Dominika Tkaczyk – 2019 July 08
Last year I spent several weeks studying how to automatically match unstructured references to DOIs (you can read about these experiments in my previous blog posts). But what about references that are not in the form of an unstructured string, but rather a structured collection of metadata fields? Are we matching them, and how? Let’s find out.
Isaac Farley – 2019 April 30
The Simple Text Query form (STQ) allows users to retrieve existing DOIs for journal articles, books, and chapters by cutting and pasting a reference or reference list into a simple query box. For years the service has been heavily used by students, editors, researchers, and publishers eager to match and link references.
We had changes to the service planned for the first half of this year - an upgraded reference matching algorithm, a more modern interface, etc. In the spirit of openness and transparency, part of our project plan was to communicate these pending changes to STQ users well in advance of our 30 April completion date. What would users think? Could they help us improve upon our plans?
Dominika Tkaczyk – 2018 December 18
In my previous blog post, Matchmaker, matchmaker, make me a match, I compared four approaches for reference matching. The comparison was done using a dataset composed of automatically-generated reference strings. Now it’s time for the matching algorithms to face the real enemy: the unstructured reference strings deposited with Crossref by some members. Are the matching algorithms ready for this challenge? Which algorithm will prove worthy of becoming the guardian of the mighty citation network? Buckle up and enjoy our second matching battle!
Dominika Tkaczyk – 2018 November 12
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?
Dominika Tkaczyk – 2018 November 09
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?
Anna Tolwinska – 2018 May 30
Ed Pentz – 2017 March 15
We have updated our DOI display guidelines as of March 2017, this month! I described the what and the why in my previous blog post New Crossref DOI display guidelines are on the way and in an email I wrote to all our members in September 2016. I’m pleased to say that the updated Crossref DOI display guidelines are available via this fantastic new website and are now active. Here is the URL of the full set of guidelines in case you want to bookmark it (https://0-www-crossref-org.libus.csd.mu.edu/display-guidelines/) and a shareable image to spread the word on social media.
Rachael Lammey – 2016 December 05
We began accepting preprints as a new content type last month (in a category known as “posted content” in our XML schema). Over 1,000 records have already been registered in the first few weeks since we launched the service.
By extending our existing services to preprints, we want to help make sure that:
Ed Pentz – 2016 September 27
Crossref will be updating its DOI Display Guidelines within the next couple of weeks. This is a big deal. We last made a change in 2011 so it’s not something that happens often or that we take lightly. In short, the changes are to drop “dx” from DOI links and to use “https:” rather than “http:”. An example of the new best practice in displaying a Crossref DOI link is: https://0-doi-org.libus.csd.mu.edu/10.1629/22161
Kirsty Meddings – 2016 June 21
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