To address the growing scale and complexity of scholarly data, we’ve launched a new data science function at Crossref. In April, we were excited to welcome our first data scientists, Jason Portenoy and Alex Bédard-Vallée, to the team. With their arrival, the Data Science team is now fully up and running. In this blog post, we’re sharing our vision and what’s ahead for data science at Crossref.

New US National Academy of Sciences Report reveals the complex web of societal vulnerabilities that could amplify nuclear war’s devastating impact TLDR/Summary The US National Academy of Sciences has just released a comprehensive report on the “Environmental Effects of Nuclear War”. This work extends analysis beyond physical damage to examine impacts on human social and economic systems.

A recent report by the Dutch RIVM, PFAS in the blood of the Dutch population (doi:10.21945/RIVM-2025-0094), writes that seven PFAS compounds are found in blood samples of all tested people. Another nine compounds are found in at least 1-in-10 people. Because there is relevant data in the report on the 28 studied PFAS compound, I wanted to have the report more FAIR than it is on the website. Why this report?

When I read Andrej Karpathy’s endorsement of “context engineering” in a Twitter exchange with Shopify’s Tobi Lutke, I felt he tapped into something we all felt to some degree: tweet={"url":"https:\/\/twitter.com\/karpathy\/status\/1937902205765607626","author_name":"Andrej Karpathy","author_url":"https:\/\/twitter.com\/karpathy","html":"\u003Cblockquote class=\"twitter-tweet\" align=\"center\"\u003E\u003Cp lang=\"en\" dir=\"ltr\"\u003E+1 for

I missed this paper (Yuan et al. 2024) when it came out last year, but my friend and colleague Jeremiah Scott brought it to my attention. The bit on nuchal sesamoids in shrews is so good and so weird that I’m just going to copy and paste it in its entirety.

I’ve long been a proponent of making quantitative research reproducible. It’s the main reason I do all my scientific writing in Quarto—I can mix code and text in the same document so I don’t need to copy/paste numbers, tables, and figures from some statistical program into a word processor. Everything automatically ends up one compiled document based on the most current data.

(This was buried in Part 5 of my 2011 review of the Sideshow Apatosaurus maquette, but it’s long deserved to be a post of its own, and now it is. I’m not adding anything new here, just extracting and reposting the relevant bits, for reasons that will become clear in a future post.

My blog focuses on the two primary ways "AI"—or more accurately, transformer-based models—are impacting academic search.

For the Bremen Research Data Day, our WiNoDa colleagues from gfBio had registered us quite early for the “FAIRplay Station”. Like last year, they wanted to participate with the game “Data Detectives”, in which various objects had to be identified using metadata such as date, location, etc. The Museum of Natural History had kindly provided us with some fossils/plaster casts that were described by up to five clues.

Für den Bremer Tag der Forschungsdaten hatten die WiNoDa-Kolleginnen von gfBio uns schon recht früh für die „FAIRplay Station“ angemeldet. Wie schon im letzten Jahr wollten sie mit dem Spiel „Data Detectives“ antreten, bei dem verschiedene Objekte mittels Hinweisen auf Metadaten wie Datierung, Fundort etc. identifiziert werden müssen.

Are meta-scientists ignoring philosophy of science (PoS)? Are they re-inventing the wheel? A recent panel at the Metascience conference engaged with this question, and the first sentence of the abstract states “Critics argue that metascience merely reinvents the wheel of other academic fields.” It’s a topic I have been thinking about for a while, so I will share my thoughts on this question.