Latest blog posts
Lucy Ofiesh
2020 May 21

Calling all prospective board members

The Crossref Nominating Committee is inviting expressions of interest to join the Board of Directors of Crossref for the term starting in 2021. The committee will gather responses from those interested and create the slate of candidates that our membership will vote on in an election in September. Expressions of interest will be due Friday, June 19, 2020. The role of the board at Crossref is to provide strategic and financial oversight of the organization, as well as guidance to the Executive Director and the staff leadership team, with the key responsibilities being:

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Laura J Wilkinson
2020 April 29

Come for a swim in our new pool of Education materials

After 20 years in operation, and as our system matures from experimental to foundational infrastructure, it’s time to review our documentation. Having a solid core of education materials about the why and the how of Crossref is essential in making participation possible, easy, and equitable. As our system has evolved, our membership has grown and diversified, and so have our tools - both for depositing metadata with Crossref, and for retrieving and making use of it.

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Jennifer Kemp
2020 April 29

Crossing the Rubicon - The case for making chapters visible

To help better support the discovery, sale and analysis of books, Jennifer Kemp from Crossref and Mike Taylor from Digital Science, present seven reasons why publishers should collect chapter-level metadata. Book publishers should have been in the best possible position to take advantage of the movement of scholarly publishing to the internet. After all, they have behind them an extraordinary legacy of creating and distributing data about books: the metadata that supports discovery, sales and analysis.

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Paul Davis
2020 April 27

Memoirs of a DOI detective...it’s error-mentary dear members

Hello, I’m Paul Davis and I’ve been part of the Crossref support team since May 2017. In that time I’ve become more adept as a DOI detective, helping our members work out whodunnit when it comes to submission errors.

If you have ever received one of our error messages after you have submitted metadata to us, you may know that some are helpful and others are, well, difficult to decode. I’m here to help you to become your own DOI detective.

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Double trouble with DOIs

Dominika Tkaczyk

Dominika Tkaczyk – 2020 March 10

In Crossref LabsMetadataMetadata Quality

Detective Matcher stopped abruptly behind the corner of a short building, praying that his loud heartbeat doesn’t give up his presence. This missing DOI case was unlike any other before, keeping him awake for many seconds already. It took a great effort and a good amount of help from his clever assistant Fuzzy Comparison to make sense of the sparse clues provided by Miss Unstructured Reference, an elegant young lady with a shy smile, who begged him to take up this case at any cost.

What’s your (citations’) style?

Dominika Tkaczyk

Dominika Tkaczyk – 2019 October 29

In CitationCrossref LabsMachine Learning

Bibliographic references in scientific papers are the end result of a process typically composed of: finding the right document to cite, obtaining its metadata, and formatting the metadata using a specific citation style. This end result, however, does not preserve the information about the citation style used to generate it. Can the citation style be somehow guessed from the reference string only? TL;DR I built an automatic citation style classifier.

What if I told you that bibliographic references can be structured?

Dominika Tkaczyk

Dominika Tkaczyk – 2019 July 08

In LinkingCitationCrossref LabsReference Matching

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.

Reference matching: for real this time

Dominika Tkaczyk

Dominika Tkaczyk – 2018 December 18

In LinkingCitationCrossref LabsReference Matching

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!

Matchmaker, matchmaker, make me a match

Dominika Tkaczyk

Dominika Tkaczyk – 2018 November 12

In LinkingCitationCrossref LabsReference Matching

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?

What does the sample say?

Dominika Tkaczyk

Dominika Tkaczyk – 2018 November 09

In LinkingCitationCrossref LabsReference Matching

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?

URLs and DOIs: a complicated relationship

Joe Wass

Joe Wass – 2016 November 04

In Content RegistrationCrossref LabsEvent DataIdentifiersPersistence

As the linking hub for scholarly content, it’s our job to tame URLs and put in their place something better. Why? Most URLs suffer from link rot and can be created, deleted or changed at any time. And that’s a problem if you’re trying to cite them.

Using AWS S3 as a large key-value store for Chronograph

Joe Wass

Joe Wass – 2016 August 02

In Crossref LabsDOIsEvent DataProgrammingWikipedia

One of the cool things about working in Crossref Labs is that interesting experiments come up from time to time. One experiment, entitled “what happens if you plot DOI referral domains on a chart?” turned into the Chronograph project. In case you missed it, Chronograph analyses our DOI resolution logs and shows how many times each DOI link was resolved per month, and also how many times a given domain referred traffic to DOI links per day.

HTTPS and Wikipedia

Joe Wass

Joe Wass – 2016 May 31

In Crossref LabsDataDOIsEvent DataWikipedia

This is a joint blog post with Dario Taraborelli, coming from WikiCite 2016.

In 2014 we were taking our first steps along the path that would lead us to Crossref Event Data. At this time I started looking into the DOI resolution logs to see if we could get any interesting information out of them. This project, which became Chronograph, showed which domains were driving traffic to Crossref DOIs.

You can read about the latest results from this analysis in the “Where do DOI Clicks Come From” blog post.

Having this data tells us, amongst other things:

  • where people are using DOIs in unexpected places
  • where people are using DOIs in unexpected ways
  • where we knew people were using DOIs but the links are more popular than we realised

Where do DOI clicks come from?

Joe Wass

Joe Wass – 2016 May 19

In Crossref LabsDOIsPersistenceIdentifiersEvent DataLinkingWikipedia

As part of our Event Data work we’ve been investigating where DOI resolutions come from. A resolution could be someone clicking a DOI hyperlink, or a search engine spider gathering data or a publisher’s system performing its duties. Our server logs tell us every time a DOI was resolved and, if it was by someone using a web browser, which website they were on when they clicked the DOI. This is called a referral.
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Calling all prospective board members

2020 May 21

Come for a swim in our new pool of Education materials

2020 April 29

Crossing the Rubicon - The case for making chapters visible

2020 April 29

Memoirs of a DOI detective...it’s error-mentary dear members

2020 April 27

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