Automatic reference matching lets us discover citation relations in large document collections, calculate citation counts, H-indexes, impact factors, etc. At Crossref, we currently use a matching approach based on reference string parsing. Some time ago we realized there is a much simpler approach. And now it is finally battle time: which of the two approaches is better?
At Crossref Labs, we often come across interesting research questions and try to answer them by analyzing our data. Depending on the nature of the experiment, processing over 100M records might be time-consuming or even impossible. In those dark moments we turn to sampling and statistical tools. But what can we infer from only a sample of the data?
A couple of weeks ago we shared with you that data citation is here, and that you can start doing data citation today. But why would you want to? There are always so many priorities, why should this be at the top of the list?
Our LIVE Annual Meeting is back in North America for the first time since 2015, and with just 10 days to go, there’s a lot going on in preparation. As you’d expect with a How good is your metadata? theme—the two-days will be entirely devoted to the subject of metadata—because it touches everything we do, and everything that publishers, hosting platforms, funders, researchers, and librarians do. Oh, and it’s actually super awesome too—and occasionally fun.
Best practices seem to be having a moment. In the ten years since the Books Advisory Group first created a best practice guide for books, the community beyond Crossref has developed or updated at least 17 best practice resources, as collected here by the Metadata 2020 initiative. (Full disclosure: I co-chair its Best Practices group.)
Over 100 Million unique scholarly works are distributed into systems across the research enterprise 24/7 via our APIs at a rate of around 633 Million queries a month. Crossref is broadcasting descriptions of these works (metadata) to all corners of the digital universe.
As part of our blog series highlighting some of the tools and services that use our API, we asked Michael Parkin—Data Scientist at the European Bioinformatics Institute—a few questions about how Europe PMC uses our metadata where preprints are concerned.
2019 August 16
We'll be rocking your world again at PIDapalooza 2020
2019 August 16
LIVE19, the strategy one: have your say
2019 August 11
Funders and infrastructure: let’s get building
2019 July 29
