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A transparent record of life after publication

Crossref Event Data and the importance of understanding what lies beneath the data. Some things in life are better left a mystery. There is an argument for opaqueness when the act of full disclosure only limits your level of enjoyment: in my case, I need a complete lack of transparency to enjoy both chicken nuggets and David Lynch films. And that works for me. But metrics are not nuggets. Because in order to consume them, you really need to know how they’re made.

Publishers, help us capture Events for your content

The day I received my learner driver permit, I remember being handed three things: a plastic thermosealed reminder that age sixteen was not a good look on me; a yellow L-plate sign as flimsy as my driving ability; and a weighty ‘how to drive’ guide listing all the things that I absolutely must not, under any circumstances, even-if-it-seems-like-a-really-swell-idea-at-the-time, never, ever do.

Event Data as Underlying Altmetrics Infrastructure at the 4:AM Altmetrics Conference

Joe Wass

Joe Wass – 2017 September 25

In Event DataAltmetricsBibliometrics

I’m here in Toronto and looking forward to a busy week. Maddy Watson and I are in town for the 4:AM Altmetrics Conference, as well as the altmetrics17 workshop and Hack-day. I’ll be speaking at each, and for those of you who aren’t able to make it, I’ve combined both presentations into a handy blog post, which follows on from my last one. But first, nothing beats a good demo.

You do want to see how it’s made — seeing what goes into altmetrics

There’s a saying about oil, something along the lines of “you really don’t want to see how it’s made”. And whilst I’m reluctant to draw too many parallels between the petrochemical industry and scholarly publishing, there are some interesting comparisons to be drawn. Oil starts its life deep underground as an amorphous sticky substance. Prospectors must identify oil fields, drill, extract the oil and refine it. It finds its way into things as diverse as aspirin, paint and hammocks.

Event Data enters Beta

We’ve been talking about it at events, blogging about it on our site, living it, breathing it, and even sometimes dreaming about it, and now we are delighted to announce that Crossref Event Data has entered Beta.

URLs and DOIs: a complicated relationship

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 the Crossref Metadata API. Part 2 (with PaperHive)

We first met the team from PaperHive at SSP in June, pointed them in the direction of the Crossref Metadata API and let things progress from there. That’s the nice thing about having an API - because it’s a common and easy way for developers to access and use metadata, it makes it possible to use with lots of diverse systems and services.

So how are things going? Alexander Naydenov, PaperHive’s Co-founder gives us an update on how they’re working with the Crossref metadata:

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

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

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?

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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