Latest blog posts
Martyn Rittman
2021 June 11

Event Data: Help us fill in the gaps

To date, we have collected around 740 million events from 12 different source since we launched our Event Data service service in 2017. Each event is an online mention of the research associated with a DOI, either via the DOI directly or using the associated URL. However, we know that there is much more out there. Because of this, we would like to explore where we could expand. We invite proposals to conduct a gap analysis for Event Data sources, looking at what we currently collect and seeing what more could be added.

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Martyn Rittman
2021 June 09

An Advisory Group for Preprints

We are delighted to announce the formation of a new Advisory Group to support us in improving preprint metadata. Preprints have grown in popularity over the last few years, with increasing focus brought by the need to rapidly disseminate knowledge in the midst of a global pandemic. We have supported metadata deposits for preprints under the content type ‘posted content’ since 2016, and members currently register a total of around 17,000 new preprints metadata records each month.

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Geoffrey Bilder
2021 June 07

Time to put the "R" back in "R&D"

It is time to put the ‘R’ back into R&D. The Crossref R&D team was originally created to focus on the kinds of research projects that have allowed Crossref to make transformational technology changes, launch innovative new services, and engage with entirely new constituencies. Some Illustrious projects that had their origins in the R&D group include: DOI Content Negotiation Similarity Check (originally CrossCheck) ORCID (originally Author DOIs) Crossmark The Open Funder Registry The Crossref REST API Linked Clinical Trials Event Data Grant registration ROR And for each project that has graduated, there have been several that have not.

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Ginny Hendricks
2021 June 03

The road ahead: our strategy through 2025

This announcement has been in the works for some time, but everything seems to take longer when there is a pandemic going on, including finding time and headspace to plan out our strategy for the next few years. Over the last year or so we have had our heads down addressing how to scale our 20-yr-old system and operation – and adapting to new ways of working. But we’ve also spent time talking to people, forging alliances, looking ahead, and making plans.

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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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Event Data: Help us fill in the gaps

2021 June 11

An Advisory Group for Preprints

2021 June 09

Time to put the "R" back in "R&D"

2021 June 07

The road ahead: our strategy through 2025

2021 June 03

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