![\"\"](\"https://i.ibb.co/7dy89Wy4/Roden-Stute-Bild.jpg\")
Wie gelingt es, Wissen in hochspezialisierten Organisationen langfristig zu sichern und zugleich im Alltag nutzbar zu machen? Mit dieser Frage besch\u00e4ftigte sich ein Praxisprojekt im Masterstudiengang Bibliotheks- und Informationswissenschaft (MALIS) an der TH K\u00f6ln. Im Fokus standen die Organisationshandb\u00fccher (OrgHandb\u00fccher) der Spezialbibliotheken der Bundeswehr \u2013 ein traditionell etabliertes, in der Praxis jedoch zunehmend vernachl\u00e4ssigtes Instrument.
\n\n
Ausgangslage: Ein Werkzeug verliert an Relevanz
\nSeit Mitte der 1990er-Jahre sind OrgHandb\u00fccher f\u00fcr alle Spezialbibliotheken der Bundeswehr verpflichtend. Sie sollen Prozesse dokumentieren, Zust\u00e4ndigkeiten kl\u00e4ren und Erfahrungswissen sichern. Doch viele Handb\u00fccher waren seit Jahren nicht mehr aktualisiert, der Zugriff gestaltete sich schwierig und kollaboratives Arbeiten war nicht vorgesehen.
Stattdessen wichen Bibliotheken auf eigene L\u00f6sungen wie SharePoint oder Wikis aus. Das Ergebnis: eine fragmentierte Wissenslandschaft \u2013 mit dem Risiko, dass wertvolles Erfahrungswissen durch Personalwechsel verloren geht.
\nMethodisches Vorgehen: Datenbasis schaffen
\nUm die tats\u00e4chliche Nutzung der OrgHandb\u00fccher zu erfassen, setzte das Projekt auf einen Methodenmix:
Die R\u00fccklaufquote lag bei \u00fcber 70 % \u2013 ein starkes Signal f\u00fcr das Interesse am Thema. Die Ergebnisse waren jedoch ern\u00fcchternd: Zwei Drittel der Befragten nutzten das OrgHandbuch \u00fcberhaupt nicht. Gr\u00fcnde waren fehlende Einweisung, veraltete Inhalte und eine un\u00fcbersichtliche Struktur. Wenn es genutzt wurde, diente es vor allem als Leitfaden oder beim Onboarding neuer Kolleginnen und Kollegen.
\nL\u00f6sung: Ein digitales OrgHandbuch in Confluence
\nAuf Basis dieser Erkenntnisse entwickelte das Projekt ein exemplarisches OrgHandbuch in Confluence, der Wiki-Plattform der Bundeswehr.
Die wichtigsten Merkmale:
\nDamit wird das OrgHandbuch von einem statischen Dokument zu einem lebendigen, kollaborativen Wissensinstrument weiterentwickelt.
\nAusblick: Verstetigung als Schl\u00fcssel
\nDie technische Umsetzung war ein erster Schritt \u2013 entscheidend wird die kontinuierliche Pflege und Integration in den Arbeitsalltag. Nur so kann das OrgHandbuch langfristig Akzeptanz finden.
Dar\u00fcber hinaus zeigt das Projekt: Moderne Wissensmanagement-Ans\u00e4tze lassen sich auch in hochstrukturierten Organisationen wie der Bundeswehr erfolgreich einf\u00fchren. Die \u00dcbertragung auf andere Institutionen liegt nahe \u2013 \u00fcberall dort, wo Wissen nicht an Personen gebunden bleiben darf, sondern institutionell gesichert werden muss.
\nFazit
\nDas MALIS-Praxisprojekt verbindet wissenschaftliche Analyse mit praxisnaher Umsetzung und zeigt:
\u00a0
\nProjektzeitraum: Februar 2025 \u2013 August 2025
\nProjektbetreuer*in: Prof. Dr. Simone F\u00fchles-Ubach
Dieser Artikel steht unter der Lizenz CC BY.
","doi":"https://doi.org/10.59350/q5sft-0wj68","funding_references":null,"guid":"https://malisprojekte.web.th-koeln.de/wordpress/?p=2470","id":"b926da11-7cc0-4f9e-b2e4-b80949af0e28","image":"https://i.ibb.co/7dy89Wy4/Roden-Stute-Bild.jpg","images":[{"height":"1536","src":"https://i.ibb.co/7dy89Wy4/Roden-Stute-Bild.jpg","width":"1024"},{"alt":"Abbildung 1: Titelbild (Quelle: ChatGPT, Version vom 10. August 2025, OpenAI, erstellt von Bettina Roden, chatgpt.com)","src":"https://i.ibb.co/7dy89Wy4/Roden-Stute-Bild.jpg"}],"indexed":true,"indexed_at":1778866903,"language":"de","parent_doi":null,"published_at":1778864707,"reference":[],"registered_at":0,"relationships":[],"rid":"rfxry-0cp34","status":"active","summary":"\n Wie gelingt es, Wissen in hochspezialisierten Organisationen langfristig zu sichern und zugleich im Alltag nutzbar zu machen? Mit dieser Frage besch\u00e4ftigte sich ein Praxisprojekt im Masterstudiengang Bibliotheks- und Informationswissenschaft (MALIS) an der TH K\u00f6ln.\n","tags":["Confluence","Digitale Transformation","Erfahrungswissen","Kollaboration","MALIS"],"title":"Wissensplattform statt Handbuch: Organisationshandb\u00fccher als lebendiges Wissensinstrument neu gedacht","updated_at":1778864707,"url":"https://malisprojekte.web.th-koeln.de/wordpress/wissensplattform-statt-handbuch-organisationshandbuecher-als-lebendiges-wissensinstrument-neu-gedacht/","version":"v1"}},{"document":{"abstract":null,"archive_url":null,"authors":[{"affiliation":[{"id":"https://ror.org/05167c961","name":"Western University of Health Sciences"}],"contributor_roles":[],"family":"Wedel","given":"Matt","url":"https://orcid.org/0000-0001-6082-3103"}],"blog":{"archive_collection":22153,"archive_host":null,"archive_prefix":"https://wayback.archive-it.org/22153/20231105213934/","archive_timestamps":null,"authors":[{"name":"Mike Taylor"}],"canonical_url":null,"category":"earthAndRelatedEnvironmentalSciences","community_id":"0e13541f-417e-46c0-a859-65927249df72","created_at":1675209600,"current_feed_url":null,"description":"SV-POW! ... All sauropod vertebrae, except when we're talking about Open Access. ISSN 3033-3695","doi":null,"doi_as_guid":false,"favicon":null,"feed_format":"application/atom+xml","feed_url":"https://svpow.com/feed/atom/","filter":null,"funding":null,"generator":"WordPress.com","generator_raw":"WordPress.com","home_page_url":"https://svpow.com","id":"c6cbbd2e-4675-4680-8a3f-784388009821","indexed":false,"issn":"3033-3695","language":"en","license":"https://creativecommons.org/licenses/by/4.0/legalcode","mastodon":null,"prefix":"10.59350","registered_at":1729882329,"relative_url":null,"ror":null,"secure":true,"slug":"svpow","status":"active","subfield":"1911","subfield_validated":true,"title":"Sauropod Vertebra Picture of the Week","updated_at":1778835620.071768,"use_api":true,"use_mastodon":false,"user_id":"04d03585-c8bb-40f2-9619-5076a5e0aed2"},"blog_name":"Sauropod Vertebra Picture of the Week","blog_slug":"svpow","content_html":"![\"\"](\"https://svpow.wordpress.com/wp-content/uploads/2026/05/bizarre-headgear-1-juvenile-utahceratops.jpg\")
An imposing view of a juvenile Utahceratops.
As threatened, I was in Oklahoma at the tail end of last week and over the weekend, mostly to give talks. My Friday evening public lecture was on horned dinosaurs, and it was tied in with the launch of a temporary exhibit called “Bizarre Headgear: Ceratopsians and the Evolution of Extraordinary Skulls”. I’ll cover the talks in another post; this one is about that exhibit.
\n![\"\"](\"https://svpow.wordpress.com/wp-content/uploads/2026/05/bizarre-headgear-2-pterosaurs-and-pigs.jpg\")
From the museum’s central atrium, there are a couple of passages into the special exhibition gallery that houses “Bizarre Headgear”. My preferred way in is the second doorway, farther from the front of the museum, which puts you face-to-face with pterosaurs and hell pigs. This sets up the basic division of the room: mostly Mesozoic and mostly dinos to the left, mostly Cenozoic and mostly mammals to the right (with a few exceptions, like the Synthetoceras visible on the back wall).
\n![\"\"](\"https://svpow.wordpress.com/wp-content/uploads/2026/05/bizarre-headgear-3-ceratopsians-and-other-dinos.jpg\")
From there, turn left and you’ll see horned dinosaurs and many other interesting critters. A lot of them.
\n![\"\"](\"https://svpow.wordpress.com/wp-content/uploads/2026/05/bizarre-headgear-4-extant-animals.jpg\")
Turn right and you’ll see a lot more non-dinosaurs, mostly extinct and extant mammals with a smattering of non-mammals.
\n![\"\"](\"https://svpow.wordpress.com/wp-content/uploads/2026/05/bizarre-headgear-5-psittacosaurus.jpg\")
I was there to yap about horned dinos, and the exhibit does not slack in this department, starting with this charming side-by-side skeletal reconstruction and lift restoration of Psittacosaurus. The sculpture is by Shane Foulkes, and it looks like a real animal.
\n![\"\"](\"https://svpow.wordpress.com/wp-content/uploads/2026/05/bizarre-headgear-6-archaeoceratops-and-friends.jpg\")
A highlight of the exhibit for me is this case of early ceratopsians. From right to left (far to near in this photo) are cast skulls of Liaoceratops, Auroraceratops, Archaeoceratops, and Protoceratops. These are little Aquilops-alikes from Asia. Back in 2014, Farke et al. got this topology:
\nPsittacosaurus (Liaoceratops (Aquilops (Auroraceratops (Archaeoceratops + all more derived ceratopsians))))
\nand in 2024, Tanaka recovered these relationships for those same taxa (I’m dropping many others here):
\nPsittacosaurus (Liaoceratops (Archaeoceratops ((Aquilops + Auroraceratops) + (all more derived ceratopsians))))
\nI’d never seen so many of these adorable little weirdos in one place. Heck, I’d never even seen casts of Liaoceratops and Auroraceratops in person. So it was nice to get acquainted with the aunts and cousins of Aquilops.
\n![\"\"](\"https://svpow.wordpress.com/wp-content/uploads/2026/05/bizarre-headgear-7-ceratopsian-row.jpg\")
The ceratopsian show continues with a pair of Protoceratops skeletons, followed by skulls of Zuniceratops, Diabloceratops, Kosmoceratops, and a cool Utahceratops with some soft tissue reconstructed. There’s also a mounted skeleton of Torosaurus, and the juvenile Utahceratops shown at the top of the post. This diversity of critters from across the ceratopsian tree was clutch when I helped lead a student tour on Monday. And it was nice to see a lot of animals that weren’t described when I was growing up, and that the average museum-goer might be less familiar with — Diabloceratops instead of Centrosaurus or Styracosaurus, Kosmoceratops and Utahceratops in place of Triceratops and Chasmosaurus.
\n![\"\"](\"https://svpow.wordpress.com/wp-content/uploads/2026/05/bizarre-headgear-8-pachyrhinosaurus-painting-and-sculpture.jpg\")
The exhibit has a lot more than just skulls and skeletons. There are loads of sculptures, both life-sized fleshed-out heads and miniatures showing the whole animal, like this Pachyrhinosaurus. And lots of wall art. I believe all of the sculptures are by Shane Foulkes (and apologies if I missed anyone else). Most of the paintings are by Andrey Atuchin, but there is at least one Mark Hallett piece in the exhibit: Synthetoceras being menaced by an amphicyonid ‘bear-dog’.
\n![\"\"](\"https://svpow.wordpress.com/wp-content/uploads/2026/05/bizarre-headgear-10-bovid-skulls.jpg\")
The mostly-mammals, mostly-extant side of the exhibit is equally impressive. I’m including fewer photos from that side, because this is already a long post, but I counted at least 65 skulls of non-dinosaurs, including 3 proboscideans and 5 cetaceans. Invertebrates even get a look in, with some of the more baroquely-horned beetles. I nipped into the exhibit while it was still being set up to get some photos for my talk, like this awesome array of African bovids. All of these non-ceratopsians are there to put the evolution of bizarre headgear in dinosaurs into context, and to show that dinos were not incomprehensible monsters, but animals whose anatomy and ecology we can understand, or at least make pretty good inferences about. The signage is uniformly excellent — discreet, informative, and attractively laid out, with a consistent arrangement and color palette.
\nAs long as we’re keeping score, I counted 5 mounted dinosaur skeletons, and 16 other dinosaur skulls. This exhibit is stacked. Every single person I talked to about it, including other paleontologists, staff, security guards, and museum visitors, volunteered something along the lines of “Holy cow, that is a lot of amazing stuff.” The sheer density and diversity of material on display has a qualitative impact, which gave me the feeling of walking through a cabinet of curiosities the size of a basketball court. I think it’s the most impressive temporary exhibit I’ve ever seen, and by far my favorite.
\n![\"\"](\"https://svpow.wordpress.com/wp-content/uploads/2026/05/bizarre-headgear-9-hammerhead-shark-skull.jpg\")
Here’s another thing I’d never seen in person: a cast skull of a hammerhead shark. Just incredible. As the artist and author Ricardo Delgado, creator of the Age of Reptiles comics, often says, “Nature is the best creature designer.”
\n![\"\"](\"https://svpow.wordpress.com/wp-content/uploads/2026/05/bizarre-headgear-11-rob-gaston.jpg\")
The “Bizarre Headgear” exhibit is the brainchild of Rob Gaston, shown here with some bespectacled doofus for scale. Rob and the crew at Gaston Design do great work — I’ve got a couple of their casts right here in my home office as I type. Because I got to go behind the scenes while they were setting up, I got to say hi to Rob and congratulate him on such a fantastic exhibit. If you’re within striking distance of Norman, Oklahoma, between now and late August, go see it. It’s included with the extremely reasonable museum admission (max $12 for non-senior adults, even less expensive for everyone else), and hey, you get to see the whole rest of the museum, too. See the museum website for details.
\n![\"\"](\"https://svpow.wordpress.com/wp-content/uploads/2026/05/bizarre-headgear-12.jpg\")
Parting shot: some utter genius in the museum gift shop got into the spirit of things by putting a Triceratops mask on this stuffed polar bear. I love this unreasonably and it’s only because of carry-on luggage limitations that I didn’t bring it home with me. Maybe you will succeed where I fell short.
\nI’ll have more to say about my trip in another post (Sauroposeidon!), so here I’ll just say a quick thanks to the museum director, Dr. Janet Braun, for the kind invitation to come speak; to Assistant Director Laura Moon and all the staff for making my visit successful and enjoyable; and to vert paleo curator Dr. Jacqueline Lungmus and the VP staff and volunteers for letting me come play in their sandbox. It was a heck of a trip, and you’ll be able to read more about it real soon.
\n\n
![\"\"](\"https://i.ibb.co/xSjZNkvC/Mueller-Bild1.jpg\")
Was bedeutet es, eine historische Sammlung zu erschlie\u00dfen? Was macht man da? Diese Fragen waren eine Leitlinie im Rahmen meines MALIS-Projekts und um sie zu beantworten, wurde die historische Sammlung von Georg Andreas und Gerlinde Bachem gew\u00e4hlt, die seit 2012 in der USB K\u00f6ln auf ihre Erschlie\u00dfung wartet.
\n\n
Die Sammlung Bachem ist ungew\u00f6hnlich, denn: Es gibt keinen inhaltlichen Zusammenhang! Herr Bachem verfolgte beim Sammeln zwei Ziele: Erstens seltene und besondere B\u00fccher zu erwerben, zweitens aus jedem Jahr seit Beginn des Buchdrucks mindestens ein Exemplar zu besitzen. Das bedeutet, es geht um kulturhistorisch wertvolle, teils einzigartige Werke.
\nWie geht man also vor, wenn eine Erschlie\u00dfung ansteht? Zun\u00e4chst muss das Vorgehen geplant werden. Im Rahmen des Projekts wurde entschieden, dass der Fokus auf den Kleinformaten (unter 30cm) liegen soll, da dies zeitlich als realistisch angesehen werden konnte. Es folgten Entscheidungen \u00fcber die zuk\u00fcnftige Aufstellung und das Signaturensystem. Dann ging die konkrete Arbeit los!
\nKatalogisierung:
\nHistorische Drucke sind anspruchsvoll zu katalogisieren, sie besitzen Eigenheiten, die moderne Drucke nicht kennen. Da sind z.B. typographische Besonderheiten wie Ligaturen, Virgel, Abbreviaturen oder alte lateinische Abk\u00fcrzungen. Dann ist die Unterscheidung von verschiedenen Ausgaben teils schwierig, ebenso wie die Datenlage im Verbundkatalog. Des Weiteren sind zwar Kenntnisse im Regelwerk RDA notwendig, aber vor allem auch noch RAK-WB und es ist notwendig, sich mit der Erfassungsgeschichte und den Eigenheiten der Verbundkatalogisierung zu besch\u00e4ftigen. Die Katalogisierung eines historischen Drucks kann zwischen 15 Minuten und 3 Stunden dauern, das h\u00e4ngt von der Komplexit\u00e4t des Buchs ab. Insgesamt konnten 314 Werke katalogisiert werden!
Provenienzverzeichnung:
\nProvenienz bedeutet \u201eHerkunft\u201c, das hei\u00dft, es werden Vorbesitzer (Personen oder K\u00f6rperschaften) nachgewiesen, um die Geschichte des Buches nachzuweisen. Insgesamt konnten 179 Provenienzen erfasst werden, darunter au\u00dfergew\u00f6hnliche. So konnte ich beispielsweise einige B\u00fccher adligen oder k\u00f6niglichen Privatbibliotheken zuordnen: K\u00f6nigin Maria Theresia von Frankreich, K\u00f6nig Ernst August von Hannover, Liselotte von der Pfalz, Maria Theresia von \u00d6sterreich, K\u00f6nig Ludwig XIII. von Frankreich sowie K\u00f6nig Ludwig XV. von Frankreich
Technische und konservatorische Buchbearbeitung:
\nDie Reihenfolge ist: Reinigung, Stempelung, Signaturschilder kleben, Reparaturen durchf\u00fchren, ggf. Restaurierungsma\u00dfnahmen einleiten. Danach kann die Aufstellung im Magazin erfolgen und die Erschlie\u00dfung ist in der USB beendet.
Was ist geschafft?
\nDie Kleinformate wurden erfolgreich erschlossen, d.h. sie sind zug\u00e4nglich und national recherchierbar! Insgesamt demonstriert die Bearbeitung der Sammlung Bachems exemplarisch, wie gezielte Erschlie\u00dfung, Sichtbarmachung und konservatorische Ma\u00dfnahmen den Wert historischer Sammlungen f\u00fcr Forschung und \u00d6ffentlichkeit signifikant erh\u00f6hen k\u00f6nnen.
![\"\"](\"https://i.ibb.co/9MwWLPb/Mueller-Bild2.jpg\")
\u00a0
\nProjektzeitraum: April 2025 \u2013 August 2025
\nProjektbetreuer*in: Prof. Dr. Siegfried Schmidt
Dieser Artikel steht unter der Lizenz CC BY.
","doi":"https://doi.org/10.59350/76rg6-79w64","funding_references":null,"guid":"https://malisprojekte.web.th-koeln.de/wordpress/?p=2452","id":"f60f9107-e4f8-4a70-98b9-ec6176dd3df8","image":"https://i.ibb.co/xSjZNkvC/Mueller-Bild1.jpg","images":[{"height":"875","src":"https://i.ibb.co/xSjZNkvC/Mueller-Bild1.jpg","width":"1166"},{"height":"880","src":"https://i.ibb.co/9MwWLPb/Mueller-Bild2.jpg","width":"1173"},{"alt":"Abbildung 1: Titelbild (Quelle: Privat, Lucia Anna M\u00fcller)","src":"https://i.ibb.co/xSjZNkvC/Mueller-Bild1.jpg"},{"alt":"Abbildung 2 (Quelle: Privat, Lucia Anna M\u00fcller)","src":"https://i.ibb.co/9MwWLPb/Mueller-Bild2.jpg"}],"indexed":true,"indexed_at":1778864488,"language":"de","parent_doi":null,"published_at":1778862490,"reference":[],"registered_at":0,"relationships":[],"rid":"raz6q-tkj77","status":"active","summary":"\n Was bedeutet es, eine historische Sammlung zu erschlie\u00dfen? Was macht man da? Diese Fragen waren eine Leitlinie im Rahmen meines MALIS-Projekts und um sie zu beantworten, wurde die historische Sammlung von Georg Andreas und Gerlinde Bachem gew\u00e4hlt, die seit 2012 in der USB K\u00f6ln auf ihre Erschlie\u00dfung wartet.\n\nDie Sammlung Bachem ist ungew\u00f6hnlich, denn: Es gibt keinen inhaltlichen Zusammenhang!","tags":["Bibliophilie","Erschlie\u00dfung","Historische Drucke","Kulturgut","MALIS"],"title":"Erfassung und Erschlie\u00dfung einer historischen Privatsammlung am Beispiel der Sammlung Georg Andreas und Gerlinde Bachem in der USB K\u00f6ln","updated_at":1778862490,"url":"https://malisprojekte.web.th-koeln.de/wordpress/erfassung-und-erschliessung-einer-historischen-privatsammlung-am-beispiel-der-sammlung-georg-andreas-und-gerlinde-bachem-in-der-usb-koeln/","version":"v1"}},{"document":{"abstract":"On 8 May 2026, during the Graduation Ceremony of the Executive Masters in Management of Research Infrastructures (EMMRI), OpenCitations was awarded the Certificate of Excellence in Research Infrastructure Leadership.","archive_url":null,"authors":[{"affiliation":[{"id":"https://ror.org/01111rn36","name":"University of Bologna"}],"contributor_roles":[],"family":"Di Giambattista","given":"Chiara","url":"https://orcid.org/0000-0001-8665-095X"}],"blog":{"archive_collection":22125,"archive_host":null,"archive_prefix":"https://wayback.archive-it.org/22125/20231105110316/","archive_timestamps":[20231105110316,20240505181542,20241105110224,20250505110302],"authors":[{"name":"OpenCitations Team"}],"canonical_url":null,"category":"otherSocialSciences","community_id":"84fbaf60-5174-43f6-976e-5f0b6f1da9a1","created_at":1681862400,"current_feed_url":null,"description":"The blog of the OpenCitations Infrastructure","doi":null,"doi_as_guid":false,"favicon":"https://rogue-scholar.org/api/communities/c8efeda5-cd52-472d-9537-6915b9c62e34/logo","feed_format":"application/atom+xml","feed_url":"https://opencitations.hypotheses.org/feed/atom/","filter":null,"funding":null,"generator":"WordPress","generator_raw":"WordPress 6.6.2","home_page_url":"https://opencitations.hypotheses.org","id":"1e1a0f67-e922-4977-b5b8-c5ec19c2f43a","indexed":false,"issn":null,"language":"en","license":"https://creativecommons.org/licenses/by/4.0/legalcode","mastodon":"https://@scicomm.xyz/@opencitations","prefix":"10.59350","registered_at":1727299025,"relative_url":null,"ror":"https://ror.org/00wb4mk85","secure":true,"slug":"opencitations","status":"active","subfield":"1802","subfield_validated":null,"title":"OpenCitations blog","updated_at":1778835160.035895,"use_api":true,"use_mastodon":true,"user_id":"13119f55-bbed-46a9-9338-80103d8c6b05"},"blog_name":"OpenCitations blog","blog_slug":"opencitations","content_html":"On 8 May 2026, during the Graduation Ceremony of the Executive Masters in Management of Research Infrastructures (EMMRI), OpenCitations was awarded the Certificate of Excellence in Research Infrastructure Leadership. This recognition was achieved through the participation of members of the OpenCitations team in the 2024\u20132026 class of the Excellence Programme for Research Infrastructures, an initiative designed to support research infrastructures in developing organisational competencies across their teams, fostering sustainable and effective leadership models.
\nThe OpenCitations participants included Director Silvio Peroni, CTO Ivan Heibi, Research Manager Claudio Fabbri, Systems Administrator Mario Petrella, and Communications Director Chiara Di Giambattista, who took part in the 11 modules of the programme. Across these modules, OpenCitations built a network of relationships and exchanges with other selected research infrastructures and strengthened its competencies in the following areas:
\nThe graduation ceremony, the final step of this two-year journey, brought together faculty members and representatives from the research infrastructures. Among the reflections shared during the event, one phrase captured the spirit of the programme: \u201cLeadership is a form of enthusiasm\u201d. Indeed, this experience made it clear that such enthusiasm was widely shared among participants, including colleagues from different infrastructures worldwide. The exchange of perspectives promoted throughout each module of the programme fostered a more grounded and pragmatic understanding of how research infrastructures evolve and collaborate in an international environment.
\nWe would like to thank the EMMRI team, in particular the Director Professor Marialuisa Lavritrano, and Professor Enrico Guarini and Drs. Laura Farina, for selecting OpenCitations for this programme and for developing an initiative that is both well-structured and internationally relevant, hosted at the University of Milano-Bicocca.
\nAt the end of this programme, OpenCitations carries forward the responsibility to build on the stimulating discussions and insights gained throughout the course. We will work to further develop the competencies acquired and reflect on both the strengths and limitations identified through this exchange, to continue supporting the long-term sustainability and development of OpenCitations as an open scholarly infrastructure
\n","doi":"https://doi.org/10.59350/ds8e6-rt906","funding_references":null,"guid":"https://opencitations.hypotheses.org/?p=4334","id":"d9ccf763-4b0b-40e3-abc9-56a114b8d65f","image":"https://opencitations.hypotheses.org/files/2026/05/Scuola-media-1080-x-1350-px-1500-x-900-px-1500-x-900-px-1.png","images":[],"indexed":true,"indexed_at":1778874014,"language":"en","parent_doi":null,"published_at":1778840346,"reference":[],"registered_at":0,"relationships":[],"rid":"em2y4-b1n13","status":"active","summary":"On 8 May 2026, during the Graduation Ceremony of the Executive Masters in Management of Research Infrastructures (EMMRI), OpenCitations was awarded the Certificate of Excellence in Research Infrastructure Leadership.","tags":["Governance And Finances","Non Class\u00e9","Open Access","Open Scholarship","Open Science"],"title":"OpenCitations has been awarded the Certificate of Excellence in Research Infrastructure Leadership","updated_at":1778840346,"url":"https://opencitations.hypotheses.org/4334","version":"v1"}},{"document":{"abstract":null,"archive_url":null,"authors":[{"contributor_roles":[],"family":"Turner","given":"Stephen D."}],"blog":{"archive_collection":null,"archive_host":null,"archive_prefix":null,"archive_timestamps":null,"authors":[{"name":"Stephen Turner"}],"canonical_url":null,"category":"biologicalSciences","community_id":"382941a7-2ffa-41df-8bbb-5f772188517f","created_at":1734172613,"current_feed_url":null,"description":"A practicing data scientist's take on AI, genomics, biosecurity, and the ways AI is reshaping how science gets done. Weekly updates from the field. Occasional notes on programming.","doi":null,"doi_as_guid":false,"favicon":null,"feed_format":"application/rss+xml","feed_url":"https://blog.stephenturner.us/feed","filter":null,"funding":null,"generator":"Substack","generator_raw":"Substack","home_page_url":"https://blog.stephenturner.us/","id":"bffe125c-3dfa-4f25-998f-e62878677c7c","indexed":true,"issn":null,"language":"en","license":"https://creativecommons.org/licenses/by/4.0/legalcode","mastodon":"https://bsky.app/profile/stephenturner.us","prefix":"10.59350","registered_at":0,"relative_url":null,"ror":null,"secure":true,"slug":"stephenturner","status":"active","subfield":"1311","subfield_validated":true,"title":"Paired Ends","updated_at":1778835598.79035,"use_api":null,"use_mastodon":false,"user_id":"ae63ef98-7475-4cc1-b3eb-244d5e096f0f"},"blog_name":"Paired Ends","blog_slug":"stephenturner","content_html":"AI-heavy week, but the throughline is what happens when the platforms and infrastructure under our work start to rot, from GitHub to preprint servers to peer-reviewed literature.
The GitHub ship is sinking, the lifeboats leak
Vibe-coded into a corner
The Lancet sues the AI that cites The Lancet
Hallucinated citations, now with a denominator
arXiv takes the banhammer out for AI-written work
David Bushell wrote a vivid eulogy for GitHub (\u201cGitHub used to be cool and now it\u2019s a lame slop graveyard\u201d), and a few days later GitLab\u2019s new CEO Bill Staples published \u201cGitLab Act 2\u201d, which to me sounds like a flailing pivot toward agentic everything.
Bushell\u2019s case against GitHub is part vibes but contains an uptime chart that does look bad after the Microsoft acquisition.
When I posted this chart on Bluesky earlier this week, I had a few folks pointing to the deluge of AI coding agents and automated pull requests as the reason. But if you look closely at the chart, this service degradation long predated AI coding agents and ChatGPT itself.
![\"\"](\"https://substackcdn.com/image/fetch/$s_!6ew2!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fed1b0b11-6f3f-4159-b566-3c60cdedf5c5_1273x916.png\" "\\"\\"")
But: Git is not GitHub. He recommends Codeberg (running Forgejo) as the safe alternative, with self-hosted Forgejo as the power-user option. He also recommended GitLab, then added an edit:
oh dear, they\u2019ve contracted the rot
The Staples letter is what he means. GitLab is reorganizing into roughly 60 smaller R&D teams, flattening management, exiting up to 30% of its country footprint, and (oh my): \u201crewiring internal processes with AI agents, automating the reviews, approvals, and handoffs to speed us up.\u201d The strategic thesis is that \u201csoftware will be built by machines, directed by people.\u201d
The blog post calls git \u201cdesigned for human-rate commits\u201d and pitches a \u201cgenerational rebuild of the underlying infrastructure to handle agent-rate work as the default.\u201d
I\u2019m not an agent power user, and maybe I\u2019ll retract my thoughts on this in a few months. But, if your agents are opening so many merge requests that git itself is the bottleneck, the answer is probably fewer agents.
It\u2019ll be interesting to see if this translates into actual migrations. Pretty much all of computational biology / bioinformatics lives on GitHub: software packages, snakemake/nf-core workflows, Bioconductor packages, lab repos, course materials. Don\u2019t forget about other infrastructure as well: GitHub Pages (e.g. pkgdown pages for R packages), CI w/ GitHub Actions, GitHub container registry, etc. Moving the social graph (issues, PRs, stars, discoverability) is enormous work, and I don\u2019t know if Codeberg could absorb the load. I can\u2019t imagine what a realistic and practical exit plan would look like.
I\u2019m not usually one to give air to the anti-AI hype. Most of what I read here is boring and irritating. However, Shubham\u2019s \u201cI\u2019m going back to writing code by hand\u201d is good. He spent ~30 weekends and >200 commits building k10s, a GPU-aware Kubernetes TUI, entirely through Claude. Then he sat down and read model.go for the first time. It was 1690 lines. He\u2019s archiving it and starting over in Rust.
AI builds features, not architecture; every prompt landed cleanly, the cumulative effect was a god object. Vibe-coding \u201cmade everything feel cheap\u201d so scope crept from a niche GPU tool to a generic k9s clone. My favorite line:
like \u201cem-dash\u201d is to ai writing, \u201cgod-object\u201d is to ai coding
His proposed remedy is putting architectural invariants into CLAUDE.md or AGENTS.md so the model sees them on every invocation.
See also the HN thread. One comment stuck out: \u201cCan\u2019t you just ask AI to break up large files into smaller ones and also explain how the code works so you can understand it?\u201d If the AI got you into the god-object hole, asking the AI to refactor its way out is probably not the move.
I was at a week-long innovation lab around AI and drug discovery this weekend. A thought in the back of my head all week was something I keep coming back to in my thinking in computational biology: the bottleneck in agentic science is evaluation, not generation. You can prompt your way to a working pipeline in a weekend. You can\u2019t prompt your way to knowing it\u2019s right.
Elsevier has joined a class-action lawsuit against Meta alleging Meta reproduced copyrighted works to train Llama. As Nature notes, this is the first AI copyright suit from major publishing houses. Elsevier publishes Cell and The Lancet, so a fair chunk of the biomedical literature is now formally a plaintiff against a frontier lab.
The lawsuit alleges Meta used Common Crawl and also that Meta downloaded and torrented works from LibGen and Sci-Hub. Meta\u2019s defense is the usual one: training is transformative use. US judges in two 2025 rulings reportedly distinguished between training (often transformative) and acquisition (the act of downloading copyrighted material), which is where torrenting from Sci-Hub is going to be a problem for Meta regardless of how fair use resolves.
Irony is dead.
Elsevier sells access to research funded by taxpayers and donated by authors who weren\u2019t paid for the manuscript and often paid Elsevier APCs to make it open. Meta scraped some of that content, allegedly via Sci-Hub, which exists precisely because Elsevier\u2019s access model is widely considered indefensible. Now Elsevier wants damages on behalf of authors who didn\u2019t get paid the first time around either. The most coherent position is probably that Meta should have paid for licensed access and that Elsevier should not be the entity collecting the check, but that isn\u2019t on offer.
If this case establishes that scraping paywalled academic content is infringement, the practical effect on open-science-trained models could be larger than the effect on Llama. Llama already exists. A future model that wants to train on biomedical literature now has a clearer legal target on its back.
A new Lancet correspondence by Topaz et al. audited 2.5 million biomedical papers for fabricated references, and the numbers are bad. The accompanying Comment by Bauchner and Rivara argues that any published paper with a fabricated reference should be retracted, which is a reasonable position that approximately no one will implement.
Topaz and colleagues pulled >100 million references from >2 million papers in PubMed Central\u2019s Open Access subset between Jan 2023 and Feb 2026. They kept the 97 million (77%) with a PMID, verified those against PubMed, Crossref, OpenAlex, and Google Scholar, used Claude to filter reference errors (misformatted but real) from genuine fabrications, and validated precision at 91% with three independent reviewers. They found 4,046 fabricated references across 2,810 papers.
The fabrication rate increased more than 12 times, from approximately four per 10,000 papers in 2023, to 51.3 per 10,000 papers in the fourth quarter of 2025
![\"\"](\"https://substackcdn.com/image/fetch/$s_!2FMa!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F022d121d-53f2-4aec-bbed-04737155bb3f_2121x1070.png\"){kind=spacer}
The inflection point is mid-2024, which is when LLM-assisted papers would start clearing typical 100-200 day submission lags. One paper on ureteroileal anastomotic techniques had 18 of 30 verified references fabricated, each tailored to the surgical topic and attributed to real urologists. The authors also flag a paper-mill pattern: the same two-author pair appearing across 11 papers in a single surgical journal in 2025.
Read this along with #3 above. If Elsevier wins the case against Meta, the legal incentives push toward licensed-only training data. The Lancet audit suggests the academic literature itself is already meaningfully polluted by models trained on it. I think this will get worse before it gets better.
Yesterday, Thomas G. Dietterich (arXiv moderator for cs.LG) announced that arXiv will implement 1-year ban for papers containing incontrovertible evidence of unchecked LLM-generated errors, such as hallucinated references or results. Here\u2019s the full text of the thread:
Attention arXiv authors: Our Code of Conduct states that by signing your name as an author of a paper, each author takes full responsibility for all its contents, irrespective of how the contents were generated.
If generative AI tools generate inappropriate language, plagiarized content, biased content, errors, mistakes, incorrect references, or misleading content, and that output is included in scientific works, it is the responsibility of the author(s).
We have recently clarified our penalties for this. If a submission contains incontrovertible evidence that the authors did not check the results of LLM generation, this means we can\u2019t trust anything in the paper.
The penalty is a 1-year ban from arXiv followed by the requirement that subsequent arXiv submissions must first be accepted at a reputable peer-reviewed venue.
Examples of incontrovertible evidence: hallucinated references, meta-comments from the LLM (\u201dhere is a 200 word summary; would you like me to make any changes?\u201d; \u201cthe data in this table is illustrative, fill it in with the real numbers from your experiments\u201d).
I\u2019m about as split on this one as the comments on the OP are. On one hand, GOOD. Hallucinated citations and unchecked AI-authored content is polluting the literature everywhere. I think this borderlines on scientific misconduct, and it destroys trust in the entire scientific enterprise.
Oh the other hand there are lots of problems with detection and enforcement. AI detection software is a cat and mouse game that doesn\u2019t work reliably. And on the enforcement side \u2014 what happens when you\u2019re a co-author on a paper with a hallucinated citation? Say I tell my grad student to work on the methods section and they get an undergrad to write a small section that they worked on, and said undergrad carelessly inserts a fabricated citation. If this paper makes its way onto arXiv, does that infraction go all the way up the chain with the banhammer coming down on all co-authors? Have you ever submitted a paper written with a bunch of co-authors and meticulously looked up every reference or checked that every parameter setting in the detailed methods section is actually a valid parameter for whatever tool was being used? I have.
I think a middle ground solution with a big red banner or warning flag on the abstract page or search results noting that the paper likely contains unverified AI-generated content.
![\"\"](\"https://substackcdn.com/image/fetch/$s_!71Lh!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fa4b57310-795f-4211-80bb-6fe9ab994d50_1448x1086.png\")
Again, the detection piece is difficult, and authors should be given a chance to respond before getting the scarlet letter. I think the 1-year ban is severe, and if applied to all co-authors, could be extremely damaging to one\u2019s career just because a middle author responsible for page 98 of a large supplemental info section was careless and wasn\u2019t carefully scrutinized. I also worry that such a ban could be inconsistently applied since there\u2019s a lot of subjectivity and guesswork involved with this endeavor.
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The paper isn\u2019t real. Any resemblance to a real paper or real authors is purely coincidental.","src":"https://substackcdn.com/image/fetch/$s_!71Lh!,w_1456,c_limit,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fa4b57310-795f-4211-80bb-6fe9ab994d50_1448x1086.png"},{"src":"https://substackcdn.com/image/fetch/$s_!6ew2!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fed1b0b11-6f3f-4159-b566-3c60cdedf5c5_1273x916.png"},{"src":"https://substackcdn.com/image/fetch/$s_!2FMa!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F022d121d-53f2-4aec-bbed-04737155bb3f_2121x1070.png"},{"src":"https://substackcdn.com/image/fetch/$s_!71Lh!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fa4b57310-795f-4211-80bb-6fe9ab994d50_1448x1086.png"}],"indexed":true,"indexed_at":1778837687,"language":"en","parent_doi":null,"published_at":1778835935,"reference":[],"registered_at":0,"relationships":[],"rid":"ne4rm-36y89","status":"active","summary":"GitHub problems, vibe coding regrets, Elsevier sues Meta, fabricated citations, the arXiv banhammer for AI-generated content","tags":["Papers","AI"],"title":"Five Things (May 15, 2026): AI is why we can't have nice things","updated_at":1778835935,"url":"https://blog.stephenturner.us/p/five-things-may-15-2026","version":"v1"}},{"document":{"abstract":null,"archive_url":null,"authors":[{"contributor_roles":[],"family":"Sielert","given":"Deborah"},{"affiliation":[{"id":"https://ror.org/0546hnb39","name":"University of Konstanz"}],"contributor_roles":[],"family":"Flaig","given":"Sebastian","url":"https://orcid.org/0009-0001-1247-6976"}],"blog":{"archive_collection":null,"archive_host":null,"archive_prefix":null,"archive_timestamps":null,"authors":[{"name":"Open Access Network"}],"canonical_url":null,"category":"otherSocialSciences","community_id":"969d397b-49b9-4c53-9220-607ef85409e5","created_at":1743604215.212958,"current_feed_url":null,"description":"Neueste Beitr\u00e4ge","doi":null,"doi_as_guid":false,"favicon":null,"feed_format":"application/rss+xml","feed_url":"https://open-access.network/rss-feed?type=200","filter":null,"funding":null,"generator":"Other","generator_raw":"Other","home_page_url":"https://open-access.network","id":"f5a57494-4e8e-41d9-b84c-26cb9b0ab291","indexed":true,"issn":null,"language":"de","license":"https://creativecommons.org/licenses/by/4.0/legalcode","mastodon":null,"prefix":"10.64395","registered_at":0,"relative_url":null,"ror":null,"secure":true,"slug":"oa_network","status":"active","subfield":"1802","subfield_validated":null,"title":"Open Access Network","updated_at":1778835091.735266,"use_api":null,"use_mastodon":false,"user_id":null},"blog_name":"Open Access Network","blog_slug":"oa_network","content_html":"Worauf m\u00fcssen Wissenschaftler*innen am Beginn ihrer akademischen Karriere beim Open-Access-Publizieren achten? Und welche Informationsangebote und Tools k\u00f6nnen dieser Zielgruppe beim Einstieg in die Open-Access-Thematik helfen? \u00dcber diese und viele weitere Fragen hat Deborah Sielert im Podcast \u201eNachwuchsFragen\u201c der Graduiertenakademie an der Leibniz-Universit\u00e4t Hannover gesprochen.\n\nOpen-Access-Publizieren aus Nachwuchsperspektive\nIn der 43-min\u00fctigen Folge \u201ePublizieren mit Open Access\u201c gibt Deborah Sielert eine Einf\u00fchrung in das Thema Open Access, die speziell f\u00fcr junge Wissenschaftler*innen mit noch wenig Erfahrung im wissenschaftlichen Publikationssystem zugeschnitten ist. Neben einem kurzen geschichtlichen Abriss der Entwicklungen des wissenschaftlichen Publizierens, die zur Open-Access-Transformation gef\u00fchrt haben, erkl\u00e4rt sie zentrale Begriffe und Abk\u00fcrzungen, von APC \u00fcber DEAL bis hin zu CC-BY-NC und den Zugangswegen zu Open Access mit ihren verschiedenen Farbbezeichnungen. \nBesonders spannend ist Deborah Sielerts doppelte Perspektive: Einerseits hat sie w\u00e4hrend ihrer Promotion eigene Erfahrungen als junge Forscherin gemacht, andererseits sieht sie nun als Open-Access-Beraterin an der TIB auch die weitl\u00e4ufigen Hintergr\u00fcnde des wissenschaftlichen Publizierens. In dieser Doppelrolle berichtet sie von den Herausforderungen, mit denen Early Career Researchers beim Open-Access-Publizieren konfrontiert sind, und benennt gleichzeitig L\u00f6sungen und Hilfsangebote. Bei der mitunter m\u00fchevollen Suche nach einem passenden Publikationsort f\u00fcr eine Open-Access-Publikation k\u00f6nnen neben den einrichtungsspezifischen Beratungsangeboten an der Bibliothek beispielsweise das B!SON-Tool oder auch der Erfahrungsaustausch mit der Fachcommunity unterst\u00fctzen. Au\u00dferdem sp\u00fcren insbesondere Wissenschaftler*innen am Anfang ihrer Karriere den Publikationsdruck der weit verbreiteten \u201ePublish or Perish\u201c-Kultur, was unseri\u00f6se Predatory Journals versuchen f\u00fcr ihre Zwecke zu nutzen. Auch hier k\u00f6nnen technische Angebote wie Positiv- bzw. Negativlisten von \u201eThink Check Submit\u201c oder das Verzeichnis DOAJ, aber auch die pers\u00f6nliche Open-Access-Beratung an der eigenen Einrichtung Unsicherheiten reduzieren und f\u00fcr derartige Stolpersteine im Publikationswesen sensibilisieren.\n\n\u201eIch h\u00e4tte gerne mehr Wissen \u00fcber den Publikationsmarkt und Themen wie Lizenzen gehabt, denn da besteht f\u00fcr mich ein Zusammenhang zu Selbstwirksamkeit und zum selbstbewussten Navigieren durch die Promotions- und Postdoc-Phase.\u201c\n\u2013 Deborah Sielert \u2013\n\nR\u00fcckblickend auf ihre eigenen Erfahrungen w\u00e4hrend der Promotion macht Deborah Sielert deutlich, wie wichtig der Informationsfluss an junge Wissenschaftler*innen ist. Wer seine Rechte als Urheber*in kennt, kann selbstbewusster mit Verlagen verhandeln und informierte Entscheidungen treffen. Nachwuchsforschende sind nicht den Zw\u00e4ngen eines starren Systems ausgeliefert, sondern k\u00f6nnen aktiv Einfluss nehmen \u2013 etwa durch die bewusste Wahl eines Journals oder einer Lizenz. \u201eIm R\u00fcckblick, wenn ich jetzt nochmal publizieren wollen w\u00fcrde, w\u00fcrde ich eher schauen, welches Journal ich zum Beispiel vom Gesch\u00e4ftsmodell her unterst\u00fctzenswert finde\u201c, res\u00fcmiert sie diesen Gedanken.\n\nLink zur Folge\nDie Podcastfolge kann auf der Webseite des \u201eNachwuchsFragen\u201c-Podcast oder auf allen g\u00e4ngigen Podcast-Plattformen geh\u00f6rt werden.","doi":"https://doi.org/10.64395/hsdb7-ak430","funding_references":null,"guid":"https://open-access.network/blog/open-access-fuer-nachwuchsforschende-folge-im-podcast-nachwuchsfragen","id":"1aaaadae-eabd-4aa2-a2d0-582c3b34afe8","image":null,"images":[],"indexed":true,"indexed_at":1778834134,"language":"de","parent_doi":null,"published_at":1778830980,"reference":[],"registered_at":0,"relationships":[],"rid":"e3fem-bf772","status":"active","summary":"Worauf m\u00fcssen Wissenschaftler*innen am Beginn ihrer akademischen Karriere beim Open-Access-Publizieren achten? Und welche Informationsangebote und Tools k\u00f6nnen dieser Zielgruppe beim Einstieg in die Open-Access-Thematik helfen? \u00dcber diese und viele weitere Fragen hat Deborah Sielert im Podcast \u201eNachwuchsFragen\u201c der Graduiertenakademie an der Leibniz-Universit\u00e4t Hannover gesprochen.","tags":["Beratung","Open Access In Der Praxis"],"title":"Open Access f\u00fcr Nachwuchsforschende \u2013 Folge im Podcast \u201eNachwuchsFragen\u201c","updated_at":1778830980,"url":"https://open-access.network/blog/open-access-fuer-nachwuchsforschende-folge-im-podcast-nachwuchsfragen","version":"v1"}},{"document":{"abstract":null,"archive_url":null,"authors":[{"affiliation":[{"id":"https://ror.org/02k3smh20","name":"University of Kentucky"}],"contributor_roles":[],"family":"Fruehwald","given":"Josef","url":"https://orcid.org/0000-0001-8480-9461"}],"blog":{"archive_collection":null,"archive_host":null,"archive_prefix":null,"archive_timestamps":null,"authors":null,"canonical_url":null,"category":"socialScience","community_id":"d875be0a-4a87-4c67-bbc8-803adec3b6a7","created_at":1753900307.048582,"current_feed_url":null,"description":null,"doi":null,"doi_as_guid":false,"favicon":null,"feed_format":"application/rss+xml","feed_url":"https://jofrhwld.github.io/blog/index.xml","filter":null,"funding":null,"generator":"Quarto","generator_raw":"Quarto 1.7.32","home_page_url":"https://jofrhwld.github.io/blog/","id":"ee72741c-6561-4ed1-8f78-474b79010844","indexed":true,"issn":null,"language":"en","license":"https://creativecommons.org/licenses/by/4.0/legalcode","mastodon":null,"prefix":"10.59350","registered_at":0,"relative_url":null,"ror":null,"secure":true,"slug":"jofrhwld","status":"active","subfield":"1203","subfield_validated":null,"title":"V\u00e6l Space","updated_at":1778834761.799898,"use_api":null,"use_mastodon":false,"user_id":null},"blog_name":"V\u00e6l Space","blog_slug":"jofrhwld","content_html":"I\u2019ve been noodling over things related to causal inference for a bit now, like DAGs, adjustment sets, marginal effect etc. One thing I hadn\u2019t fully appreciated before is how your choice to estimate direct effects will make your model predictions very sensitive to the kind of prediction grid you use. The rest of this post is just me working through these complications step-by-step.
\nA relatively common kind of causal DAG that (implicitly) comes up in linguistics involves some kind of categorical predictor that has an effect on another continuous predictor.
\n![](\"https://jofrhwld.github.io/blog/posts/2026/05/2026-05-15_total-vs-direct-predictions/typst/dag-dark.svg\")
![](\"https://jofrhwld.github.io/blog/posts/2026/05/2026-05-15_total-vs-direct-predictions/typst/dag-lite.svg\")
For example:
\n![](\"https://jofrhwld.github.io/blog/posts/2026/05/2026-05-15_total-vs-direct-predictions/typst/dag-vowel-dark.svg\")
![](\"https://jofrhwld.github.io/blog/posts/2026/05/2026-05-15_total-vs-direct-predictions/typst/dag-vowel-lite.svg\")
With causal relationships like this, people often ask something like
\n\n\nIs there really an effect of consonant voicing on vowel quality, or is there just an effect of vowel duration?
\n
This is a question about the direct effect of voicing on vowel quality. If we set up the dag and check what adjustment variables we need to include to estimate the direct effect of voicing, we\u2019ll see that we need to include duration in the model.
\nvoicing_dag <- ggdag::dagify(\n quality ~ voicing + duration,\n duration ~ voicing\n)\n\ndagitty::adjustmentSets(\n voicing_dag, \n outcome = \"quality\",\n exposure = \"voicing\",\n effect = \"direct\"\n) { duration }But, if we wanted to estimate the total effect of voicing on vowel quality, we shouldn\u2019t include duration.
\ndagitty::adjustmentSets(\n voicing_dag, \n outcome = \"quality\",\n exposure = \"voicing\",\n effect = \"total\"\n) {}This difference between direct and total effects feels a bit abstract sometimes. I\u2019m going to walk through a little example using the penguins dataset, with a focus for how we should approach getting model predictions.
The causal relationships I\u2019ll look at in the penguins data set are:
![](\"https://jofrhwld.github.io/blog/posts/2026/05/2026-05-15_total-vs-direct-predictions/typst/dag-peng-dark.svg\")
![](\"https://jofrhwld.github.io/blog/posts/2026/05/2026-05-15_total-vs-direct-predictions/typst/dag-peng-lite.svg\")
If we look at the effect of species on both bill length and body mass, we can see a clear effect for both:
\npenguins |>\n select(\n species, body_mass, bill_len\n ) |>\n drop_na() |>\n pivot_longer(\n body_mass:bill_len,\n names_to = \"measure\"\n ) |>\n ggplot(\n aes(species, value)\n )+\n stat_dots(\n side = \"both\"\n ) +\n facet_wrap(\n ~measure,\n scales = \"free_y\"\n ) +\n labs(y = NULL) -> p\n\np\np+theme_darkmode()![](\"https://jofrhwld.github.io/blog/posts/2026/05/2026-05-15_total-vs-direct-predictions//index_files/figure-html/unnamed-chunk-5-1.png\")
![](\"https://jofrhwld.github.io/blog/posts/2026/05/2026-05-15_total-vs-direct-predictions//index_files/figure-html/unnamed-chunk-5-2.png\")
And if we look at the effect of body mass on bill length, we can see another very clear effect.
\npenguins |> \n ggplot(\n aes(body_mass, bill_len, color = species)\n ) + \n geom_point() +\n guides(\n color = \"none\"\n )-> p\n\np + \n stat_ellipse(\n geom = \"labelpath\",\n aes(label = species),\n hjust = 0,\n label.padding = 0.01,\n show.legend = F \n) \n\np + \n stat_ellipse(\n geom = \"labelpath\",\n aes(label = species),\n hjust = 0,\n label.padding = 0.01,\n fill = plot_bg,\n show.legend = F\n) + \n theme_darkmode()![](\"https://jofrhwld.github.io/blog/posts/2026/05/2026-05-15_total-vs-direct-predictions//index_files/figure-html/unnamed-chunk-6-1.png\")
![](\"https://jofrhwld.github.io/blog/posts/2026/05/2026-05-15_total-vs-direct-predictions//index_files/figure-html/unnamed-chunk-6-2.png\")
Let\u2019s, really quick, get the mean and standard error of bill length by species.
\npenguins |>\n drop_na(starts_with(\"bill_\")) ->\n penguin_full\n\npenguin_full|>\n summarise(\n .by = species,\n estimate = mean(bill_len),\n sd = sd(bill_len),\n n = n()\n ) |> \n mutate(\n se = sd / (sqrt(n)),\n conf.low = estimate - (1.96*se),\n conf.high = estimate + (1.96*se),\n method = \"mean\"\n ) ->\n mean_est| species | \nestimate | \nconf.low | \nconf.high | \n
|---|---|---|---|
| Adelie | \n38.8 | \n38.4 | \n39.2 | \n
| Gentoo | \n47.5 | \n47 | \n48 | \n
| Chinstrap | \n48.8 | \n48 | \n49.6 | \n
I\u2019ll call these quantities with a superscript for each species.
Here they are plotted over the data:
\n![](\"https://jofrhwld.github.io/blog/posts/2026/05/2026-05-15_total-vs-direct-predictions//index_files/figure-html/unnamed-chunk-9-1.png\")
![](\"https://jofrhwld.github.io/blog/posts/2026/05/2026-05-15_total-vs-direct-predictions//index_files/figure-html/unnamed-chunk-9-2.png\")
One way to estimate the effect of species on bill length would be to subtract these means from eachother.
\nmean_est |>\n select(\n species,\n estimate\n ) |>\n pivot_wider(\n names_from = species,\n values_from = estimate\n ) |>\n mutate(\n Chinstrap - Adelie,\n Gentoo - Adelie\n )|>\n select(\n matches(\"-\")\n ) |>\n pivot_longer(\n everything(),\n names_to = \"contrast\",\n values_to = \"estimate\"\n ) |>\n mutate(method = \"mean\") ->\n mean_comparisons\n\nmean_comparisons |> \n select(-method) |> \n tt()| contrast | \nestimate | \n
|---|---|
| Chinstrap - Adelie | \n10.04 | \n
| Gentoo - Adelie | \n8.71 | \n
If we look at these differences in means, and consider the scatterplot of body mass vs bill length, we might wonder whether the difference between Gentoo and Adelie is really that large. Maybe Gentoo penguins are just larger overall, with proportionally longer bills. That\u2019s where estimating the direct effect comes in.
\nA simple linear model will do the trick:
\nbill_model <- lm(\n bill_len ~ body_mass + species, \n data = penguin_full\n)And if we look at the estimated effect of species:
\ntidy(\n bill_model\n) |> \n filter(\n str_detect(\n term, \"species\"\n )\n ) |>\n select(term, estimate) |>\n tt()| term | \nestimate | \n
|---|---|
| speciesChinstrap | \n9.92 | \n
| speciesGentoo | \n3.56 | \n
The estimated difference between Gentoo and Adelie is, in fact, about half as much as the comparison of means suggested.
\nHere\u2019s where things start getting a little tricky, and we need to take some care in how we get and think about predicted values.
\nThe function avg_predictions() will calculate the predicted unit level bill length, then average over species. Here, stands for the species variable, and
stands form the body mass variable.
avg_predictions(\n bill_model,\n by = \"species\"\n) |>\n mutate(method = \"pred_avg\") ->\n avg_pred| species | \nestimate | \nconf.low | \nconf.high | \n
|---|---|---|---|
| Adelie | \n38.8 | \n38.4 | \n39.2 | \n
| Chinstrap | \n48.8 | \n48.3 | \n49.4 | \n
| Gentoo | \n47.5 | \n47.1 | \n47.9 | \n
We can visually compare these average predictions to the mean and standard errors we estimated above:
\nbind_rows(\n mean_est,\n avg_pred\n) |>\n ggplot(\n aes(species, estimate)\n ) + \n geom_dots(\n data = penguin_full,\n aes(x = species, y = bill_len),\n side = \"both\"\n ) + \n geom_pointinterval(\n size = 5, \n aes(\n ymin = conf.low,\n ymax = conf.high,\n color = method\n ),\n position = position_dodge(width = 0.2)\n ) ->\n p\n\np\np+theme_darkmode()![](\"https://jofrhwld.github.io/blog/posts/2026/05/2026-05-15_total-vs-direct-predictions//index_files/figure-html/unnamed-chunk-15-1.png\")
![](\"https://jofrhwld.github.io/blog/posts/2026/05/2026-05-15_total-vs-direct-predictions//index_files/figure-html/unnamed-chunk-15-2.png\")
To get predictions at representative values, we can use the datagrid() function. If we just pass the model to datagrid() and no other arguments, it will give us back a 1 row data frame where every column is either the average value across the original data, or the most frequent level.
| rowid | \nbill_len | \nbody_mass | \nspecies | \n
|---|---|---|---|
| 1 | \n43.9 | \n4202 | \nAdelie | \n
To get a prediction for each species, I\u2019ll pass a vector of species names to species.
| rowid | \nbill_len | \nbody_mass | \nspecies | \n
|---|---|---|---|
| 1 | \n43.9 | \n4202 | \nAdelie | \n
| 2 | \n43.9 | \n4202 | \nChinstrap | \n
| 3 | \n43.9 | \n4202 | \nGentoo | \n
We can describe the predictions we get as the expected bill length for each species, conditional on the average body mass.
\npredictions(\n bill_model,\n newdata = grid1\n) |> \n mutate(method = \"pred_grid1\")->\n species_predIf we compare these predicted values to the previous estimates, they\u2019re very different!
\nbind_rows(\n mean_est,\n avg_pred,\n species_pred\n) |> \n ggplot(\n aes(species, estimate)\n ) + \n geom_dots(\n data = penguin_full,\n aes(x = species, y = bill_len),\n side = \"both\"\n ) + \n geom_pointinterval(\n size = 5, \n aes(\n ymin = conf.low,\n ymax = conf.high,\n color = method\n ),\n position = position_dodge(width = 0.3)\n ) -> \n p\n\np\np + theme_darkmode()![](\"https://jofrhwld.github.io/blog/posts/2026/05/2026-05-15_total-vs-direct-predictions//index_files/figure-html/unnamed-chunk-19-1.png\")
![](\"https://jofrhwld.github.io/blog/posts/2026/05/2026-05-15_total-vs-direct-predictions//index_files/figure-html/unnamed-chunk-19-2.png\")
The predicted bill length for each species, especially Gentoo, don\u2019t look like typical bill lengths for each species. But that\u2019s because these predictions were conditional on the average body mass across all individuals, which isn\u2019t a representatuve body mass for any individual species.
\nbill_model |>\n predictions(\n newdata = datagrid(\n species = unique,\n body_mass = range\n )\n )->\n full_est\n\nbolden <- \\(x){\n str_glue(\"<b>{x}</b>\")\n}\n\npenguin_full |> \n ggplot(\n aes(body_mass, bill_len, color = species)\n ) + \n geom_point(\n size = 0.2,\n alpha = 0.5\n ) + \n geom_textline(\n data = full_est,\n aes(x = body_mass, y = estimate, label = bolden(species)),\n hjust= 0.7,\n rich = T\n )+\n geom_vline(\n xintercept = mean(penguin_full$body_mass)\n ) +\n geom_point(\n data = species_pred,\n aes(y = estimate)\n ) +\n guides(\n color = \"none\"\n ) -> p\n\np\np + theme_darkmode()![](\"https://jofrhwld.github.io/blog/posts/2026/05/2026-05-15_total-vs-direct-predictions//index_files/figure-html/unnamed-chunk-20-1.png\")
![](\"https://jofrhwld.github.io/blog/posts/2026/05/2026-05-15_total-vs-direct-predictions//index_files/figure-html/unnamed-chunk-20-2.png\")
Instead of setting body_mass to the mean across all penguins, let\u2019s instead set it to the mean within each species. We can do that with datagrid() by passing it by = \"species\".
| rowid | \nbill_len | \nbody_mass | \nspecies | \n
|---|---|---|---|
| 1 | \n38.8 | \n3701 | \nAdelie | \n
| 2 | \n48.8 | \n3733 | \nChinstrap | \n
| 3 | \n47.5 | \n5076 | \nGentoo | \n
Using this prediction grid, we could describe the preditions as:
\npredictions(\n bill_model,\n newdata = grid2\n) |> \n mutate(\n method = \"pred_grid2\"\n )->\n typical_predComparing these predictions to estimates we had before, we can see they\u2019re more in-line with what we expect the typical bill lengths to be for each species.
\nbind_rows(\n mean_est,\n avg_pred,\n species_pred,\n typical_pred\n) |> \n ggplot(\n aes(species, estimate)\n ) + \n geom_dots(\n data = penguin_full,\n aes(x = species, y = bill_len),\n side = \"both\"\n ) + \n geom_pointinterval(\n size = 5, \n aes(\n ymin = conf.low,\n ymax = conf.high,\n color = method\n ),\n position = position_dodge(width = 0.4)\n ) -> \n p\n\np\np + theme_darkmode()![](\"https://jofrhwld.github.io/blog/posts/2026/05/2026-05-15_total-vs-direct-predictions//index_files/figure-html/unnamed-chunk-23-1.png\")
![](\"https://jofrhwld.github.io/blog/posts/2026/05/2026-05-15_total-vs-direct-predictions//index_files/figure-html/unnamed-chunk-23-2.png\")
The reason we\u2019ve got predictions that are more in line with what is typical for each species is because we\u2019ve evaluated the model at body masses that are more in line with what is typical for each species.
\npenguin_full |> \n ggplot(\n aes(body_mass, bill_len, color = species)\n ) + \n geom_point(\n size = 0.2,\n alpha = 0.5\n ) + \n geom_textline(\n data = full_est,\n aes(x = body_mass, y = estimate, label = bolden(species)),\n hjust= 0.9,\n rich = T\n ) +\n geom_segment(\n data = typical_pred,\n aes(\n x = body_mass,\n xend = body_mass,\n y = estimate\n ),\n yend = -Inf\n ) +\n geom_point(\n data = typical_pred,\n aes(\n x = body_mass,\n y = estimate\n )\n ) +\n guides(\n color = \"none\"\n ) ->\n p\n\np\np + theme_darkmode()![](\"https://jofrhwld.github.io/blog/posts/2026/05/2026-05-15_total-vs-direct-predictions//index_files/figure-html/unnamed-chunk-24-1.png\")
![](\"https://jofrhwld.github.io/blog/posts/2026/05/2026-05-15_total-vs-direct-predictions//index_files/figure-html/unnamed-chunk-24-2.png\")
We can get the Average Treatment Effect of species by calculating how different each individual\u2019s bill length is predicted to be if we swapped its species.
\navg_comparisons(\n bill_model,\n variables = \"species\"\n) -> \n avg_comp| contrast | \nestimate | \n
|---|---|
| Chinstrap - Adelie | \n9.92 | \n
| Gentoo - Adelie | \n3.56 | \n
But, again, it\u2019s important that these contrasts are conditional on the body mass of each penguin. So, if you had an Adelie and a Gentoo with the same body mass, the Gentoo would have a bill length about 3.5 mm longer. But, not that many Adelie and Gentoo penguins have the same body mass!
\npenguin_full |>\n ggplot(\n aes(body_mass)\n ) +\n geom_dots(\n aes(\n fill = species,\n color = species,\n order = species\n ),\n group = 1\n ) + \n scale_y_continuous(\n expand = expansion(0)\n ) ->\n p\n\np + theme_no_y() + \n theme_sub_legend(\n position = \"inside\",\n position.inside = c(0.85,0.8)\n )\np + theme_darkmode() + theme_no_y() +\n theme_sub_legend(\n position = \"inside\",\n position.inside = c(0.85,0.8)\n )![](\"https://jofrhwld.github.io/blog/posts/2026/05/2026-05-15_total-vs-direct-predictions//index_files/figure-html/unnamed-chunk-27-1.png\")
![](\"https://jofrhwld.github.io/blog/posts/2026/05/2026-05-15_total-vs-direct-predictions//index_files/figure-html/unnamed-chunk-27-2.png\")
So, if you picked a random Adelie and a random Gentoo, the best estimate of the difference in their bill size (the direct effect) would be larger! One way we could estimate the typical difference between Gentoo and Adelie is to calculate every pairwise difference between individual penguins.
\ntibble(\n diff = as.vector(diff_mat)\n) |>\n ggplot(\n aes(diff)\n ) + \n stat_dots()+\n geom_vline(\n xintercept = mean(diff_mat)\n ) +\n scale_y_continuous(\n expand = expansion(0)\n ) +\n labs(\n x = \"Gentoo - Adelie\"\n ) ->\n p\n\np + theme_no_y()\np + theme_darkmode() + theme_no_y()![](\"https://jofrhwld.github.io/blog/posts/2026/05/2026-05-15_total-vs-direct-predictions//index_files/figure-html/unnamed-chunk-29-1.png\")
![](\"https://jofrhwld.github.io/blog/posts/2026/05/2026-05-15_total-vs-direct-predictions//index_files/figure-html/unnamed-chunk-29-2.png\")
Almost every Gentoo has a longer beak than every Adelie. And the average of these pairwise comparisons is the total effect of species on bill length.
\nmean(diff_mat)[1] 8.713487To be honest, I\u2019m not 100% sure what the upshot here is. Let\u2019s imagine a case where following consonant voicing only had an indirect effect on vowel quality via vowel duration. It would be an interesting result to find that after adjusting for duration, the effect of voicing is effectively 0. But estimating and plotting model predictions that show no difference between voicing contexts would be strange, since voicing contexts also systematically differ in terms of duration. You\u2019d effectively be plotting predicted values of very atypical cases.
\nYou could try plotting both kinds of predictions\u2026 but I\u2019m already dreading the kind of tortured prose involved in describing the different kinds of predictions to readers.
\n@online{fruehwald2026,\n author = {Fruehwald, Josef},\n title = {Getting Predictions When Estimating Direct Vs Total Effects.},\n series = {V\u00e6l Space},\n date = {2026-05-15},\n url = {https://jofrhwld.github.io/blog/posts/2026/05/2026-05-15_total-vs-direct-predictions/},\n doi = {10.59350/rps04-6zc41},\n langid = {en}\n}\nOver the past decade, transformative agreements have been instrumental in driving the transition to open access by redirecting former subscription costs to fund open access publishing for affiliated authors of the negotiating institutions (de Jonge et al. 2025; D\u00e9r 2025). Open publishing agreements have gained serious traction, with the ESAC registry listing 1,644 such agreements as of April 29, 2026, including 177 concluded with German institutions and consortia (ESAC Initiative, n.d.).
\nIn D\u00f6rner (2026), I conducted a content analysis of 13 transformative agreements between scientific publishers and German consortia, with a focus on contractual provisions related to open metadata and data-analytical research services. With respect to open metadata provisions, 12 of the 13 agreements mandated metadata submission to Crossref. However, only four agreements specified detailed metadata fields for Crossref delivery, despite these being non-exhaustive lists. Metadata fields explicitly referenced included, inter alia, author information, ORCID identifiers, affiliations, and open access licence information.
\nThis blog post extends the prior content analysis by assessing the implementation of contractual provisions through a data-driven approach, focusing on two aspects: (i) CC BY licence adoption and (ii) open metadata coverage including ORCID and ROR IDs, TDM information, funding information, funder DOIs, and open abstracts. I build upon prior work by the Hybrid Open Access Dashboard (HOAD) and the Sesame Open Science (SOS) Crossref truth table. HOAD is an openly available data analytics tool that currently tracks, amongst other things, the use of Creative Commons (CC) licences and the coverage of open metadata in Crossref for open access articles in hybrid journals. The metadata captured by HOAD include text and data mining (TDM) information, ORCID coverage, funding information, and the coverage of open abstracts and citations (Achterberg and Jahn 2023). However, some dimensions are missing from HOAD, such as ROR coverage and information for articles in fully open access journals. The SOS Crossref truth table is a processed table based on Crossref data indicating presence and counts of several metadata elements for each record in Crossref. Compared to HOAD the truth table provides detailed information on affiliations and ROR coverage, but does not include TDM and CC licence information. Furthermore, its scope is broader, meaning that articles made available through transformative agreements are not pre-identified.
\nThis analysis reproduces and adapts the data analytics workflow underlying HOAD, as describe in Jahn (2025b). To this end, data retrieval started with obtaining journal and institutional information from preserved transformative agreement data from the cOAlition S Journal Checker Tool (JCT) 1. I subsequently filtered the data based on the ESAC IDs of the selected 13 transformative agreements (see Table\u00a01) to obtain information about journal portfolios and participating institutions pertaining specifically to the respective agreements. Journal information was further enriched with linking ISSNs (ISSN-Ls), as provided by the ISSN International Centre in the February 2026 version, based on ISSN matching to allow unique reference of journals.
\nUsing the compiled JCT data, I retrieved article-level metadata from the Crossref April 2026 database snapshot and enriched it with first-author affiliation data from the OpenAlex Walden April 2026 database snapshot. All data was accessed via the SUB G\u00f6ttingen Open Scholarly Data Warehouse. It should be noted that affiliation metadata coverage in OpenAlex has been reported to have declined substantially following the transition to Walden, partly due to publishers not sharing affiliation metadata via Crossref and partly due to technical issues within OpenAlex itself (Jahn 2025a), which may affect the completeness of first-author affiliation matching in this analysis.
\nThe article-level data was restricted to the publication years 2019\u20132025, based on the issued date, to account for varying transformative agreement terms and full-year data availability (see Table\u00a01). Non-scholarly journal content, such as table of contents etc., was excluded via paratext recognition, enrichment with first-author affiliation data was done by matching JCT participating institution information with OpenAlex affiliation data using ROR-IDs and institutional names as a fall back option. Furthermore the SOS Crossref truth table data from the January 2026 snapshot was matched using DOIs.
\n| Publisher | \nConsortium Lead | \nTerm | \nESAC ID | \n
|---|---|---|---|
| Elsevier | \nDEAL | \n01.09.2023\u201331.12.2028 | \nels2023deal | \n
| Hogrefe | \nSUB G\u00f6ttingen | \n01.01.2021\u201331.12.2023 | \nhogrefe2021gac | \n
| 01.01.2024\u201331.12.2026 | \nhogrefe2024gac | \n||
| Optica | \nTIB | \n01.01.2023\u201331.12.2026 | \nopg2023tib | \n
| Royal Society of Chemistry | \nTIB | \n01.01.2024\u201331.12.2027 | \nrsc2024tib | \n
| Springer Nature | \nDEAL | \n01.01.2020\u201331.12.2023 | \nsn2020deal | \n
| 01.01.2024\u201331.12.2028 | \nsn2024deal | \n||
| MPDL | \n01.01.2021\u201331.12.2024 | \nsn2021gac | \n|
| Trans Tech Publications | \nTIB | \n01.01.2024\u201331.12.2026 | \nttp2024tib | \n
| Walter de Gruyter | \nSUB G\u00f6ttingen | \n01.01.2022\u201331.12.2022 | \ndegruy2022gac | \n
| 01.01.2023\u201331.12.2024 | \ndegruy2023gac | \n||
| Wiley | \nDEAL | \n01.01.2019\u201331.12.2023 | \nwiley2019deal | \n
| 01.01.2024\u201331.12.2028 | \nwiley2024deal | \n
My workflow extends the current workflows for HOAD in the following respects: (1) journal coverage includes both hybrid and fully open access journals rather than hybrid journals only, (2) article data is restricted to pertain only to the selected 13 transformative agreements presented in Table\u00a01, (3) I additionally enriched the data set with data from the SOS Crossref truth table.
\nTo obtain information about metadata coverage, I computed counts of authors, affiliations, funders, and their respective persistent identifiers, as well as indicators for the presence of key metadata fields such as TDM support and open abstracts. Affiliation and ROR ID counts were computed as distinct values per article. This means that if multiple authors from the same institution appear on an article, the affiliation and its designated ROR ID are each counted only once. The number of affiliations was determined by first checking for ROR IDs and using name strings as a fall back option, when affiliations had no ROR IDs assigned. I identified open access articles by the presence of a CC licence in the version of record metadata. I therefore did not retrieve licence URLs for author accepted manuscript or TDM article versions, as identified by Crossref\u2019s content_version field. Subsequently, articles without a CC licence were classified as non-open access, regardless of publisher policies or other access indicators.
\nThe following SQL code shows the query used to retrieve the article-level data set, compute different metrics and join the SOS Crossref truth table.
\nWITH filtered_publications AS (\n SELECT DISTINCT\n UPPER(TRIM(cr.doi)) AS doi,\n jct.issn_l,\n jct.esac_id AS jn_esac_id,\n cr.publisher AS cr_publisher,\n cr.container_title AS cr_journal_title,\n EXTRACT(YEAR FROM cr.issued) AS cr_year,\n CASE WHEN cr.abstract IS NOT NULL THEN 1 END AS has_abstract,\n cr.license,\n cr.author,\n cr.link,\n cr.funder\n FROM (\n SELECT SPLIT(issn, \",\") AS issn,\n doi,\n publisher,\n container_title,\n issued,\n license,\n abstract,\n author,\n link,\n funder\n FROM `subugoe-collaborative.cr_instant.snapshot`\n WHERE NOT REGEXP_CONTAINS(\n title,\n '(?i)^Author Index$|^Back Cover|^Contents$|^Contents:|^Corrigendum|^Cover Image|^Cover Picture|^Editorial Board|^Front Cover|^Frontispiece|^Inside Back Cover|^Inside Cover|^Inside Front Cover|^Issue Information|^List of contents|^Masthead|^Title page|^Correction$|^Corrections to|^Corrections$|^Withdrawn|^Frontmatter'\n )\n AND (\n NOT REGEXP_CONTAINS(page, '^S')\n OR page IS NULL\n )\n AND (\n NOT REGEXP_CONTAINS(issue, '^S')\n OR issue IS NULL\n )\n AND EXTRACT(YEAR FROM issued) BETWEEN 2019 AND 2025\n ) AS cr\n CROSS JOIN UNNEST(cr.issn) AS issn\n INNER JOIN `subugoe-collaborative.resources.oad_jct_jn` jct\n ON issn = jct.issn\n WHERE (\n (jct.esac_id = 'wiley2019deal' AND EXTRACT(YEAR FROM cr.issued) BETWEEN 2019 AND 2023) OR\n (jct.esac_id = 'wiley2024deal' AND EXTRACT(YEAR FROM cr.issued) BETWEEN 2024 AND 2025) OR\n (jct.esac_id = 'sn2021gac' AND EXTRACT(YEAR FROM cr.issued) BETWEEN 2021 AND 2023) OR\n (jct.esac_id = 'sn2020deal' AND EXTRACT(YEAR FROM cr.issued) BETWEEN 2020 AND 2023) OR\n (jct.esac_id = 'sn2024deal' AND EXTRACT(YEAR FROM cr.issued) BETWEEN 2024 AND 2025) OR\n (jct.esac_id = 'els2023deal' AND EXTRACT(YEAR FROM cr.issued) BETWEEN 2023 AND 2025) OR\n (jct.esac_id = 'degruy2022gac' AND EXTRACT(YEAR FROM cr.issued) = 2022) OR\n (jct.esac_id = 'degruy2023gac' AND EXTRACT(YEAR FROM cr.issued) BETWEEN 2023 AND 2024) OR\n (jct.esac_id = 'hogrefe2021gac' AND EXTRACT(YEAR FROM cr.issued) BETWEEN 2021 AND 2023) OR\n (jct.esac_id = 'hogrefe2024gac' AND EXTRACT(YEAR FROM cr.issued) BETWEEN 2024 AND 2025) OR\n (jct.esac_id = 'rsc2024tib' AND EXTRACT(YEAR FROM cr.issued) BETWEEN 2024 AND 2025) OR\n (jct.esac_id = 'opg2023tib' AND EXTRACT(YEAR FROM cr.issued) BETWEEN 2023 AND 2025) OR\n (jct.esac_id = 'ttp2024tib' AND EXTRACT(YEAR FROM cr.issued) BETWEEN 2024 AND 2025)\n )\n),\nfirst_author_data AS (\n SELECT\n UPPER(TRIM(w.doi)) AS doi,\n a.countries\n FROM `subugoe-collaborative.openalex_walden.works` w\n CROSS JOIN UNNEST(authorships) AS a\n WHERE a.author_position = 'first'\n AND 'DE' IN (\n SELECT UPPER(TRIM(country_code))\n FROM UNNEST(a.countries) AS country_code\n )\n AND EXISTS (\n SELECT 1\n FROM UNNEST(a.institutions) AS i\n JOIN `subugoe-collaborative.resources.oad_jct_inst` ji\n ON LOWER(i.ror) = LOWER(ji.ror_id)\n OR LOWER(i.display_name) = LOWER(ji.inst_name)\n WHERE i.display_name IS NOT NULL\n AND ji.inst_name IS NOT NULL\n )\n),\noad_ta_md AS (\n SELECT\n fp.doi,\n fp.cr_year,\n fp.issn_l,\n fp.cr_journal_title,\n fp.jn_esac_id,\n fp.cr_publisher,\n fp.has_abstract,\n ARRAY_LENGTH(fp.author) AS num_authors,\n (SELECT COUNT(1) FROM UNNEST(fp.author) AS authors WHERE authors.orcid IS NOT NULL) AS num_orcids,\n COUNT(DISTINCT CASE WHEN md_2.id IS NOT NULL THEN md_2.id ELSE md_1.name END) AS num_affiliations,\n COUNT(DISTINCT CASE WHEN LOWER(md_2.id_type) = 'ror' THEN md_2.id END) AS num_rors,\n ARRAY_LENGTH(fp.funder) AS num_funders,\n (SELECT COUNT(1) FROM UNNEST(fp.funder) AS funders, UNNEST(funders.id) WHERE LOWER(id_type) = \"doi\") AS num_funder_dois,\n MAX(CASE WHEN md_3.content_version IN ('vor', 'unspecified') THEN md_3.url END) AS license_url,\n CASE\n WHEN EXISTS (SELECT 1 FROM UNNEST(fp.link) WHERE intended_application = \"text-mining\") THEN 1\n ELSE 0\n END AS has_tdm,\n tt.doi AS tt_doi,\n tt.count_authors,\n tt.has_authors_id_orcid,\n tt.count_authors_id_orcid,\n tt.has_affiliations,\n tt.count_affiliations,\n tt.has_affiliations_id_ror,\n tt.count_affiliations_id_ror,\n tt.has_abstract AS tt_has_abstract,\n tt.has_funders,\n tt.count_funders,\n tt.has_funders_id_doi,\n tt.count_funders_id_doi\n FROM filtered_publications fp\n INNER JOIN first_author_data fa\n ON fp.doi = fa.doi\n LEFT JOIN UNNEST(fp.author) AS md_0\n LEFT JOIN UNNEST(md_0.affiliation) AS md_1\n LEFT JOIN UNNEST(md_1.id) AS md_2\n LEFT JOIN UNNEST(fp.license) AS md_3\n LEFT JOIN `sos-datasources.truthtables.crossref_truthtable_20260131` tt\n ON fp.doi = tt.doi\n GROUP BY\n fp.doi,\n tt.doi,\n fp.cr_year,\n fp.issn_l,\n fp.cr_journal_title,\n fp.jn_esac_id,\n fp.cr_publisher,\n fp.has_abstract,\n fp.author,\n fp.funder,\n fp.license,\n fp.link,\n tt.count_authors,\n tt.has_authors_id_orcid,\n tt.count_authors_id_orcid,\n tt.has_affiliations,\n tt.count_affiliations,\n tt.has_affiliations_id_ror,\n tt.count_affiliations_id_ror,\n tt.has_abstract,\n tt.has_funders,\n tt.count_funders,\n tt.has_funders_id_doi,\n tt.count_funders_id_doi\n)\n\nSELECT * FROM oad_ta_mdData cleaning and preparation involved several standardisation procedures: (1) harmonisation of ISSN-Ls for journals assigned to multiple ISSN-Ls, (2) consolidation of ESAC IDs for ISSN-Ls assigned to multiple ESAC IDs, in particular those resulting from publisher changes after the termination of the agreement, and (3) correction of errors in licence URLs. Journal-level standardisations were based on journal information from EZB and ZDB.
\nThe so-compiled data set I used for the analysis consists of 246,499 articles published between 2019 and 2025 and enabled by one of the 13 transformative agreements of interest.
\nI used the SOS Crossref truth table data to validate my approach and found strong alignment for all coverage metrics (ORCIDs, funding information, funder DOIs, open abstracts) except for ROR coverage. Specifically, the ROR coverage values from the SOS dataset were higher than those I computed, in some instances even considerably. A more detailed analysis of the data revealed that these differences are attributable to 355 articles for which the absolute number of ROR IDs counted in the SOS dataset exceeds the absolute number of affiliations. Inspecting a sample of 20 DOIs from this set of articles via the Crossref API revealed that when a ROR ID was present for a given affiliation, no additional name string (Crossref field name) was included in the metadata. The SQL query used to create the SOS dataset and calculate the metrics shows that the number of affiliations is determined based on the name string in the Crossref affiliation name field. This differs from the calculation approach applied here. If publishers do not provide a name string for each affiliation, additionally to the respective ROR IDs, this explains why, for these articles, the number of ROR IDs is assessed as higher by the SOS counting method than the number of actual affiliations.
\nThe contractual provisions analysed in D\u00f6rner (2026), with underlying data provided in D\u00f6rner (2025), form the baseline for the analysis presented here. Briefly, the agreements with de Gruyter, Optica, and Trans Tech Publications mandated CC BY licensing; 12 of the 13 agreements committed to metadata delivery to Crossref, with several explicitly referencing ORCIDs, ROR IDs, and funding information as metadata fields available to the publishers; and 12 agreements contained TDM provisions.
\nTable\u00a02 provides an overview of the article volume per agreement and publication year, aligned with the respective agreement terms, detailing the overall share of open access articles, the proportion published under a CC BY licence, and trends of CC BY shares across publication years.
\nFor the agreements with Optica and Trans Tech Publications, the proportion of open access articles and the proportion with a CC BY licence are identical, indicating full implementation of the CC provision. An overall slight increase in CC BY share can be observed for Optica, while Trans Tech Publications shows a decline. For de Gruyter, the CC BY share falls short of the overall open access share \u2014 the underlying data suggest this is due to some articles having been published under CC BY-NC-ND \u2014 though a general upward trend in CC BY adoption is visible.
\nFor the agreements with Elsevier, Wiley, and the Royal Society of Chemistry, where CC BY was required only as a default or preferred option rather than the sole permissible licence, the open access share consistently exceeds the CC BY share across all agreement terms, despite an overall increase in both. The Hogrefe agreements allow authors to choose from several CC licences without preference for CC BY, which is reflected in a lower CC BY share relative to the overall open access share, and a downward trend in CC BY for the 2024 agreement. For the Springer Nature agreements, the 2021 MPDL agreement shows identical open access and CC BY shares throughout its term, while the 2020 DEAL agreement shows a slightly higher overall open access share, with an upward trend in CC BY for both.
\nCrossref is critical, because many publishers use this DOI registration agency to share metadata openly. In addition to bibliographic data, efforts from initiatives such as the Initiative for Open Citations and the Initiative for Open Abstracts have led to an increase in the open availability of references and abstracts in Crossref (Van Eck and Waltman 2025).
\nTable\u00a032 provides an overview of the proportion of openly accessible metadata in Crossref for articles covered by the 13 transformative agreements, focusing on TDM support, authors\u2019 ORCIDs, author affiliations\u2019 ROR IDs, general funding information, funders\u2019 DOIs, and openly accessible abstracts.
\nFor the agreements with Elsevier, de Gruyter, and the 2021 MPDL Springer Nature agreement, TDM information has been persistently submitted to Crossref throughout the entire terms, consistent with contractual permissions for TDM for private use or research purposes. By contrast, no TDM information was delivered for the agreements with Hogrefe, the Royal Society of Chemistry, Trans Tech Publications, or Optica, despite non-commercial TDM being permissible under the first three and no TDM clause having been identified for Optica. For the Springer Nature DEAL agreements, TDM support is high throughout, reaching 100% in 2022. For Wiley, a strong decline is visible from 2023 onwards \u2014 corroborated by HOAD and the Crossref Participation Report for Wiley \u2014 though HOAD data for 2026 shows a recovery to over 90%, suggesting the decline may reflect a temporary technical issue rather than a strategic change.
\nORCID coverage ranges from 10.9% (Hogrefe for 2021) to 62.5% (Royal Society of Chemistry for 2025). Notably, the Royal Society of Chemistry agreement \u2014 which does not explicitly reference ORCIDs for Crossref delivery \u2014 shows the highest coverage. Despite most other agreements mentioning ORCIDs for author identification or metadata delivery, coverage remains mostly below 50%.
\nSubstantial disparities are visible across publishers. Optica is the only agreement with noticeable and consistent ROR coverage. Wiley shows minimal ROR coverage from 2022 onwards, and all other agreements show 0% \u2014 including the agreements with the Royal Society of Chemistry and Trans Tech Publications, which explicitly reference ROR IDs for institutional identification or reporting.
\nNo funding-related metadata was submitted to Crossref for the Hogrefe or Trans Tech Publications agreements, despite both containing funding information provisions. The Trans Tech Publications agreement, however, specified that funding information would only be recorded upon request by the authors. The Royal Society of Chemistry agreement \u2014 the only one without a funding information provision \u2014 nevertheless achieves among the highest funding information coverage, with DOIs recorded for all funders. De Gruyter shows low funding information coverage (maximum 7.4%) but with around 70% funder DOI coverage. Elsevier, which only committed to examining the feasibility of including funding information, shows coverage rising to 60% by 2025 with near-complete funder DOI coverage. The 2021 MPDL Springer Nature agreement shows declining funding information and funder DOI coverage, while the DEAL agreements show comparably higher funding information coverage but also a downward trend in funder DOI coverage. Wiley coverage of funding information oscillates around 50%, while funder DOI coverage is consistently above 90% and trending upward. Optica \u2014 the only agreement with an explicit contractual guarantee for funding information \u2014 shows the highest funding information coverage, though with a slight downward trend in funder DOI coverage.
\nAlmost no abstracts were delivered to Crossref for articles under the Elsevier agreement. Coverage is highest for Optica and Trans Tech Publications, followed by the Royal Society of Chemistry and Wiley, each exceeding 90%. None of the 13 agreements contained an explicit contractual provision for abstract delivery to Crossref.
\nThe analysis reveals substantial discrepancies between the contractual provisions of transformative agreements and their actual implementation in Crossref metadata, highlighting a gap in the operationalisation of open metadata commitments.
\nThe CC licence analysis demonstrates that contractual specificity directly correlates with implementation compliance. Agreements that explicitly mandated CC BY licensing (Optica, Trans Tech Publications, and de Gruyter) generally achieved higher compliance rates, though de Gruyter\u2019s implementation was imperfect due to residual CC BY-NC-ND usage. In contrast, agreements where CC BY was merely presented as a default or preferred option (Elsevier, Wiley, Royal Society of Chemistry) consistently showed lower CC BY adoption rates despite increasing overall open access volumes. This finding suggests that without explicit contractual mandates requiring CC BY as the sole permissible licence, publishers maintain flexibility to offer alternative licences, potentially undermining the transformative goals of these agreements.
\nThe near-absence of ROR coverage across most agreements is particularly striking. Even agreements that explicitly reference ROR IDs in the agreement text show 0% coverage, and virtually no ROR IDs were submitted for articles under the DEAL agreements \u2014 which account for the largest share of publication volume. This is problematic because ROR IDs provide persistent, unambiguous institutional identification essential for research assessment and funding attribution. Without them, bibliometric analyses must rely on error-prone string matching, introducing noise and increasing the manual curation burden. The methodological comparison with the SOS Crossref truth table further highlights the difficulty of measuring ROR coverage consistently when publishers submit ROR IDs without corresponding institutional name strings. The importance of ROR adoption is further underscored by Crossref\u2019s plans to retire the Funder Registry in favour of ROR (Portenoy 2026), making consistent ROR submission increasingly central to the Crossref metadata ecosystem.
\nIn line with de Jonge and Kramer (2026), the ORCID coverage findings suggest that publisher workflow integration and editorial systems might play a more decisive role in ORCID adoption than contractual language alone, as for instance, the Royal Society of Chemistry agreement \u2013 which does not explicitly reference ORCIDs for Crossref delivery \u2013 achieves the highest coverage regardless.
\nThe funding metadata findings illustrate a broader pattern: the presence of contractual provisions is no guarantee of implementation. The Trans Tech Publications agreement committed to recording funding information but only upon author request, and the complete absence of such metadata suggests either that authors rarely invoked this option, that the publisher lacked the necessary infrastructure, or that the provision was too vague to operationalise. Conversely, the Royal Society of Chemistry \u2014 without any funding metadata provision \u2014 achieved among the highest coverage, again pointing to publisher infrastructure and internal priorities as the more decisive factors. The declining funder DOI coverage for both Springer Nature agreement types, despite generally reasonable funding information coverage, further illustrates that even partial implementation can be inconsistent over time.
\nThe TDM findings similarly show that contractual permissions do not reliably translate into metadata delivery. The temporary decline in Wiley\u2019s TDM metadata after 2022, despite contractual permissions, likely reflects a technical issue given the subsequent recovery visible in HOAD\u2019s 2026 data, but it underscores the need for ongoing monitoring rather than reliance on contractual commitments alone.
\nTaken together, these findings demonstrate that vague or permissive contractual language on metadata tends to produce inconsistent outcomes. The cases of the Royal Society of Chemistry (high ORCID and funding coverage without explicit provisions) and Trans Tech Publications (zero funding coverage despite an explicit provision) illustrate the disconnect between contractual commitment and operational reality. Future agreements should specify exact metadata elements, required values, and implementation timelines, with measurable compliance indicators to enable systematic monitoring.
\nOne of the most compelling findings is the near-total absence of ROR ID coverage across most agreements. This underscores a clear opportunity for HOAD to expand its analytical scope by incorporating ROR coverage as a standard metric. Such an extension would be technically straightforward and would enable monitoring of ROR coverage across a wider set of agreements over time.
\nWhile this analysis is focused on 13 agreements with German consortia, the methodological approach could serve as a template for broader investigation. A distributed effort, connected to the Joint Task Force on Negotiating Openness of Publication Metadata between OA2020 (now OA Forward) and the Barcelona Declaration, has been started to analyse all openly available transformative agreements in the ESAC Registry of Open Publishing Agreements. The approach presented here could contribute to that initiative, providing empirical evidence to inform the task force\u2019s work on negotiating openness of publication metadata across publishers and nations.
\nR Code and processed data files for this data analysis are available on GitHub: https://github.com/subugoe/scholcomm_analytics/tree/main/posts/ta_coverage_analysis
\nData tables used for data retrieval are publicly available on Google BigQuery, as provided by the SUB G\u00f6ttingen: https://subugoe.github.io/scholcomm_analytics/data.html.
\nhttps://github.com/njahn82/jct_data\u21a9\ufe0e
Table\u00a03 reuses and extends the interactive visualization framework from the Hybrid Open Access Dashboard, including its reactable-based layout and filtering system. It adds ROR ID coverage as a new metric, which was not included in HOAD\u2019s original scope and uses a modified colour palette. Code adaptations were based on HOAD\u2019s open-source implementation on GitHub.\u21a9\ufe0e
![\"PKP](\"https://pkp.sfu.ca/wp-content/uploads/2026/05/PKP-AR-2025-WP-1024x576.jpg\")
PKP is proud to share its annual report for 2025, covering the period from April 1st, 2025 to March 31st, 2026.
\nAs we reflect on the past year, the 2025 Annual Report offers an opportunity to recognize the strength and dedication of the global community that continues to drive PKP forward. From expanding collaborations to advancing strategic priorities, this year marked meaningful progress on multiple fronts. The report also highlights important developments in PKP software, ongoing research initiatives, and community-informed improvements that continue to support more equitable, accessible, and sustainable open publishing worldwide.
\nThe report tells a story centered around our strategic priorities:
\nInside you will find:
\nThe full report is available now as a downloadable PDF:
\n\nWe invite you to read it, share it, and see how your engagement with PKP contributes to something much larger: a stronger, more inclusive ecosystem for scholarly publishing worldwide. You are part of the Public Knowledge Project!
\nPlease join us to celebrate at our upcoming Annual General Meeting on May 27th ![\"\ud83c\udf89\"](\"https://s.w.org/images/core/emoji/17.0.2/72x72/1f389.png\")
This report was made possible thanks to the contributions of many folks:
\nJuan Pablo Alperin, Alejandra Casas Ni\u00f1o de Rivera, Trevor Davis, Michael Felczak, Roger Gillis, Jeanette Hatherill, Mark Huskisson, Emily Hopkins, Teresa Lee, Patricia Mangahis, Urooj Nizami, Famira Racy, Stephanie Savage, Alec Smecher, Marco Tullney, Emma Uhl, Zoe Wake Hyde and John Willinsky.
\nSpecial thanks to Alexandre Cunha for the thoughtful design and layout that brings this year\u2019s story to life.
\nAnd of course, the broader community whose support, whether through voluntary work, financial contributions, or simply using our software, makes all of this possible.
\nThe post What we achieved together in 2025: PKP\u2019s Annual Report is here appeared first on Public Knowledge Project.
","doi":"https://doi.org/10.59350/rsqxd-xr461","funding_references":null,"guid":"https://pkp.sfu.ca/?p=19051","id":"0ec7f039-05d3-4f8b-a832-ba8c6484c701","image":"https://pkp.sfu.ca/wp-content/uploads/2026/05/PKP-AR-2025-WP-1024x576.jpg","images":[{"alt":"PKP community comes together at an annual sprint event, representing that there is no PKP without you!","height":"576","sizes":"(max-width: 1024px) 100vw, 1024px","src":"https://pkp.sfu.ca/wp-content/uploads/2026/05/PKP-AR-2025-WP-1024x576.jpg","srcset":"https://pkp.sfu.ca/wp-content/uploads/2026/05/PKP-AR-2025-WP-1024x576.jpg, https://pkp.sfu.ca/wp-content/uploads/2026/05/PKP-AR-2025-WP-300x169.jpg, https://pkp.sfu.ca/wp-content/uploads/2026/05/PKP-AR-2025-WP-768x432.jpg, https://pkp.sfu.ca/wp-content/uploads/2026/05/PKP-AR-2025-WP-1536x864.jpg, https://pkp.sfu.ca/wp-content/uploads/2026/05/PKP-AR-2025-WP.jpg","width":"1024"},{"alt":"\ud83c\udf89","src":"https://s.w.org/images/core/emoji/17.0.2/72x72/1f389.png"},{"src":"https://pkp.sfu.ca/wp-content/uploads/2026/05/PKP-AR-2025-WP-1024x576.jpg"}],"indexed":true,"indexed_at":1778789948,"language":"en","parent_doi":null,"published_at":1778788655,"reference":[],"registered_at":0,"relationships":[],"rid":"5cmc5-k3m91","status":"active","summary":"\n \n PKP is proud to share its annual report for 2025, covering the period from April 1st, 2025 to March 31st, 2026.\n \n\nAs we reflect on the past year, the 2025 Annual Report offers an opportunity to recognize the strength and dedication of the global community that continues to drive PKP forward. From expanding collaborations to advancing strategic priorities, this year marked meaningful progress on multiple fronts.","tags":["News","News For Developers","News For Hosted Clients","Annual General Meeting","Annual Report"],"title":"What we achieved together in 2025: PKP\u2019s Annual Report is here","updated_at":1778788656,"url":"https://pkp.sfu.ca/2026/05/14/pkp-2025-annual-report/","version":"v1"}},{"document":{"abstract":null,"archive_url":null,"authors":[{"contributor_roles":[],"name":"Bibliomagician Staff"}],"blog":{"archive_collection":null,"archive_host":null,"archive_prefix":null,"archive_timestamps":null,"authors":[{"name":"Bibliomagician Staff"}],"canonical_url":null,"category":"computerAndInformationSciences","community_id":"f5c1522e-c8de-4681-a317-e32ddb61b26a","created_at":1751825546.966006,"current_feed_url":null,"description":"Comment & practical guidance from the LIS-Bibliometrics community","doi":null,"doi_as_guid":false,"favicon":"https://rogue-scholar.org/api/communities/f5c1522e-c8de-4681-a317-e32ddb61b26a/logo","feed_format":"application/atom+xml","feed_url":"https://thebibliomagician.wordpress.com/feed/atom","filter":null,"funding":null,"generator":"WordPress.com","generator_raw":"WordPress.com","home_page_url":"https://thebibliomagician.wordpress.com/","id":"1068bf8a-6a20-4514-8a34-ff61a63d6d43","indexed":true,"issn":null,"language":"en","license":"https://creativecommons.org/licenses/by/4.0/legalcode","mastodon":null,"prefix":"10.59350","registered_at":0,"relative_url":null,"ror":null,"secure":true,"slug":"bibliomagician","status":"active","subfield":"3309","subfield_validated":null,"title":"The Bibliomagician","updated_at":1778833877.067921,"use_api":null,"use_mastodon":false,"user_id":null},"blog_name":"The Bibliomagician","blog_slug":"bibliomagician","content_html":"When: Thursday 24 September 2026
Where: Lancaster University, UK
The LIS Bibliometrics Conference 2026 invites researchers, practitioners, librarians, information professionals, and policymakers to explore the evolving intersections between AI, bibliometrics, scholarly communication, and research evaluation.
\nAs AI technologies increasingly influence scholarly communication, research assessment, and knowledge production, the conference aims to critically examine both the opportunities and challenges AI presents for bibliometric research and practice.
\nWe are pleased to announce the following keynote speakers:
\nThe conference welcomes submissions related to, but not limited to, the following themes:
\nWe welcome proposals for:
\nFor submission, please use the link below:
Oxford Abstracts
For enquiries, please contact:
lisbibliometricsconference2026@gmail.com
For further information please see the LIS Bibliometrics Conference Webpage and the Call for Contributions.
\n\nWe look forward to welcoming you to Lancaster University (or online) for the LIS Bibliometrics Conference 2026.
\n\nUnless it states other wise, the content of the Bibliomagician is licensed under a Creative Commons Attribution 4.0 International License.
","doi":"https://doi.org/10.59350/k5x2r-xsp29","funding_references":null,"guid":"http://thebibliomagician.wordpress.com/?p=5456","id":"91535190-6eba-4b69-8f8a-9ab578e6582b","image":null,"images":[],"indexed":true,"indexed_at":1778756619,"language":"en","parent_doi":null,"published_at":1778754859,"reference":[],"registered_at":0,"relationships":[],"rid":"68vmx-be074","status":"active","summary":"\n AI Meets Bibliometrics: Advancing Metrics for a Complex Research World\n\n\n When:\n\nThursday 24 September 2026\n\n Where:\n\nLancaster University, UK The LIS Bibliometrics Conference 2026 invites researchers, practitioners, librarians, information professionals, and policymakers to explore the evolving intersections between AI, bibliometrics, scholarly communication, and research evaluation.","tags":["LIS-Bibliometrics Conference","Conference","Lis-Bibliometrics Annual Event","LIS-Bibliometrics Conference 2026"],"title":"First Call for Papers \u2013 LIS Bibliometrics Conference 2026 \u2013 AI Meets Bibliometrics","updated_at":1778755480,"url":"https://thebibliomagician.wordpress.com/2026/05/14/first-call-for-papers-lis-bibliometrics-conference-2026-ai-meets-bibliometrics/","version":"v1"}}],"items":[{"abstract":"Wie gelingt es, Wissen in hochspezialisierten Organisationen langfristig zu sichern und zugleich im Alltag nutzbar zu machen? Mit dieser Frage besch\u00e4ftigte sich ein Praxisprojekt im Masterstudiengang Bibliotheks- und Informationswissenschaft (MALIS) an der TH K\u00f6ln.","archive_url":null,"authors":[{"contributor_roles":[],"family":"Roden","given":"Bettina","url":"https://orcid.org/0009-0005-6384-5953"}],"blog":{"archive_collection":null,"archive_host":null,"archive_prefix":null,"archive_timestamps":null,"authors":null,"canonical_url":null,"category":"computerAndInformationSciences","community_id":"adb906d0-0e1c-4d03-aa84-bacf2ea8d57d","created_at":1754944681.669707,"current_feed_url":null,"description":"Folgen Sie den neuesten Praxisprojekten aus dem MALIS-Studiengang","doi":null,"doi_as_guid":false,"favicon":null,"feed_format":"application/atom+xml","feed_url":"https://malisprojekte.web.th-koeln.de/wordpress/feed/atom","filter":"category:MALIS","funding":null,"generator":"WordPress","generator_raw":"WordPress 6.8.2","home_page_url":"https://malisprojekte.web.th-koeln.de/wordpress/","id":"041b9d13-2fc5-44e1-8705-eaf2b6ea3c70","indexed":true,"issn":null,"language":"de","license":"https://creativecommons.org/licenses/by/4.0/legalcode","mastodon":null,"prefix":"10.59350","registered_at":0,"relative_url":null,"ror":null,"secure":true,"slug":"malisprojekte","status":"active","subfield":"1802","subfield_validated":null,"title":"MALIS-Projekteblog","updated_at":1778834938.3869,"use_api":false,"use_mastodon":false,"user_id":null},"blog_name":"MALIS-Projekteblog","blog_slug":"malisprojekte","content_html":"Wie gelingt es, Wissen in hochspezialisierten Organisationen langfristig zu sichern und zugleich im Alltag nutzbar zu machen? Mit dieser Frage besch\u00e4ftigte sich ein Praxisprojekt im Masterstudiengang Bibliotheks- und Informationswissenschaft (MALIS) an der TH K\u00f6ln. Im Fokus standen die Organisationshandb\u00fccher (OrgHandb\u00fccher) der Spezialbibliotheken der Bundeswehr \u2013 ein traditionell etabliertes, in der Praxis jedoch zunehmend vernachl\u00e4ssigtes Instrument.
\n\n
Ausgangslage: Ein Werkzeug verliert an Relevanz
\nSeit Mitte der 1990er-Jahre sind OrgHandb\u00fccher f\u00fcr alle Spezialbibliotheken der Bundeswehr verpflichtend. Sie sollen Prozesse dokumentieren, Zust\u00e4ndigkeiten kl\u00e4ren und Erfahrungswissen sichern. Doch viele Handb\u00fccher waren seit Jahren nicht mehr aktualisiert, der Zugriff gestaltete sich schwierig und kollaboratives Arbeiten war nicht vorgesehen.
Stattdessen wichen Bibliotheken auf eigene L\u00f6sungen wie SharePoint oder Wikis aus. Das Ergebnis: eine fragmentierte Wissenslandschaft \u2013 mit dem Risiko, dass wertvolles Erfahrungswissen durch Personalwechsel verloren geht.
\nMethodisches Vorgehen: Datenbasis schaffen
\nUm die tats\u00e4chliche Nutzung der OrgHandb\u00fccher zu erfassen, setzte das Projekt auf einen Methodenmix:
Die R\u00fccklaufquote lag bei \u00fcber 70 % \u2013 ein starkes Signal f\u00fcr das Interesse am Thema. Die Ergebnisse waren jedoch ern\u00fcchternd: Zwei Drittel der Befragten nutzten das OrgHandbuch \u00fcberhaupt nicht. Gr\u00fcnde waren fehlende Einweisung, veraltete Inhalte und eine un\u00fcbersichtliche Struktur. Wenn es genutzt wurde, diente es vor allem als Leitfaden oder beim Onboarding neuer Kolleginnen und Kollegen.
\nL\u00f6sung: Ein digitales OrgHandbuch in Confluence
\nAuf Basis dieser Erkenntnisse entwickelte das Projekt ein exemplarisches OrgHandbuch in Confluence, der Wiki-Plattform der Bundeswehr.
Die wichtigsten Merkmale:
\nDamit wird das OrgHandbuch von einem statischen Dokument zu einem lebendigen, kollaborativen Wissensinstrument weiterentwickelt.
\nAusblick: Verstetigung als Schl\u00fcssel
\nDie technische Umsetzung war ein erster Schritt \u2013 entscheidend wird die kontinuierliche Pflege und Integration in den Arbeitsalltag. Nur so kann das OrgHandbuch langfristig Akzeptanz finden.
Dar\u00fcber hinaus zeigt das Projekt: Moderne Wissensmanagement-Ans\u00e4tze lassen sich auch in hochstrukturierten Organisationen wie der Bundeswehr erfolgreich einf\u00fchren. Die \u00dcbertragung auf andere Institutionen liegt nahe \u2013 \u00fcberall dort, wo Wissen nicht an Personen gebunden bleiben darf, sondern institutionell gesichert werden muss.
\nFazit
\nDas MALIS-Praxisprojekt verbindet wissenschaftliche Analyse mit praxisnaher Umsetzung und zeigt:
\u00a0
\nProjektzeitraum: Februar 2025 \u2013 August 2025
\nProjektbetreuer*in: Prof. Dr. Simone F\u00fchles-Ubach
Dieser Artikel steht unter der Lizenz CC BY.
","doi":"https://doi.org/10.59350/q5sft-0wj68","funding_references":null,"guid":"https://malisprojekte.web.th-koeln.de/wordpress/?p=2470","id":"b926da11-7cc0-4f9e-b2e4-b80949af0e28","image":"https://i.ibb.co/7dy89Wy4/Roden-Stute-Bild.jpg","images":[{"height":"1536","src":"https://i.ibb.co/7dy89Wy4/Roden-Stute-Bild.jpg","width":"1024"},{"alt":"Abbildung 1: Titelbild (Quelle: ChatGPT, Version vom 10. August 2025, OpenAI, erstellt von Bettina Roden, chatgpt.com)","src":"https://i.ibb.co/7dy89Wy4/Roden-Stute-Bild.jpg"}],"indexed":true,"indexed_at":1778866903,"language":"de","parent_doi":null,"published_at":1778864707,"reference":[],"registered_at":0,"relationships":[],"rid":"rfxry-0cp34","status":"active","summary":"\n Wie gelingt es, Wissen in hochspezialisierten Organisationen langfristig zu sichern und zugleich im Alltag nutzbar zu machen? Mit dieser Frage besch\u00e4ftigte sich ein Praxisprojekt im Masterstudiengang Bibliotheks- und Informationswissenschaft (MALIS) an der TH K\u00f6ln.\n","tags":["Confluence","Digitale Transformation","Erfahrungswissen","Kollaboration","MALIS"],"title":"Wissensplattform statt Handbuch: Organisationshandb\u00fccher als lebendiges Wissensinstrument neu gedacht","updated_at":1778864707,"url":"https://malisprojekte.web.th-koeln.de/wordpress/wissensplattform-statt-handbuch-organisationshandbuecher-als-lebendiges-wissensinstrument-neu-gedacht/","version":"v1"},{"abstract":null,"archive_url":null,"authors":[{"affiliation":[{"id":"https://ror.org/05167c961","name":"Western University of Health Sciences"}],"contributor_roles":[],"family":"Wedel","given":"Matt","url":"https://orcid.org/0000-0001-6082-3103"}],"blog":{"archive_collection":22153,"archive_host":null,"archive_prefix":"https://wayback.archive-it.org/22153/20231105213934/","archive_timestamps":null,"authors":[{"name":"Mike Taylor"}],"canonical_url":null,"category":"earthAndRelatedEnvironmentalSciences","community_id":"0e13541f-417e-46c0-a859-65927249df72","created_at":1675209600,"current_feed_url":null,"description":"SV-POW! ... All sauropod vertebrae, except when we're talking about Open Access. ISSN 3033-3695","doi":null,"doi_as_guid":false,"favicon":null,"feed_format":"application/atom+xml","feed_url":"https://svpow.com/feed/atom/","filter":null,"funding":null,"generator":"WordPress.com","generator_raw":"WordPress.com","home_page_url":"https://svpow.com","id":"c6cbbd2e-4675-4680-8a3f-784388009821","indexed":false,"issn":"3033-3695","language":"en","license":"https://creativecommons.org/licenses/by/4.0/legalcode","mastodon":null,"prefix":"10.59350","registered_at":1729882329,"relative_url":null,"ror":null,"secure":true,"slug":"svpow","status":"active","subfield":"1911","subfield_validated":true,"title":"Sauropod Vertebra Picture of the Week","updated_at":1778835620.071768,"use_api":true,"use_mastodon":false,"user_id":"04d03585-c8bb-40f2-9619-5076a5e0aed2"},"blog_name":"Sauropod Vertebra Picture of the Week","blog_slug":"svpow","content_html":"An imposing view of a juvenile Utahceratops.
As threatened, I was in Oklahoma at the tail end of last week and over the weekend, mostly to give talks. My Friday evening public lecture was on horned dinosaurs, and it was tied in with the launch of a temporary exhibit called “Bizarre Headgear: Ceratopsians and the Evolution of Extraordinary Skulls”. I’ll cover the talks in another post; this one is about that exhibit.
\n
From the museum’s central atrium, there are a couple of passages into the special exhibition gallery that houses “Bizarre Headgear”. My preferred way in is the second doorway, farther from the front of the museum, which puts you face-to-face with pterosaurs and hell pigs. This sets up the basic division of the room: mostly Mesozoic and mostly dinos to the left, mostly Cenozoic and mostly mammals to the right (with a few exceptions, like the Synthetoceras visible on the back wall).
\n
From there, turn left and you’ll see horned dinosaurs and many other interesting critters. A lot of them.
\n
Turn right and you’ll see a lot more non-dinosaurs, mostly extinct and extant mammals with a smattering of non-mammals.
\n
I was there to yap about horned dinos, and the exhibit does not slack in this department, starting with this charming side-by-side skeletal reconstruction and lift restoration of Psittacosaurus. The sculpture is by Shane Foulkes, and it looks like a real animal.
\n
A highlight of the exhibit for me is this case of early ceratopsians. From right to left (far to near in this photo) are cast skulls of Liaoceratops, Auroraceratops, Archaeoceratops, and Protoceratops. These are little Aquilops-alikes from Asia. Back in 2014, Farke et al. got this topology:
\nPsittacosaurus (Liaoceratops (Aquilops (Auroraceratops (Archaeoceratops + all more derived ceratopsians))))
\nand in 2024, Tanaka recovered these relationships for those same taxa (I’m dropping many others here):
\nPsittacosaurus (Liaoceratops (Archaeoceratops ((Aquilops + Auroraceratops) + (all more derived ceratopsians))))
\nI’d never seen so many of these adorable little weirdos in one place. Heck, I’d never even seen casts of Liaoceratops and Auroraceratops in person. So it was nice to get acquainted with the aunts and cousins of Aquilops.
\n
The ceratopsian show continues with a pair of Protoceratops skeletons, followed by skulls of Zuniceratops, Diabloceratops, Kosmoceratops, and a cool Utahceratops with some soft tissue reconstructed. There’s also a mounted skeleton of Torosaurus, and the juvenile Utahceratops shown at the top of the post. This diversity of critters from across the ceratopsian tree was clutch when I helped lead a student tour on Monday. And it was nice to see a lot of animals that weren’t described when I was growing up, and that the average museum-goer might be less familiar with — Diabloceratops instead of Centrosaurus or Styracosaurus, Kosmoceratops and Utahceratops in place of Triceratops and Chasmosaurus.
\n
The exhibit has a lot more than just skulls and skeletons. There are loads of sculptures, both life-sized fleshed-out heads and miniatures showing the whole animal, like this Pachyrhinosaurus. And lots of wall art. I believe all of the sculptures are by Shane Foulkes (and apologies if I missed anyone else). Most of the paintings are by Andrey Atuchin, but there is at least one Mark Hallett piece in the exhibit: Synthetoceras being menaced by an amphicyonid ‘bear-dog’.
\n
The mostly-mammals, mostly-extant side of the exhibit is equally impressive. I’m including fewer photos from that side, because this is already a long post, but I counted at least 65 skulls of non-dinosaurs, including 3 proboscideans and 5 cetaceans. Invertebrates even get a look in, with some of the more baroquely-horned beetles. I nipped into the exhibit while it was still being set up to get some photos for my talk, like this awesome array of African bovids. All of these non-ceratopsians are there to put the evolution of bizarre headgear in dinosaurs into context, and to show that dinos were not incomprehensible monsters, but animals whose anatomy and ecology we can understand, or at least make pretty good inferences about. The signage is uniformly excellent — discreet, informative, and attractively laid out, with a consistent arrangement and color palette.
\nAs long as we’re keeping score, I counted 5 mounted dinosaur skeletons, and 16 other dinosaur skulls. This exhibit is stacked. Every single person I talked to about it, including other paleontologists, staff, security guards, and museum visitors, volunteered something along the lines of “Holy cow, that is a lot of amazing stuff.” The sheer density and diversity of material on display has a qualitative impact, which gave me the feeling of walking through a cabinet of curiosities the size of a basketball court. I think it’s the most impressive temporary exhibit I’ve ever seen, and by far my favorite.
\n
Here’s another thing I’d never seen in person: a cast skull of a hammerhead shark. Just incredible. As the artist and author Ricardo Delgado, creator of the Age of Reptiles comics, often says, “Nature is the best creature designer.”
\n
The “Bizarre Headgear” exhibit is the brainchild of Rob Gaston, shown here with some bespectacled doofus for scale. Rob and the crew at Gaston Design do great work — I’ve got a couple of their casts right here in my home office as I type. Because I got to go behind the scenes while they were setting up, I got to say hi to Rob and congratulate him on such a fantastic exhibit. If you’re within striking distance of Norman, Oklahoma, between now and late August, go see it. It’s included with the extremely reasonable museum admission (max $12 for non-senior adults, even less expensive for everyone else), and hey, you get to see the whole rest of the museum, too. See the museum website for details.
\n
Parting shot: some utter genius in the museum gift shop got into the spirit of things by putting a Triceratops mask on this stuffed polar bear. I love this unreasonably and it’s only because of carry-on luggage limitations that I didn’t bring it home with me. Maybe you will succeed where I fell short.
\nI’ll have more to say about my trip in another post (Sauroposeidon!), so here I’ll just say a quick thanks to the museum director, Dr. Janet Braun, for the kind invitation to come speak; to Assistant Director Laura Moon and all the staff for making my visit successful and enjoyable; and to vert paleo curator Dr. Jacqueline Lungmus and the VP staff and volunteers for letting me come play in their sandbox. It was a heck of a trip, and you’ll be able to read more about it real soon.
\n\n
Was bedeutet es, eine historische Sammlung zu erschlie\u00dfen? Was macht man da? Diese Fragen waren eine Leitlinie im Rahmen meines MALIS-Projekts und um sie zu beantworten, wurde die historische Sammlung von Georg Andreas und Gerlinde Bachem gew\u00e4hlt, die seit 2012 in der USB K\u00f6ln auf ihre Erschlie\u00dfung wartet.
\n\n
Die Sammlung Bachem ist ungew\u00f6hnlich, denn: Es gibt keinen inhaltlichen Zusammenhang! Herr Bachem verfolgte beim Sammeln zwei Ziele: Erstens seltene und besondere B\u00fccher zu erwerben, zweitens aus jedem Jahr seit Beginn des Buchdrucks mindestens ein Exemplar zu besitzen. Das bedeutet, es geht um kulturhistorisch wertvolle, teils einzigartige Werke.
\nWie geht man also vor, wenn eine Erschlie\u00dfung ansteht? Zun\u00e4chst muss das Vorgehen geplant werden. Im Rahmen des Projekts wurde entschieden, dass der Fokus auf den Kleinformaten (unter 30cm) liegen soll, da dies zeitlich als realistisch angesehen werden konnte. Es folgten Entscheidungen \u00fcber die zuk\u00fcnftige Aufstellung und das Signaturensystem. Dann ging die konkrete Arbeit los!
\nKatalogisierung:
\nHistorische Drucke sind anspruchsvoll zu katalogisieren, sie besitzen Eigenheiten, die moderne Drucke nicht kennen. Da sind z.B. typographische Besonderheiten wie Ligaturen, Virgel, Abbreviaturen oder alte lateinische Abk\u00fcrzungen. Dann ist die Unterscheidung von verschiedenen Ausgaben teils schwierig, ebenso wie die Datenlage im Verbundkatalog. Des Weiteren sind zwar Kenntnisse im Regelwerk RDA notwendig, aber vor allem auch noch RAK-WB und es ist notwendig, sich mit der Erfassungsgeschichte und den Eigenheiten der Verbundkatalogisierung zu besch\u00e4ftigen. Die Katalogisierung eines historischen Drucks kann zwischen 15 Minuten und 3 Stunden dauern, das h\u00e4ngt von der Komplexit\u00e4t des Buchs ab. Insgesamt konnten 314 Werke katalogisiert werden!
Provenienzverzeichnung:
\nProvenienz bedeutet \u201eHerkunft\u201c, das hei\u00dft, es werden Vorbesitzer (Personen oder K\u00f6rperschaften) nachgewiesen, um die Geschichte des Buches nachzuweisen. Insgesamt konnten 179 Provenienzen erfasst werden, darunter au\u00dfergew\u00f6hnliche. So konnte ich beispielsweise einige B\u00fccher adligen oder k\u00f6niglichen Privatbibliotheken zuordnen: K\u00f6nigin Maria Theresia von Frankreich, K\u00f6nig Ernst August von Hannover, Liselotte von der Pfalz, Maria Theresia von \u00d6sterreich, K\u00f6nig Ludwig XIII. von Frankreich sowie K\u00f6nig Ludwig XV. von Frankreich
Technische und konservatorische Buchbearbeitung:
\nDie Reihenfolge ist: Reinigung, Stempelung, Signaturschilder kleben, Reparaturen durchf\u00fchren, ggf. Restaurierungsma\u00dfnahmen einleiten. Danach kann die Aufstellung im Magazin erfolgen und die Erschlie\u00dfung ist in der USB beendet.
Was ist geschafft?
\nDie Kleinformate wurden erfolgreich erschlossen, d.h. sie sind zug\u00e4nglich und national recherchierbar! Insgesamt demonstriert die Bearbeitung der Sammlung Bachems exemplarisch, wie gezielte Erschlie\u00dfung, Sichtbarmachung und konservatorische Ma\u00dfnahmen den Wert historischer Sammlungen f\u00fcr Forschung und \u00d6ffentlichkeit signifikant erh\u00f6hen k\u00f6nnen.
\u00a0
\nProjektzeitraum: April 2025 \u2013 August 2025
\nProjektbetreuer*in: Prof. Dr. Siegfried Schmidt
Dieser Artikel steht unter der Lizenz CC BY.
","doi":"https://doi.org/10.59350/76rg6-79w64","funding_references":null,"guid":"https://malisprojekte.web.th-koeln.de/wordpress/?p=2452","id":"f60f9107-e4f8-4a70-98b9-ec6176dd3df8","image":"https://i.ibb.co/xSjZNkvC/Mueller-Bild1.jpg","images":[{"height":"875","src":"https://i.ibb.co/xSjZNkvC/Mueller-Bild1.jpg","width":"1166"},{"height":"880","src":"https://i.ibb.co/9MwWLPb/Mueller-Bild2.jpg","width":"1173"},{"alt":"Abbildung 1: Titelbild (Quelle: Privat, Lucia Anna M\u00fcller)","src":"https://i.ibb.co/xSjZNkvC/Mueller-Bild1.jpg"},{"alt":"Abbildung 2 (Quelle: Privat, Lucia Anna M\u00fcller)","src":"https://i.ibb.co/9MwWLPb/Mueller-Bild2.jpg"}],"indexed":true,"indexed_at":1778864488,"language":"de","parent_doi":null,"published_at":1778862490,"reference":[],"registered_at":0,"relationships":[],"rid":"raz6q-tkj77","status":"active","summary":"\n Was bedeutet es, eine historische Sammlung zu erschlie\u00dfen? Was macht man da? Diese Fragen waren eine Leitlinie im Rahmen meines MALIS-Projekts und um sie zu beantworten, wurde die historische Sammlung von Georg Andreas und Gerlinde Bachem gew\u00e4hlt, die seit 2012 in der USB K\u00f6ln auf ihre Erschlie\u00dfung wartet.\n\nDie Sammlung Bachem ist ungew\u00f6hnlich, denn: Es gibt keinen inhaltlichen Zusammenhang!","tags":["Bibliophilie","Erschlie\u00dfung","Historische Drucke","Kulturgut","MALIS"],"title":"Erfassung und Erschlie\u00dfung einer historischen Privatsammlung am Beispiel der Sammlung Georg Andreas und Gerlinde Bachem in der USB K\u00f6ln","updated_at":1778862490,"url":"https://malisprojekte.web.th-koeln.de/wordpress/erfassung-und-erschliessung-einer-historischen-privatsammlung-am-beispiel-der-sammlung-georg-andreas-und-gerlinde-bachem-in-der-usb-koeln/","version":"v1"},{"abstract":"On 8 May 2026, during the Graduation Ceremony of the Executive Masters in Management of Research Infrastructures (EMMRI), OpenCitations was awarded the Certificate of Excellence in Research Infrastructure Leadership.","archive_url":null,"authors":[{"affiliation":[{"id":"https://ror.org/01111rn36","name":"University of Bologna"}],"contributor_roles":[],"family":"Di Giambattista","given":"Chiara","url":"https://orcid.org/0000-0001-8665-095X"}],"blog":{"archive_collection":22125,"archive_host":null,"archive_prefix":"https://wayback.archive-it.org/22125/20231105110316/","archive_timestamps":[20231105110316,20240505181542,20241105110224,20250505110302],"authors":[{"name":"OpenCitations Team"}],"canonical_url":null,"category":"otherSocialSciences","community_id":"84fbaf60-5174-43f6-976e-5f0b6f1da9a1","created_at":1681862400,"current_feed_url":null,"description":"The blog of the OpenCitations Infrastructure","doi":null,"doi_as_guid":false,"favicon":"https://rogue-scholar.org/api/communities/c8efeda5-cd52-472d-9537-6915b9c62e34/logo","feed_format":"application/atom+xml","feed_url":"https://opencitations.hypotheses.org/feed/atom/","filter":null,"funding":null,"generator":"WordPress","generator_raw":"WordPress 6.6.2","home_page_url":"https://opencitations.hypotheses.org","id":"1e1a0f67-e922-4977-b5b8-c5ec19c2f43a","indexed":false,"issn":null,"language":"en","license":"https://creativecommons.org/licenses/by/4.0/legalcode","mastodon":"https://@scicomm.xyz/@opencitations","prefix":"10.59350","registered_at":1727299025,"relative_url":null,"ror":"https://ror.org/00wb4mk85","secure":true,"slug":"opencitations","status":"active","subfield":"1802","subfield_validated":null,"title":"OpenCitations blog","updated_at":1778835160.035895,"use_api":true,"use_mastodon":true,"user_id":"13119f55-bbed-46a9-9338-80103d8c6b05"},"blog_name":"OpenCitations blog","blog_slug":"opencitations","content_html":"On 8 May 2026, during the Graduation Ceremony of the Executive Masters in Management of Research Infrastructures (EMMRI), OpenCitations was awarded the Certificate of Excellence in Research Infrastructure Leadership. This recognition was achieved through the participation of members of the OpenCitations team in the 2024\u20132026 class of the Excellence Programme for Research Infrastructures, an initiative designed to support research infrastructures in developing organisational competencies across their teams, fostering sustainable and effective leadership models.
\nThe OpenCitations participants included Director Silvio Peroni, CTO Ivan Heibi, Research Manager Claudio Fabbri, Systems Administrator Mario Petrella, and Communications Director Chiara Di Giambattista, who took part in the 11 modules of the programme. Across these modules, OpenCitations built a network of relationships and exchanges with other selected research infrastructures and strengthened its competencies in the following areas:
\nThe graduation ceremony, the final step of this two-year journey, brought together faculty members and representatives from the research infrastructures. Among the reflections shared during the event, one phrase captured the spirit of the programme: \u201cLeadership is a form of enthusiasm\u201d. Indeed, this experience made it clear that such enthusiasm was widely shared among participants, including colleagues from different infrastructures worldwide. The exchange of perspectives promoted throughout each module of the programme fostered a more grounded and pragmatic understanding of how research infrastructures evolve and collaborate in an international environment.
\nWe would like to thank the EMMRI team, in particular the Director Professor Marialuisa Lavritrano, and Professor Enrico Guarini and Drs. Laura Farina, for selecting OpenCitations for this programme and for developing an initiative that is both well-structured and internationally relevant, hosted at the University of Milano-Bicocca.
\nAt the end of this programme, OpenCitations carries forward the responsibility to build on the stimulating discussions and insights gained throughout the course. We will work to further develop the competencies acquired and reflect on both the strengths and limitations identified through this exchange, to continue supporting the long-term sustainability and development of OpenCitations as an open scholarly infrastructure
\n","doi":"https://doi.org/10.59350/ds8e6-rt906","funding_references":null,"guid":"https://opencitations.hypotheses.org/?p=4334","id":"d9ccf763-4b0b-40e3-abc9-56a114b8d65f","image":"https://opencitations.hypotheses.org/files/2026/05/Scuola-media-1080-x-1350-px-1500-x-900-px-1500-x-900-px-1.png","images":[],"indexed":true,"indexed_at":1778874014,"language":"en","parent_doi":null,"published_at":1778840346,"reference":[],"registered_at":0,"relationships":[],"rid":"em2y4-b1n13","status":"active","summary":"On 8 May 2026, during the Graduation Ceremony of the Executive Masters in Management of Research Infrastructures (EMMRI), OpenCitations was awarded the Certificate of Excellence in Research Infrastructure Leadership.","tags":["Governance And Finances","Non Class\u00e9","Open Access","Open Scholarship","Open Science"],"title":"OpenCitations has been awarded the Certificate of Excellence in Research Infrastructure Leadership","updated_at":1778840346,"url":"https://opencitations.hypotheses.org/4334","version":"v1"},{"abstract":null,"archive_url":null,"authors":[{"contributor_roles":[],"family":"Turner","given":"Stephen D."}],"blog":{"archive_collection":null,"archive_host":null,"archive_prefix":null,"archive_timestamps":null,"authors":[{"name":"Stephen Turner"}],"canonical_url":null,"category":"biologicalSciences","community_id":"382941a7-2ffa-41df-8bbb-5f772188517f","created_at":1734172613,"current_feed_url":null,"description":"A practicing data scientist's take on AI, genomics, biosecurity, and the ways AI is reshaping how science gets done. Weekly updates from the field. Occasional notes on programming.","doi":null,"doi_as_guid":false,"favicon":null,"feed_format":"application/rss+xml","feed_url":"https://blog.stephenturner.us/feed","filter":null,"funding":null,"generator":"Substack","generator_raw":"Substack","home_page_url":"https://blog.stephenturner.us/","id":"bffe125c-3dfa-4f25-998f-e62878677c7c","indexed":true,"issn":null,"language":"en","license":"https://creativecommons.org/licenses/by/4.0/legalcode","mastodon":"https://bsky.app/profile/stephenturner.us","prefix":"10.59350","registered_at":0,"relative_url":null,"ror":null,"secure":true,"slug":"stephenturner","status":"active","subfield":"1311","subfield_validated":true,"title":"Paired Ends","updated_at":1778835598.79035,"use_api":null,"use_mastodon":false,"user_id":"ae63ef98-7475-4cc1-b3eb-244d5e096f0f"},"blog_name":"Paired Ends","blog_slug":"stephenturner","content_html":"AI-heavy week, but the throughline is what happens when the platforms and infrastructure under our work start to rot, from GitHub to preprint servers to peer-reviewed literature.
The GitHub ship is sinking, the lifeboats leak
Vibe-coded into a corner
The Lancet sues the AI that cites The Lancet
Hallucinated citations, now with a denominator
arXiv takes the banhammer out for AI-written work
David Bushell wrote a vivid eulogy for GitHub (\u201cGitHub used to be cool and now it\u2019s a lame slop graveyard\u201d), and a few days later GitLab\u2019s new CEO Bill Staples published \u201cGitLab Act 2\u201d, which to me sounds like a flailing pivot toward agentic everything.
Bushell\u2019s case against GitHub is part vibes but contains an uptime chart that does look bad after the Microsoft acquisition.
When I posted this chart on Bluesky earlier this week, I had a few folks pointing to the deluge of AI coding agents and automated pull requests as the reason. But if you look closely at the chart, this service degradation long predated AI coding agents and ChatGPT itself.
But: Git is not GitHub. He recommends Codeberg (running Forgejo) as the safe alternative, with self-hosted Forgejo as the power-user option. He also recommended GitLab, then added an edit:
oh dear, they\u2019ve contracted the rot
The Staples letter is what he means. GitLab is reorganizing into roughly 60 smaller R&D teams, flattening management, exiting up to 30% of its country footprint, and (oh my): \u201crewiring internal processes with AI agents, automating the reviews, approvals, and handoffs to speed us up.\u201d The strategic thesis is that \u201csoftware will be built by machines, directed by people.\u201d
The blog post calls git \u201cdesigned for human-rate commits\u201d and pitches a \u201cgenerational rebuild of the underlying infrastructure to handle agent-rate work as the default.\u201d
I\u2019m not an agent power user, and maybe I\u2019ll retract my thoughts on this in a few months. But, if your agents are opening so many merge requests that git itself is the bottleneck, the answer is probably fewer agents.
It\u2019ll be interesting to see if this translates into actual migrations. Pretty much all of computational biology / bioinformatics lives on GitHub: software packages, snakemake/nf-core workflows, Bioconductor packages, lab repos, course materials. Don\u2019t forget about other infrastructure as well: GitHub Pages (e.g. pkgdown pages for R packages), CI w/ GitHub Actions, GitHub container registry, etc. Moving the social graph (issues, PRs, stars, discoverability) is enormous work, and I don\u2019t know if Codeberg could absorb the load. I can\u2019t imagine what a realistic and practical exit plan would look like.
I\u2019m not usually one to give air to the anti-AI hype. Most of what I read here is boring and irritating. However, Shubham\u2019s \u201cI\u2019m going back to writing code by hand\u201d is good. He spent ~30 weekends and >200 commits building k10s, a GPU-aware Kubernetes TUI, entirely through Claude. Then he sat down and read model.go for the first time. It was 1690 lines. He\u2019s archiving it and starting over in Rust.
AI builds features, not architecture; every prompt landed cleanly, the cumulative effect was a god object. Vibe-coding \u201cmade everything feel cheap\u201d so scope crept from a niche GPU tool to a generic k9s clone. My favorite line:
like \u201cem-dash\u201d is to ai writing, \u201cgod-object\u201d is to ai coding
His proposed remedy is putting architectural invariants into CLAUDE.md or AGENTS.md so the model sees them on every invocation.
See also the HN thread. One comment stuck out: \u201cCan\u2019t you just ask AI to break up large files into smaller ones and also explain how the code works so you can understand it?\u201d If the AI got you into the god-object hole, asking the AI to refactor its way out is probably not the move.
I was at a week-long innovation lab around AI and drug discovery this weekend. A thought in the back of my head all week was something I keep coming back to in my thinking in computational biology: the bottleneck in agentic science is evaluation, not generation. You can prompt your way to a working pipeline in a weekend. You can\u2019t prompt your way to knowing it\u2019s right.
Elsevier has joined a class-action lawsuit against Meta alleging Meta reproduced copyrighted works to train Llama. As Nature notes, this is the first AI copyright suit from major publishing houses. Elsevier publishes Cell and The Lancet, so a fair chunk of the biomedical literature is now formally a plaintiff against a frontier lab.
The lawsuit alleges Meta used Common Crawl and also that Meta downloaded and torrented works from LibGen and Sci-Hub. Meta\u2019s defense is the usual one: training is transformative use. US judges in two 2025 rulings reportedly distinguished between training (often transformative) and acquisition (the act of downloading copyrighted material), which is where torrenting from Sci-Hub is going to be a problem for Meta regardless of how fair use resolves.
Irony is dead.
Elsevier sells access to research funded by taxpayers and donated by authors who weren\u2019t paid for the manuscript and often paid Elsevier APCs to make it open. Meta scraped some of that content, allegedly via Sci-Hub, which exists precisely because Elsevier\u2019s access model is widely considered indefensible. Now Elsevier wants damages on behalf of authors who didn\u2019t get paid the first time around either. The most coherent position is probably that Meta should have paid for licensed access and that Elsevier should not be the entity collecting the check, but that isn\u2019t on offer.
If this case establishes that scraping paywalled academic content is infringement, the practical effect on open-science-trained models could be larger than the effect on Llama. Llama already exists. A future model that wants to train on biomedical literature now has a clearer legal target on its back.
A new Lancet correspondence by Topaz et al. audited 2.5 million biomedical papers for fabricated references, and the numbers are bad. The accompanying Comment by Bauchner and Rivara argues that any published paper with a fabricated reference should be retracted, which is a reasonable position that approximately no one will implement.
Topaz and colleagues pulled >100 million references from >2 million papers in PubMed Central\u2019s Open Access subset between Jan 2023 and Feb 2026. They kept the 97 million (77%) with a PMID, verified those against PubMed, Crossref, OpenAlex, and Google Scholar, used Claude to filter reference errors (misformatted but real) from genuine fabrications, and validated precision at 91% with three independent reviewers. They found 4,046 fabricated references across 2,810 papers.
The fabrication rate increased more than 12 times, from approximately four per 10,000 papers in 2023, to 51.3 per 10,000 papers in the fourth quarter of 2025
The inflection point is mid-2024, which is when LLM-assisted papers would start clearing typical 100-200 day submission lags. One paper on ureteroileal anastomotic techniques had 18 of 30 verified references fabricated, each tailored to the surgical topic and attributed to real urologists. The authors also flag a paper-mill pattern: the same two-author pair appearing across 11 papers in a single surgical journal in 2025.
Read this along with #3 above. If Elsevier wins the case against Meta, the legal incentives push toward licensed-only training data. The Lancet audit suggests the academic literature itself is already meaningfully polluted by models trained on it. I think this will get worse before it gets better.
Yesterday, Thomas G. Dietterich (arXiv moderator for cs.LG) announced that arXiv will implement 1-year ban for papers containing incontrovertible evidence of unchecked LLM-generated errors, such as hallucinated references or results. Here\u2019s the full text of the thread:
Attention arXiv authors: Our Code of Conduct states that by signing your name as an author of a paper, each author takes full responsibility for all its contents, irrespective of how the contents were generated.
If generative AI tools generate inappropriate language, plagiarized content, biased content, errors, mistakes, incorrect references, or misleading content, and that output is included in scientific works, it is the responsibility of the author(s).
We have recently clarified our penalties for this. If a submission contains incontrovertible evidence that the authors did not check the results of LLM generation, this means we can\u2019t trust anything in the paper.
The penalty is a 1-year ban from arXiv followed by the requirement that subsequent arXiv submissions must first be accepted at a reputable peer-reviewed venue.
Examples of incontrovertible evidence: hallucinated references, meta-comments from the LLM (\u201dhere is a 200 word summary; would you like me to make any changes?\u201d; \u201cthe data in this table is illustrative, fill it in with the real numbers from your experiments\u201d).
I\u2019m about as split on this one as the comments on the OP are. On one hand, GOOD. Hallucinated citations and unchecked AI-authored content is polluting the literature everywhere. I think this borderlines on scientific misconduct, and it destroys trust in the entire scientific enterprise.
Oh the other hand there are lots of problems with detection and enforcement. AI detection software is a cat and mouse game that doesn\u2019t work reliably. And on the enforcement side \u2014 what happens when you\u2019re a co-author on a paper with a hallucinated citation? Say I tell my grad student to work on the methods section and they get an undergrad to write a small section that they worked on, and said undergrad carelessly inserts a fabricated citation. If this paper makes its way onto arXiv, does that infraction go all the way up the chain with the banhammer coming down on all co-authors? Have you ever submitted a paper written with a bunch of co-authors and meticulously looked up every reference or checked that every parameter setting in the detailed methods section is actually a valid parameter for whatever tool was being used? I have.
I think a middle ground solution with a big red banner or warning flag on the abstract page or search results noting that the paper likely contains unverified AI-generated content.
Again, the detection piece is difficult, and authors should be given a chance to respond before getting the scarlet letter. I think the 1-year ban is severe, and if applied to all co-authors, could be extremely damaging to one\u2019s career just because a middle author responsible for page 98 of a large supplemental info section was careless and wasn\u2019t carefully scrutinized. I also worry that such a ban could be inconsistently applied since there\u2019s a lot of subjectivity and guesswork involved with this endeavor.
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The paper isn\u2019t real. Any resemblance to a real paper or real authors is purely coincidental.","src":"https://substackcdn.com/image/fetch/$s_!71Lh!,w_1456,c_limit,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fa4b57310-795f-4211-80bb-6fe9ab994d50_1448x1086.png"},{"src":"https://substackcdn.com/image/fetch/$s_!6ew2!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fed1b0b11-6f3f-4159-b566-3c60cdedf5c5_1273x916.png"},{"src":"https://substackcdn.com/image/fetch/$s_!2FMa!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F022d121d-53f2-4aec-bbed-04737155bb3f_2121x1070.png"},{"src":"https://substackcdn.com/image/fetch/$s_!71Lh!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fa4b57310-795f-4211-80bb-6fe9ab994d50_1448x1086.png"}],"indexed":true,"indexed_at":1778837687,"language":"en","parent_doi":null,"published_at":1778835935,"reference":[],"registered_at":0,"relationships":[],"rid":"ne4rm-36y89","status":"active","summary":"GitHub problems, vibe coding regrets, Elsevier sues Meta, fabricated citations, the arXiv banhammer for AI-generated content","tags":["Papers","AI"],"title":"Five Things (May 15, 2026): AI is why we can't have nice things","updated_at":1778835935,"url":"https://blog.stephenturner.us/p/five-things-may-15-2026","version":"v1"},{"abstract":null,"archive_url":null,"authors":[{"contributor_roles":[],"family":"Sielert","given":"Deborah"},{"affiliation":[{"id":"https://ror.org/0546hnb39","name":"University of Konstanz"}],"contributor_roles":[],"family":"Flaig","given":"Sebastian","url":"https://orcid.org/0009-0001-1247-6976"}],"blog":{"archive_collection":null,"archive_host":null,"archive_prefix":null,"archive_timestamps":null,"authors":[{"name":"Open Access Network"}],"canonical_url":null,"category":"otherSocialSciences","community_id":"969d397b-49b9-4c53-9220-607ef85409e5","created_at":1743604215.212958,"current_feed_url":null,"description":"Neueste Beitr\u00e4ge","doi":null,"doi_as_guid":false,"favicon":null,"feed_format":"application/rss+xml","feed_url":"https://open-access.network/rss-feed?type=200","filter":null,"funding":null,"generator":"Other","generator_raw":"Other","home_page_url":"https://open-access.network","id":"f5a57494-4e8e-41d9-b84c-26cb9b0ab291","indexed":true,"issn":null,"language":"de","license":"https://creativecommons.org/licenses/by/4.0/legalcode","mastodon":null,"prefix":"10.64395","registered_at":0,"relative_url":null,"ror":null,"secure":true,"slug":"oa_network","status":"active","subfield":"1802","subfield_validated":null,"title":"Open Access Network","updated_at":1778835091.735266,"use_api":null,"use_mastodon":false,"user_id":null},"blog_name":"Open Access Network","blog_slug":"oa_network","content_html":"Worauf m\u00fcssen Wissenschaftler*innen am Beginn ihrer akademischen Karriere beim Open-Access-Publizieren achten? Und welche Informationsangebote und Tools k\u00f6nnen dieser Zielgruppe beim Einstieg in die Open-Access-Thematik helfen? \u00dcber diese und viele weitere Fragen hat Deborah Sielert im Podcast \u201eNachwuchsFragen\u201c der Graduiertenakademie an der Leibniz-Universit\u00e4t Hannover gesprochen.\n\nOpen-Access-Publizieren aus Nachwuchsperspektive\nIn der 43-min\u00fctigen Folge \u201ePublizieren mit Open Access\u201c gibt Deborah Sielert eine Einf\u00fchrung in das Thema Open Access, die speziell f\u00fcr junge Wissenschaftler*innen mit noch wenig Erfahrung im wissenschaftlichen Publikationssystem zugeschnitten ist. Neben einem kurzen geschichtlichen Abriss der Entwicklungen des wissenschaftlichen Publizierens, die zur Open-Access-Transformation gef\u00fchrt haben, erkl\u00e4rt sie zentrale Begriffe und Abk\u00fcrzungen, von APC \u00fcber DEAL bis hin zu CC-BY-NC und den Zugangswegen zu Open Access mit ihren verschiedenen Farbbezeichnungen. \nBesonders spannend ist Deborah Sielerts doppelte Perspektive: Einerseits hat sie w\u00e4hrend ihrer Promotion eigene Erfahrungen als junge Forscherin gemacht, andererseits sieht sie nun als Open-Access-Beraterin an der TIB auch die weitl\u00e4ufigen Hintergr\u00fcnde des wissenschaftlichen Publizierens. In dieser Doppelrolle berichtet sie von den Herausforderungen, mit denen Early Career Researchers beim Open-Access-Publizieren konfrontiert sind, und benennt gleichzeitig L\u00f6sungen und Hilfsangebote. Bei der mitunter m\u00fchevollen Suche nach einem passenden Publikationsort f\u00fcr eine Open-Access-Publikation k\u00f6nnen neben den einrichtungsspezifischen Beratungsangeboten an der Bibliothek beispielsweise das B!SON-Tool oder auch der Erfahrungsaustausch mit der Fachcommunity unterst\u00fctzen. Au\u00dferdem sp\u00fcren insbesondere Wissenschaftler*innen am Anfang ihrer Karriere den Publikationsdruck der weit verbreiteten \u201ePublish or Perish\u201c-Kultur, was unseri\u00f6se Predatory Journals versuchen f\u00fcr ihre Zwecke zu nutzen. Auch hier k\u00f6nnen technische Angebote wie Positiv- bzw. Negativlisten von \u201eThink Check Submit\u201c oder das Verzeichnis DOAJ, aber auch die pers\u00f6nliche Open-Access-Beratung an der eigenen Einrichtung Unsicherheiten reduzieren und f\u00fcr derartige Stolpersteine im Publikationswesen sensibilisieren.\n\n\u201eIch h\u00e4tte gerne mehr Wissen \u00fcber den Publikationsmarkt und Themen wie Lizenzen gehabt, denn da besteht f\u00fcr mich ein Zusammenhang zu Selbstwirksamkeit und zum selbstbewussten Navigieren durch die Promotions- und Postdoc-Phase.\u201c\n\u2013 Deborah Sielert \u2013\n\nR\u00fcckblickend auf ihre eigenen Erfahrungen w\u00e4hrend der Promotion macht Deborah Sielert deutlich, wie wichtig der Informationsfluss an junge Wissenschaftler*innen ist. Wer seine Rechte als Urheber*in kennt, kann selbstbewusster mit Verlagen verhandeln und informierte Entscheidungen treffen. Nachwuchsforschende sind nicht den Zw\u00e4ngen eines starren Systems ausgeliefert, sondern k\u00f6nnen aktiv Einfluss nehmen \u2013 etwa durch die bewusste Wahl eines Journals oder einer Lizenz. \u201eIm R\u00fcckblick, wenn ich jetzt nochmal publizieren wollen w\u00fcrde, w\u00fcrde ich eher schauen, welches Journal ich zum Beispiel vom Gesch\u00e4ftsmodell her unterst\u00fctzenswert finde\u201c, res\u00fcmiert sie diesen Gedanken.\n\nLink zur Folge\nDie Podcastfolge kann auf der Webseite des \u201eNachwuchsFragen\u201c-Podcast oder auf allen g\u00e4ngigen Podcast-Plattformen geh\u00f6rt werden.","doi":"https://doi.org/10.64395/hsdb7-ak430","funding_references":null,"guid":"https://open-access.network/blog/open-access-fuer-nachwuchsforschende-folge-im-podcast-nachwuchsfragen","id":"1aaaadae-eabd-4aa2-a2d0-582c3b34afe8","image":null,"images":[],"indexed":true,"indexed_at":1778834134,"language":"de","parent_doi":null,"published_at":1778830980,"reference":[],"registered_at":0,"relationships":[],"rid":"e3fem-bf772","status":"active","summary":"Worauf m\u00fcssen Wissenschaftler*innen am Beginn ihrer akademischen Karriere beim Open-Access-Publizieren achten? Und welche Informationsangebote und Tools k\u00f6nnen dieser Zielgruppe beim Einstieg in die Open-Access-Thematik helfen? \u00dcber diese und viele weitere Fragen hat Deborah Sielert im Podcast \u201eNachwuchsFragen\u201c der Graduiertenakademie an der Leibniz-Universit\u00e4t Hannover gesprochen.","tags":["Beratung","Open Access In Der Praxis"],"title":"Open Access f\u00fcr Nachwuchsforschende \u2013 Folge im Podcast \u201eNachwuchsFragen\u201c","updated_at":1778830980,"url":"https://open-access.network/blog/open-access-fuer-nachwuchsforschende-folge-im-podcast-nachwuchsfragen","version":"v1"},{"abstract":null,"archive_url":null,"authors":[{"affiliation":[{"id":"https://ror.org/02k3smh20","name":"University of Kentucky"}],"contributor_roles":[],"family":"Fruehwald","given":"Josef","url":"https://orcid.org/0000-0001-8480-9461"}],"blog":{"archive_collection":null,"archive_host":null,"archive_prefix":null,"archive_timestamps":null,"authors":null,"canonical_url":null,"category":"socialScience","community_id":"d875be0a-4a87-4c67-bbc8-803adec3b6a7","created_at":1753900307.048582,"current_feed_url":null,"description":null,"doi":null,"doi_as_guid":false,"favicon":null,"feed_format":"application/rss+xml","feed_url":"https://jofrhwld.github.io/blog/index.xml","filter":null,"funding":null,"generator":"Quarto","generator_raw":"Quarto 1.7.32","home_page_url":"https://jofrhwld.github.io/blog/","id":"ee72741c-6561-4ed1-8f78-474b79010844","indexed":true,"issn":null,"language":"en","license":"https://creativecommons.org/licenses/by/4.0/legalcode","mastodon":null,"prefix":"10.59350","registered_at":0,"relative_url":null,"ror":null,"secure":true,"slug":"jofrhwld","status":"active","subfield":"1203","subfield_validated":null,"title":"V\u00e6l Space","updated_at":1778834761.799898,"use_api":null,"use_mastodon":false,"user_id":null},"blog_name":"V\u00e6l Space","blog_slug":"jofrhwld","content_html":"I\u2019ve been noodling over things related to causal inference for a bit now, like DAGs, adjustment sets, marginal effect etc. One thing I hadn\u2019t fully appreciated before is how your choice to estimate direct effects will make your model predictions very sensitive to the kind of prediction grid you use. The rest of this post is just me working through these complications step-by-step.
\nA relatively common kind of causal DAG that (implicitly) comes up in linguistics involves some kind of categorical predictor that has an effect on another continuous predictor.
\n
For example:
\n
With causal relationships like this, people often ask something like
\n\n\nIs there really an effect of consonant voicing on vowel quality, or is there just an effect of vowel duration?
\n
This is a question about the direct effect of voicing on vowel quality. If we set up the dag and check what adjustment variables we need to include to estimate the direct effect of voicing, we\u2019ll see that we need to include duration in the model.
\nvoicing_dag <- ggdag::dagify(\n quality ~ voicing + duration,\n duration ~ voicing\n)\n\ndagitty::adjustmentSets(\n voicing_dag, \n outcome = \"quality\",\n exposure = \"voicing\",\n effect = \"direct\"\n) { duration }But, if we wanted to estimate the total effect of voicing on vowel quality, we shouldn\u2019t include duration.
\ndagitty::adjustmentSets(\n voicing_dag, \n outcome = \"quality\",\n exposure = \"voicing\",\n effect = \"total\"\n) {}This difference between direct and total effects feels a bit abstract sometimes. I\u2019m going to walk through a little example using the penguins dataset, with a focus for how we should approach getting model predictions.
The causal relationships I\u2019ll look at in the penguins data set are:
If we look at the effect of species on both bill length and body mass, we can see a clear effect for both:
\npenguins |>\n select(\n species, body_mass, bill_len\n ) |>\n drop_na() |>\n pivot_longer(\n body_mass:bill_len,\n names_to = \"measure\"\n ) |>\n ggplot(\n aes(species, value)\n )+\n stat_dots(\n side = \"both\"\n ) +\n facet_wrap(\n ~measure,\n scales = \"free_y\"\n ) +\n labs(y = NULL) -> p\n\np\np+theme_darkmode()
And if we look at the effect of body mass on bill length, we can see another very clear effect.
\npenguins |> \n ggplot(\n aes(body_mass, bill_len, color = species)\n ) + \n geom_point() +\n guides(\n color = \"none\"\n )-> p\n\np + \n stat_ellipse(\n geom = \"labelpath\",\n aes(label = species),\n hjust = 0,\n label.padding = 0.01,\n show.legend = F \n) \n\np + \n stat_ellipse(\n geom = \"labelpath\",\n aes(label = species),\n hjust = 0,\n label.padding = 0.01,\n fill = plot_bg,\n show.legend = F\n) + \n theme_darkmode()
Let\u2019s, really quick, get the mean and standard error of bill length by species.
\npenguins |>\n drop_na(starts_with(\"bill_\")) ->\n penguin_full\n\npenguin_full|>\n summarise(\n .by = species,\n estimate = mean(bill_len),\n sd = sd(bill_len),\n n = n()\n ) |> \n mutate(\n se = sd / (sqrt(n)),\n conf.low = estimate - (1.96*se),\n conf.high = estimate + (1.96*se),\n method = \"mean\"\n ) ->\n mean_est| species | \nestimate | \nconf.low | \nconf.high | \n
|---|---|---|---|
| Adelie | \n38.8 | \n38.4 | \n39.2 | \n
| Gentoo | \n47.5 | \n47 | \n48 | \n
| Chinstrap | \n48.8 | \n48 | \n49.6 | \n
I\u2019ll call these quantities with a superscript for each species.
Here they are plotted over the data:
\n
One way to estimate the effect of species on bill length would be to subtract these means from eachother.
\nmean_est |>\n select(\n species,\n estimate\n ) |>\n pivot_wider(\n names_from = species,\n values_from = estimate\n ) |>\n mutate(\n Chinstrap - Adelie,\n Gentoo - Adelie\n )|>\n select(\n matches(\"-\")\n ) |>\n pivot_longer(\n everything(),\n names_to = \"contrast\",\n values_to = \"estimate\"\n ) |>\n mutate(method = \"mean\") ->\n mean_comparisons\n\nmean_comparisons |> \n select(-method) |> \n tt()| contrast | \nestimate | \n
|---|---|
| Chinstrap - Adelie | \n10.04 | \n
| Gentoo - Adelie | \n8.71 | \n
If we look at these differences in means, and consider the scatterplot of body mass vs bill length, we might wonder whether the difference between Gentoo and Adelie is really that large. Maybe Gentoo penguins are just larger overall, with proportionally longer bills. That\u2019s where estimating the direct effect comes in.
\nA simple linear model will do the trick:
\nbill_model <- lm(\n bill_len ~ body_mass + species, \n data = penguin_full\n)And if we look at the estimated effect of species:
\ntidy(\n bill_model\n) |> \n filter(\n str_detect(\n term, \"species\"\n )\n ) |>\n select(term, estimate) |>\n tt()| term | \nestimate | \n
|---|---|
| speciesChinstrap | \n9.92 | \n
| speciesGentoo | \n3.56 | \n
The estimated difference between Gentoo and Adelie is, in fact, about half as much as the comparison of means suggested.
\nHere\u2019s where things start getting a little tricky, and we need to take some care in how we get and think about predicted values.
\nThe function avg_predictions() will calculate the predicted unit level bill length, then average over species. Here, stands for the species variable, and
stands form the body mass variable.
avg_predictions(\n bill_model,\n by = \"species\"\n) |>\n mutate(method = \"pred_avg\") ->\n avg_pred| species | \nestimate | \nconf.low | \nconf.high | \n
|---|---|---|---|
| Adelie | \n38.8 | \n38.4 | \n39.2 | \n
| Chinstrap | \n48.8 | \n48.3 | \n49.4 | \n
| Gentoo | \n47.5 | \n47.1 | \n47.9 | \n
We can visually compare these average predictions to the mean and standard errors we estimated above:
\nbind_rows(\n mean_est,\n avg_pred\n) |>\n ggplot(\n aes(species, estimate)\n ) + \n geom_dots(\n data = penguin_full,\n aes(x = species, y = bill_len),\n side = \"both\"\n ) + \n geom_pointinterval(\n size = 5, \n aes(\n ymin = conf.low,\n ymax = conf.high,\n color = method\n ),\n position = position_dodge(width = 0.2)\n ) ->\n p\n\np\np+theme_darkmode()
To get predictions at representative values, we can use the datagrid() function. If we just pass the model to datagrid() and no other arguments, it will give us back a 1 row data frame where every column is either the average value across the original data, or the most frequent level.
| rowid | \nbill_len | \nbody_mass | \nspecies | \n
|---|---|---|---|
| 1 | \n43.9 | \n4202 | \nAdelie | \n
To get a prediction for each species, I\u2019ll pass a vector of species names to species.
| rowid | \nbill_len | \nbody_mass | \nspecies | \n
|---|---|---|---|
| 1 | \n43.9 | \n4202 | \nAdelie | \n
| 2 | \n43.9 | \n4202 | \nChinstrap | \n
| 3 | \n43.9 | \n4202 | \nGentoo | \n
We can describe the predictions we get as the expected bill length for each species, conditional on the average body mass.
\npredictions(\n bill_model,\n newdata = grid1\n) |> \n mutate(method = \"pred_grid1\")->\n species_predIf we compare these predicted values to the previous estimates, they\u2019re very different!
\nbind_rows(\n mean_est,\n avg_pred,\n species_pred\n) |> \n ggplot(\n aes(species, estimate)\n ) + \n geom_dots(\n data = penguin_full,\n aes(x = species, y = bill_len),\n side = \"both\"\n ) + \n geom_pointinterval(\n size = 5, \n aes(\n ymin = conf.low,\n ymax = conf.high,\n color = method\n ),\n position = position_dodge(width = 0.3)\n ) -> \n p\n\np\np + theme_darkmode()
The predicted bill length for each species, especially Gentoo, don\u2019t look like typical bill lengths for each species. But that\u2019s because these predictions were conditional on the average body mass across all individuals, which isn\u2019t a representatuve body mass for any individual species.
\nbill_model |>\n predictions(\n newdata = datagrid(\n species = unique,\n body_mass = range\n )\n )->\n full_est\n\nbolden <- \\(x){\n str_glue(\"<b>{x}</b>\")\n}\n\npenguin_full |> \n ggplot(\n aes(body_mass, bill_len, color = species)\n ) + \n geom_point(\n size = 0.2,\n alpha = 0.5\n ) + \n geom_textline(\n data = full_est,\n aes(x = body_mass, y = estimate, label = bolden(species)),\n hjust= 0.7,\n rich = T\n )+\n geom_vline(\n xintercept = mean(penguin_full$body_mass)\n ) +\n geom_point(\n data = species_pred,\n aes(y = estimate)\n ) +\n guides(\n color = \"none\"\n ) -> p\n\np\np + theme_darkmode()
Instead of setting body_mass to the mean across all penguins, let\u2019s instead set it to the mean within each species. We can do that with datagrid() by passing it by = \"species\".
| rowid | \nbill_len | \nbody_mass | \nspecies | \n
|---|---|---|---|
| 1 | \n38.8 | \n3701 | \nAdelie | \n
| 2 | \n48.8 | \n3733 | \nChinstrap | \n
| 3 | \n47.5 | \n5076 | \nGentoo | \n
Using this prediction grid, we could describe the preditions as:
\npredictions(\n bill_model,\n newdata = grid2\n) |> \n mutate(\n method = \"pred_grid2\"\n )->\n typical_predComparing these predictions to estimates we had before, we can see they\u2019re more in-line with what we expect the typical bill lengths to be for each species.
\nbind_rows(\n mean_est,\n avg_pred,\n species_pred,\n typical_pred\n) |> \n ggplot(\n aes(species, estimate)\n ) + \n geom_dots(\n data = penguin_full,\n aes(x = species, y = bill_len),\n side = \"both\"\n ) + \n geom_pointinterval(\n size = 5, \n aes(\n ymin = conf.low,\n ymax = conf.high,\n color = method\n ),\n position = position_dodge(width = 0.4)\n ) -> \n p\n\np\np + theme_darkmode()
The reason we\u2019ve got predictions that are more in line with what is typical for each species is because we\u2019ve evaluated the model at body masses that are more in line with what is typical for each species.
\npenguin_full |> \n ggplot(\n aes(body_mass, bill_len, color = species)\n ) + \n geom_point(\n size = 0.2,\n alpha = 0.5\n ) + \n geom_textline(\n data = full_est,\n aes(x = body_mass, y = estimate, label = bolden(species)),\n hjust= 0.9,\n rich = T\n ) +\n geom_segment(\n data = typical_pred,\n aes(\n x = body_mass,\n xend = body_mass,\n y = estimate\n ),\n yend = -Inf\n ) +\n geom_point(\n data = typical_pred,\n aes(\n x = body_mass,\n y = estimate\n )\n ) +\n guides(\n color = \"none\"\n ) ->\n p\n\np\np + theme_darkmode()
We can get the Average Treatment Effect of species by calculating how different each individual\u2019s bill length is predicted to be if we swapped its species.
\navg_comparisons(\n bill_model,\n variables = \"species\"\n) -> \n avg_comp| contrast | \nestimate | \n
|---|---|
| Chinstrap - Adelie | \n9.92 | \n
| Gentoo - Adelie | \n3.56 | \n
But, again, it\u2019s important that these contrasts are conditional on the body mass of each penguin. So, if you had an Adelie and a Gentoo with the same body mass, the Gentoo would have a bill length about 3.5 mm longer. But, not that many Adelie and Gentoo penguins have the same body mass!
\npenguin_full |>\n ggplot(\n aes(body_mass)\n ) +\n geom_dots(\n aes(\n fill = species,\n color = species,\n order = species\n ),\n group = 1\n ) + \n scale_y_continuous(\n expand = expansion(0)\n ) ->\n p\n\np + theme_no_y() + \n theme_sub_legend(\n position = \"inside\",\n position.inside = c(0.85,0.8)\n )\np + theme_darkmode() + theme_no_y() +\n theme_sub_legend(\n position = \"inside\",\n position.inside = c(0.85,0.8)\n )
So, if you picked a random Adelie and a random Gentoo, the best estimate of the difference in their bill size (the direct effect) would be larger! One way we could estimate the typical difference between Gentoo and Adelie is to calculate every pairwise difference between individual penguins.
\ntibble(\n diff = as.vector(diff_mat)\n) |>\n ggplot(\n aes(diff)\n ) + \n stat_dots()+\n geom_vline(\n xintercept = mean(diff_mat)\n ) +\n scale_y_continuous(\n expand = expansion(0)\n ) +\n labs(\n x = \"Gentoo - Adelie\"\n ) ->\n p\n\np + theme_no_y()\np + theme_darkmode() + theme_no_y()
Almost every Gentoo has a longer beak than every Adelie. And the average of these pairwise comparisons is the total effect of species on bill length.
\nmean(diff_mat)[1] 8.713487To be honest, I\u2019m not 100% sure what the upshot here is. Let\u2019s imagine a case where following consonant voicing only had an indirect effect on vowel quality via vowel duration. It would be an interesting result to find that after adjusting for duration, the effect of voicing is effectively 0. But estimating and plotting model predictions that show no difference between voicing contexts would be strange, since voicing contexts also systematically differ in terms of duration. You\u2019d effectively be plotting predicted values of very atypical cases.
\nYou could try plotting both kinds of predictions\u2026 but I\u2019m already dreading the kind of tortured prose involved in describing the different kinds of predictions to readers.
\n@online{fruehwald2026,\n author = {Fruehwald, Josef},\n title = {Getting Predictions When Estimating Direct Vs Total Effects.},\n series = {V\u00e6l Space},\n date = {2026-05-15},\n url = {https://jofrhwld.github.io/blog/posts/2026/05/2026-05-15_total-vs-direct-predictions/},\n doi = {10.59350/rps04-6zc41},\n langid = {en}\n}\nOver the past decade, transformative agreements have been instrumental in driving the transition to open access by redirecting former subscription costs to fund open access publishing for affiliated authors of the negotiating institutions (de Jonge et al. 2025; D\u00e9r 2025). Open publishing agreements have gained serious traction, with the ESAC registry listing 1,644 such agreements as of April 29, 2026, including 177 concluded with German institutions and consortia (ESAC Initiative, n.d.).
\nIn D\u00f6rner (2026), I conducted a content analysis of 13 transformative agreements between scientific publishers and German consortia, with a focus on contractual provisions related to open metadata and data-analytical research services. With respect to open metadata provisions, 12 of the 13 agreements mandated metadata submission to Crossref. However, only four agreements specified detailed metadata fields for Crossref delivery, despite these being non-exhaustive lists. Metadata fields explicitly referenced included, inter alia, author information, ORCID identifiers, affiliations, and open access licence information.
\nThis blog post extends the prior content analysis by assessing the implementation of contractual provisions through a data-driven approach, focusing on two aspects: (i) CC BY licence adoption and (ii) open metadata coverage including ORCID and ROR IDs, TDM information, funding information, funder DOIs, and open abstracts. I build upon prior work by the Hybrid Open Access Dashboard (HOAD) and the Sesame Open Science (SOS) Crossref truth table. HOAD is an openly available data analytics tool that currently tracks, amongst other things, the use of Creative Commons (CC) licences and the coverage of open metadata in Crossref for open access articles in hybrid journals. The metadata captured by HOAD include text and data mining (TDM) information, ORCID coverage, funding information, and the coverage of open abstracts and citations (Achterberg and Jahn 2023). However, some dimensions are missing from HOAD, such as ROR coverage and information for articles in fully open access journals. The SOS Crossref truth table is a processed table based on Crossref data indicating presence and counts of several metadata elements for each record in Crossref. Compared to HOAD the truth table provides detailed information on affiliations and ROR coverage, but does not include TDM and CC licence information. Furthermore, its scope is broader, meaning that articles made available through transformative agreements are not pre-identified.
\nThis analysis reproduces and adapts the data analytics workflow underlying HOAD, as describe in Jahn (2025b). To this end, data retrieval started with obtaining journal and institutional information from preserved transformative agreement data from the cOAlition S Journal Checker Tool (JCT) 1. I subsequently filtered the data based on the ESAC IDs of the selected 13 transformative agreements (see Table\u00a01) to obtain information about journal portfolios and participating institutions pertaining specifically to the respective agreements. Journal information was further enriched with linking ISSNs (ISSN-Ls), as provided by the ISSN International Centre in the February 2026 version, based on ISSN matching to allow unique reference of journals.
\nUsing the compiled JCT data, I retrieved article-level metadata from the Crossref April 2026 database snapshot and enriched it with first-author affiliation data from the OpenAlex Walden April 2026 database snapshot. All data was accessed via the SUB G\u00f6ttingen Open Scholarly Data Warehouse. It should be noted that affiliation metadata coverage in OpenAlex has been reported to have declined substantially following the transition to Walden, partly due to publishers not sharing affiliation metadata via Crossref and partly due to technical issues within OpenAlex itself (Jahn 2025a), which may affect the completeness of first-author affiliation matching in this analysis.
\nThe article-level data was restricted to the publication years 2019\u20132025, based on the issued date, to account for varying transformative agreement terms and full-year data availability (see Table\u00a01). Non-scholarly journal content, such as table of contents etc., was excluded via paratext recognition, enrichment with first-author affiliation data was done by matching JCT participating institution information with OpenAlex affiliation data using ROR-IDs and institutional names as a fall back option. Furthermore the SOS Crossref truth table data from the January 2026 snapshot was matched using DOIs.
\n| Publisher | \nConsortium Lead | \nTerm | \nESAC ID | \n
|---|---|---|---|
| Elsevier | \nDEAL | \n01.09.2023\u201331.12.2028 | \nels2023deal | \n
| Hogrefe | \nSUB G\u00f6ttingen | \n01.01.2021\u201331.12.2023 | \nhogrefe2021gac | \n
| 01.01.2024\u201331.12.2026 | \nhogrefe2024gac | \n||
| Optica | \nTIB | \n01.01.2023\u201331.12.2026 | \nopg2023tib | \n
| Royal Society of Chemistry | \nTIB | \n01.01.2024\u201331.12.2027 | \nrsc2024tib | \n
| Springer Nature | \nDEAL | \n01.01.2020\u201331.12.2023 | \nsn2020deal | \n
| 01.01.2024\u201331.12.2028 | \nsn2024deal | \n||
| MPDL | \n01.01.2021\u201331.12.2024 | \nsn2021gac | \n|
| Trans Tech Publications | \nTIB | \n01.01.2024\u201331.12.2026 | \nttp2024tib | \n
| Walter de Gruyter | \nSUB G\u00f6ttingen | \n01.01.2022\u201331.12.2022 | \ndegruy2022gac | \n
| 01.01.2023\u201331.12.2024 | \ndegruy2023gac | \n||
| Wiley | \nDEAL | \n01.01.2019\u201331.12.2023 | \nwiley2019deal | \n
| 01.01.2024\u201331.12.2028 | \nwiley2024deal | \n
My workflow extends the current workflows for HOAD in the following respects: (1) journal coverage includes both hybrid and fully open access journals rather than hybrid journals only, (2) article data is restricted to pertain only to the selected 13 transformative agreements presented in Table\u00a01, (3) I additionally enriched the data set with data from the SOS Crossref truth table.
\nTo obtain information about metadata coverage, I computed counts of authors, affiliations, funders, and their respective persistent identifiers, as well as indicators for the presence of key metadata fields such as TDM support and open abstracts. Affiliation and ROR ID counts were computed as distinct values per article. This means that if multiple authors from the same institution appear on an article, the affiliation and its designated ROR ID are each counted only once. The number of affiliations was determined by first checking for ROR IDs and using name strings as a fall back option, when affiliations had no ROR IDs assigned. I identified open access articles by the presence of a CC licence in the version of record metadata. I therefore did not retrieve licence URLs for author accepted manuscript or TDM article versions, as identified by Crossref\u2019s content_version field. Subsequently, articles without a CC licence were classified as non-open access, regardless of publisher policies or other access indicators.
\nThe following SQL code shows the query used to retrieve the article-level data set, compute different metrics and join the SOS Crossref truth table.
\nWITH filtered_publications AS (\n SELECT DISTINCT\n UPPER(TRIM(cr.doi)) AS doi,\n jct.issn_l,\n jct.esac_id AS jn_esac_id,\n cr.publisher AS cr_publisher,\n cr.container_title AS cr_journal_title,\n EXTRACT(YEAR FROM cr.issued) AS cr_year,\n CASE WHEN cr.abstract IS NOT NULL THEN 1 END AS has_abstract,\n cr.license,\n cr.author,\n cr.link,\n cr.funder\n FROM (\n SELECT SPLIT(issn, \",\") AS issn,\n doi,\n publisher,\n container_title,\n issued,\n license,\n abstract,\n author,\n link,\n funder\n FROM `subugoe-collaborative.cr_instant.snapshot`\n WHERE NOT REGEXP_CONTAINS(\n title,\n '(?i)^Author Index$|^Back Cover|^Contents$|^Contents:|^Corrigendum|^Cover Image|^Cover Picture|^Editorial Board|^Front Cover|^Frontispiece|^Inside Back Cover|^Inside Cover|^Inside Front Cover|^Issue Information|^List of contents|^Masthead|^Title page|^Correction$|^Corrections to|^Corrections$|^Withdrawn|^Frontmatter'\n )\n AND (\n NOT REGEXP_CONTAINS(page, '^S')\n OR page IS NULL\n )\n AND (\n NOT REGEXP_CONTAINS(issue, '^S')\n OR issue IS NULL\n )\n AND EXTRACT(YEAR FROM issued) BETWEEN 2019 AND 2025\n ) AS cr\n CROSS JOIN UNNEST(cr.issn) AS issn\n INNER JOIN `subugoe-collaborative.resources.oad_jct_jn` jct\n ON issn = jct.issn\n WHERE (\n (jct.esac_id = 'wiley2019deal' AND EXTRACT(YEAR FROM cr.issued) BETWEEN 2019 AND 2023) OR\n (jct.esac_id = 'wiley2024deal' AND EXTRACT(YEAR FROM cr.issued) BETWEEN 2024 AND 2025) OR\n (jct.esac_id = 'sn2021gac' AND EXTRACT(YEAR FROM cr.issued) BETWEEN 2021 AND 2023) OR\n (jct.esac_id = 'sn2020deal' AND EXTRACT(YEAR FROM cr.issued) BETWEEN 2020 AND 2023) OR\n (jct.esac_id = 'sn2024deal' AND EXTRACT(YEAR FROM cr.issued) BETWEEN 2024 AND 2025) OR\n (jct.esac_id = 'els2023deal' AND EXTRACT(YEAR FROM cr.issued) BETWEEN 2023 AND 2025) OR\n (jct.esac_id = 'degruy2022gac' AND EXTRACT(YEAR FROM cr.issued) = 2022) OR\n (jct.esac_id = 'degruy2023gac' AND EXTRACT(YEAR FROM cr.issued) BETWEEN 2023 AND 2024) OR\n (jct.esac_id = 'hogrefe2021gac' AND EXTRACT(YEAR FROM cr.issued) BETWEEN 2021 AND 2023) OR\n (jct.esac_id = 'hogrefe2024gac' AND EXTRACT(YEAR FROM cr.issued) BETWEEN 2024 AND 2025) OR\n (jct.esac_id = 'rsc2024tib' AND EXTRACT(YEAR FROM cr.issued) BETWEEN 2024 AND 2025) OR\n (jct.esac_id = 'opg2023tib' AND EXTRACT(YEAR FROM cr.issued) BETWEEN 2023 AND 2025) OR\n (jct.esac_id = 'ttp2024tib' AND EXTRACT(YEAR FROM cr.issued) BETWEEN 2024 AND 2025)\n )\n),\nfirst_author_data AS (\n SELECT\n UPPER(TRIM(w.doi)) AS doi,\n a.countries\n FROM `subugoe-collaborative.openalex_walden.works` w\n CROSS JOIN UNNEST(authorships) AS a\n WHERE a.author_position = 'first'\n AND 'DE' IN (\n SELECT UPPER(TRIM(country_code))\n FROM UNNEST(a.countries) AS country_code\n )\n AND EXISTS (\n SELECT 1\n FROM UNNEST(a.institutions) AS i\n JOIN `subugoe-collaborative.resources.oad_jct_inst` ji\n ON LOWER(i.ror) = LOWER(ji.ror_id)\n OR LOWER(i.display_name) = LOWER(ji.inst_name)\n WHERE i.display_name IS NOT NULL\n AND ji.inst_name IS NOT NULL\n )\n),\noad_ta_md AS (\n SELECT\n fp.doi,\n fp.cr_year,\n fp.issn_l,\n fp.cr_journal_title,\n fp.jn_esac_id,\n fp.cr_publisher,\n fp.has_abstract,\n ARRAY_LENGTH(fp.author) AS num_authors,\n (SELECT COUNT(1) FROM UNNEST(fp.author) AS authors WHERE authors.orcid IS NOT NULL) AS num_orcids,\n COUNT(DISTINCT CASE WHEN md_2.id IS NOT NULL THEN md_2.id ELSE md_1.name END) AS num_affiliations,\n COUNT(DISTINCT CASE WHEN LOWER(md_2.id_type) = 'ror' THEN md_2.id END) AS num_rors,\n ARRAY_LENGTH(fp.funder) AS num_funders,\n (SELECT COUNT(1) FROM UNNEST(fp.funder) AS funders, UNNEST(funders.id) WHERE LOWER(id_type) = \"doi\") AS num_funder_dois,\n MAX(CASE WHEN md_3.content_version IN ('vor', 'unspecified') THEN md_3.url END) AS license_url,\n CASE\n WHEN EXISTS (SELECT 1 FROM UNNEST(fp.link) WHERE intended_application = \"text-mining\") THEN 1\n ELSE 0\n END AS has_tdm,\n tt.doi AS tt_doi,\n tt.count_authors,\n tt.has_authors_id_orcid,\n tt.count_authors_id_orcid,\n tt.has_affiliations,\n tt.count_affiliations,\n tt.has_affiliations_id_ror,\n tt.count_affiliations_id_ror,\n tt.has_abstract AS tt_has_abstract,\n tt.has_funders,\n tt.count_funders,\n tt.has_funders_id_doi,\n tt.count_funders_id_doi\n FROM filtered_publications fp\n INNER JOIN first_author_data fa\n ON fp.doi = fa.doi\n LEFT JOIN UNNEST(fp.author) AS md_0\n LEFT JOIN UNNEST(md_0.affiliation) AS md_1\n LEFT JOIN UNNEST(md_1.id) AS md_2\n LEFT JOIN UNNEST(fp.license) AS md_3\n LEFT JOIN `sos-datasources.truthtables.crossref_truthtable_20260131` tt\n ON fp.doi = tt.doi\n GROUP BY\n fp.doi,\n tt.doi,\n fp.cr_year,\n fp.issn_l,\n fp.cr_journal_title,\n fp.jn_esac_id,\n fp.cr_publisher,\n fp.has_abstract,\n fp.author,\n fp.funder,\n fp.license,\n fp.link,\n tt.count_authors,\n tt.has_authors_id_orcid,\n tt.count_authors_id_orcid,\n tt.has_affiliations,\n tt.count_affiliations,\n tt.has_affiliations_id_ror,\n tt.count_affiliations_id_ror,\n tt.has_abstract,\n tt.has_funders,\n tt.count_funders,\n tt.has_funders_id_doi,\n tt.count_funders_id_doi\n)\n\nSELECT * FROM oad_ta_mdData cleaning and preparation involved several standardisation procedures: (1) harmonisation of ISSN-Ls for journals assigned to multiple ISSN-Ls, (2) consolidation of ESAC IDs for ISSN-Ls assigned to multiple ESAC IDs, in particular those resulting from publisher changes after the termination of the agreement, and (3) correction of errors in licence URLs. Journal-level standardisations were based on journal information from EZB and ZDB.
\nThe so-compiled data set I used for the analysis consists of 246,499 articles published between 2019 and 2025 and enabled by one of the 13 transformative agreements of interest.
\nI used the SOS Crossref truth table data to validate my approach and found strong alignment for all coverage metrics (ORCIDs, funding information, funder DOIs, open abstracts) except for ROR coverage. Specifically, the ROR coverage values from the SOS dataset were higher than those I computed, in some instances even considerably. A more detailed analysis of the data revealed that these differences are attributable to 355 articles for which the absolute number of ROR IDs counted in the SOS dataset exceeds the absolute number of affiliations. Inspecting a sample of 20 DOIs from this set of articles via the Crossref API revealed that when a ROR ID was present for a given affiliation, no additional name string (Crossref field name) was included in the metadata. The SQL query used to create the SOS dataset and calculate the metrics shows that the number of affiliations is determined based on the name string in the Crossref affiliation name field. This differs from the calculation approach applied here. If publishers do not provide a name string for each affiliation, additionally to the respective ROR IDs, this explains why, for these articles, the number of ROR IDs is assessed as higher by the SOS counting method than the number of actual affiliations.
\nThe contractual provisions analysed in D\u00f6rner (2026), with underlying data provided in D\u00f6rner (2025), form the baseline for the analysis presented here. Briefly, the agreements with de Gruyter, Optica, and Trans Tech Publications mandated CC BY licensing; 12 of the 13 agreements committed to metadata delivery to Crossref, with several explicitly referencing ORCIDs, ROR IDs, and funding information as metadata fields available to the publishers; and 12 agreements contained TDM provisions.
\nTable\u00a02 provides an overview of the article volume per agreement and publication year, aligned with the respective agreement terms, detailing the overall share of open access articles, the proportion published under a CC BY licence, and trends of CC BY shares across publication years.
\nFor the agreements with Optica and Trans Tech Publications, the proportion of open access articles and the proportion with a CC BY licence are identical, indicating full implementation of the CC provision. An overall slight increase in CC BY share can be observed for Optica, while Trans Tech Publications shows a decline. For de Gruyter, the CC BY share falls short of the overall open access share \u2014 the underlying data suggest this is due to some articles having been published under CC BY-NC-ND \u2014 though a general upward trend in CC BY adoption is visible.
\nFor the agreements with Elsevier, Wiley, and the Royal Society of Chemistry, where CC BY was required only as a default or preferred option rather than the sole permissible licence, the open access share consistently exceeds the CC BY share across all agreement terms, despite an overall increase in both. The Hogrefe agreements allow authors to choose from several CC licences without preference for CC BY, which is reflected in a lower CC BY share relative to the overall open access share, and a downward trend in CC BY for the 2024 agreement. For the Springer Nature agreements, the 2021 MPDL agreement shows identical open access and CC BY shares throughout its term, while the 2020 DEAL agreement shows a slightly higher overall open access share, with an upward trend in CC BY for both.
\nCrossref is critical, because many publishers use this DOI registration agency to share metadata openly. In addition to bibliographic data, efforts from initiatives such as the Initiative for Open Citations and the Initiative for Open Abstracts have led to an increase in the open availability of references and abstracts in Crossref (Van Eck and Waltman 2025).
\nTable\u00a032 provides an overview of the proportion of openly accessible metadata in Crossref for articles covered by the 13 transformative agreements, focusing on TDM support, authors\u2019 ORCIDs, author affiliations\u2019 ROR IDs, general funding information, funders\u2019 DOIs, and openly accessible abstracts.
\nFor the agreements with Elsevier, de Gruyter, and the 2021 MPDL Springer Nature agreement, TDM information has been persistently submitted to Crossref throughout the entire terms, consistent with contractual permissions for TDM for private use or research purposes. By contrast, no TDM information was delivered for the agreements with Hogrefe, the Royal Society of Chemistry, Trans Tech Publications, or Optica, despite non-commercial TDM being permissible under the first three and no TDM clause having been identified for Optica. For the Springer Nature DEAL agreements, TDM support is high throughout, reaching 100% in 2022. For Wiley, a strong decline is visible from 2023 onwards \u2014 corroborated by HOAD and the Crossref Participation Report for Wiley \u2014 though HOAD data for 2026 shows a recovery to over 90%, suggesting the decline may reflect a temporary technical issue rather than a strategic change.
\nORCID coverage ranges from 10.9% (Hogrefe for 2021) to 62.5% (Royal Society of Chemistry for 2025). Notably, the Royal Society of Chemistry agreement \u2014 which does not explicitly reference ORCIDs for Crossref delivery \u2014 shows the highest coverage. Despite most other agreements mentioning ORCIDs for author identification or metadata delivery, coverage remains mostly below 50%.
\nSubstantial disparities are visible across publishers. Optica is the only agreement with noticeable and consistent ROR coverage. Wiley shows minimal ROR coverage from 2022 onwards, and all other agreements show 0% \u2014 including the agreements with the Royal Society of Chemistry and Trans Tech Publications, which explicitly reference ROR IDs for institutional identification or reporting.
\nNo funding-related metadata was submitted to Crossref for the Hogrefe or Trans Tech Publications agreements, despite both containing funding information provisions. The Trans Tech Publications agreement, however, specified that funding information would only be recorded upon request by the authors. The Royal Society of Chemistry agreement \u2014 the only one without a funding information provision \u2014 nevertheless achieves among the highest funding information coverage, with DOIs recorded for all funders. De Gruyter shows low funding information coverage (maximum 7.4%) but with around 70% funder DOI coverage. Elsevier, which only committed to examining the feasibility of including funding information, shows coverage rising to 60% by 2025 with near-complete funder DOI coverage. The 2021 MPDL Springer Nature agreement shows declining funding information and funder DOI coverage, while the DEAL agreements show comparably higher funding information coverage but also a downward trend in funder DOI coverage. Wiley coverage of funding information oscillates around 50%, while funder DOI coverage is consistently above 90% and trending upward. Optica \u2014 the only agreement with an explicit contractual guarantee for funding information \u2014 shows the highest funding information coverage, though with a slight downward trend in funder DOI coverage.
\nAlmost no abstracts were delivered to Crossref for articles under the Elsevier agreement. Coverage is highest for Optica and Trans Tech Publications, followed by the Royal Society of Chemistry and Wiley, each exceeding 90%. None of the 13 agreements contained an explicit contractual provision for abstract delivery to Crossref.
\nThe analysis reveals substantial discrepancies between the contractual provisions of transformative agreements and their actual implementation in Crossref metadata, highlighting a gap in the operationalisation of open metadata commitments.
\nThe CC licence analysis demonstrates that contractual specificity directly correlates with implementation compliance. Agreements that explicitly mandated CC BY licensing (Optica, Trans Tech Publications, and de Gruyter) generally achieved higher compliance rates, though de Gruyter\u2019s implementation was imperfect due to residual CC BY-NC-ND usage. In contrast, agreements where CC BY was merely presented as a default or preferred option (Elsevier, Wiley, Royal Society of Chemistry) consistently showed lower CC BY adoption rates despite increasing overall open access volumes. This finding suggests that without explicit contractual mandates requiring CC BY as the sole permissible licence, publishers maintain flexibility to offer alternative licences, potentially undermining the transformative goals of these agreements.
\nThe near-absence of ROR coverage across most agreements is particularly striking. Even agreements that explicitly reference ROR IDs in the agreement text show 0% coverage, and virtually no ROR IDs were submitted for articles under the DEAL agreements \u2014 which account for the largest share of publication volume. This is problematic because ROR IDs provide persistent, unambiguous institutional identification essential for research assessment and funding attribution. Without them, bibliometric analyses must rely on error-prone string matching, introducing noise and increasing the manual curation burden. The methodological comparison with the SOS Crossref truth table further highlights the difficulty of measuring ROR coverage consistently when publishers submit ROR IDs without corresponding institutional name strings. The importance of ROR adoption is further underscored by Crossref\u2019s plans to retire the Funder Registry in favour of ROR (Portenoy 2026), making consistent ROR submission increasingly central to the Crossref metadata ecosystem.
\nIn line with de Jonge and Kramer (2026), the ORCID coverage findings suggest that publisher workflow integration and editorial systems might play a more decisive role in ORCID adoption than contractual language alone, as for instance, the Royal Society of Chemistry agreement \u2013 which does not explicitly reference ORCIDs for Crossref delivery \u2013 achieves the highest coverage regardless.
\nThe funding metadata findings illustrate a broader pattern: the presence of contractual provisions is no guarantee of implementation. The Trans Tech Publications agreement committed to recording funding information but only upon author request, and the complete absence of such metadata suggests either that authors rarely invoked this option, that the publisher lacked the necessary infrastructure, or that the provision was too vague to operationalise. Conversely, the Royal Society of Chemistry \u2014 without any funding metadata provision \u2014 achieved among the highest coverage, again pointing to publisher infrastructure and internal priorities as the more decisive factors. The declining funder DOI coverage for both Springer Nature agreement types, despite generally reasonable funding information coverage, further illustrates that even partial implementation can be inconsistent over time.
\nThe TDM findings similarly show that contractual permissions do not reliably translate into metadata delivery. The temporary decline in Wiley\u2019s TDM metadata after 2022, despite contractual permissions, likely reflects a technical issue given the subsequent recovery visible in HOAD\u2019s 2026 data, but it underscores the need for ongoing monitoring rather than reliance on contractual commitments alone.
\nTaken together, these findings demonstrate that vague or permissive contractual language on metadata tends to produce inconsistent outcomes. The cases of the Royal Society of Chemistry (high ORCID and funding coverage without explicit provisions) and Trans Tech Publications (zero funding coverage despite an explicit provision) illustrate the disconnect between contractual commitment and operational reality. Future agreements should specify exact metadata elements, required values, and implementation timelines, with measurable compliance indicators to enable systematic monitoring.
\nOne of the most compelling findings is the near-total absence of ROR ID coverage across most agreements. This underscores a clear opportunity for HOAD to expand its analytical scope by incorporating ROR coverage as a standard metric. Such an extension would be technically straightforward and would enable monitoring of ROR coverage across a wider set of agreements over time.
\nWhile this analysis is focused on 13 agreements with German consortia, the methodological approach could serve as a template for broader investigation. A distributed effort, connected to the Joint Task Force on Negotiating Openness of Publication Metadata between OA2020 (now OA Forward) and the Barcelona Declaration, has been started to analyse all openly available transformative agreements in the ESAC Registry of Open Publishing Agreements. The approach presented here could contribute to that initiative, providing empirical evidence to inform the task force\u2019s work on negotiating openness of publication metadata across publishers and nations.
\nR Code and processed data files for this data analysis are available on GitHub: https://github.com/subugoe/scholcomm_analytics/tree/main/posts/ta_coverage_analysis
\nData tables used for data retrieval are publicly available on Google BigQuery, as provided by the SUB G\u00f6ttingen: https://subugoe.github.io/scholcomm_analytics/data.html.
\nhttps://github.com/njahn82/jct_data\u21a9\ufe0e
Table\u00a03 reuses and extends the interactive visualization framework from the Hybrid Open Access Dashboard, including its reactable-based layout and filtering system. It adds ROR ID coverage as a new metric, which was not included in HOAD\u2019s original scope and uses a modified colour palette. Code adaptations were based on HOAD\u2019s open-source implementation on GitHub.\u21a9\ufe0e
PKP is proud to share its annual report for 2025, covering the period from April 1st, 2025 to March 31st, 2026.
\nAs we reflect on the past year, the 2025 Annual Report offers an opportunity to recognize the strength and dedication of the global community that continues to drive PKP forward. From expanding collaborations to advancing strategic priorities, this year marked meaningful progress on multiple fronts. The report also highlights important developments in PKP software, ongoing research initiatives, and community-informed improvements that continue to support more equitable, accessible, and sustainable open publishing worldwide.
\nThe report tells a story centered around our strategic priorities:
\nInside you will find:
\nThe full report is available now as a downloadable PDF:
\n\nWe invite you to read it, share it, and see how your engagement with PKP contributes to something much larger: a stronger, more inclusive ecosystem for scholarly publishing worldwide. You are part of the Public Knowledge Project!
\nPlease join us to celebrate at our upcoming Annual General Meeting on May 27th
This report was made possible thanks to the contributions of many folks:
\nJuan Pablo Alperin, Alejandra Casas Ni\u00f1o de Rivera, Trevor Davis, Michael Felczak, Roger Gillis, Jeanette Hatherill, Mark Huskisson, Emily Hopkins, Teresa Lee, Patricia Mangahis, Urooj Nizami, Famira Racy, Stephanie Savage, Alec Smecher, Marco Tullney, Emma Uhl, Zoe Wake Hyde and John Willinsky.
\nSpecial thanks to Alexandre Cunha for the thoughtful design and layout that brings this year\u2019s story to life.
\nAnd of course, the broader community whose support, whether through voluntary work, financial contributions, or simply using our software, makes all of this possible.
\nThe post What we achieved together in 2025: PKP\u2019s Annual Report is here appeared first on Public Knowledge Project.
","doi":"https://doi.org/10.59350/rsqxd-xr461","funding_references":null,"guid":"https://pkp.sfu.ca/?p=19051","id":"0ec7f039-05d3-4f8b-a832-ba8c6484c701","image":"https://pkp.sfu.ca/wp-content/uploads/2026/05/PKP-AR-2025-WP-1024x576.jpg","images":[{"alt":"PKP community comes together at an annual sprint event, representing that there is no PKP without you!","height":"576","sizes":"(max-width: 1024px) 100vw, 1024px","src":"https://pkp.sfu.ca/wp-content/uploads/2026/05/PKP-AR-2025-WP-1024x576.jpg","srcset":"https://pkp.sfu.ca/wp-content/uploads/2026/05/PKP-AR-2025-WP-1024x576.jpg, https://pkp.sfu.ca/wp-content/uploads/2026/05/PKP-AR-2025-WP-300x169.jpg, https://pkp.sfu.ca/wp-content/uploads/2026/05/PKP-AR-2025-WP-768x432.jpg, https://pkp.sfu.ca/wp-content/uploads/2026/05/PKP-AR-2025-WP-1536x864.jpg, https://pkp.sfu.ca/wp-content/uploads/2026/05/PKP-AR-2025-WP.jpg","width":"1024"},{"alt":"\ud83c\udf89","src":"https://s.w.org/images/core/emoji/17.0.2/72x72/1f389.png"},{"src":"https://pkp.sfu.ca/wp-content/uploads/2026/05/PKP-AR-2025-WP-1024x576.jpg"}],"indexed":true,"indexed_at":1778789948,"language":"en","parent_doi":null,"published_at":1778788655,"reference":[],"registered_at":0,"relationships":[],"rid":"5cmc5-k3m91","status":"active","summary":"\n \n PKP is proud to share its annual report for 2025, covering the period from April 1st, 2025 to March 31st, 2026.\n \n\nAs we reflect on the past year, the 2025 Annual Report offers an opportunity to recognize the strength and dedication of the global community that continues to drive PKP forward. From expanding collaborations to advancing strategic priorities, this year marked meaningful progress on multiple fronts.","tags":["News","News For Developers","News For Hosted Clients","Annual General Meeting","Annual Report"],"title":"What we achieved together in 2025: PKP\u2019s Annual Report is here","updated_at":1778788656,"url":"https://pkp.sfu.ca/2026/05/14/pkp-2025-annual-report/","version":"v1"},{"abstract":null,"archive_url":null,"authors":[{"contributor_roles":[],"name":"Bibliomagician Staff"}],"blog":{"archive_collection":null,"archive_host":null,"archive_prefix":null,"archive_timestamps":null,"authors":[{"name":"Bibliomagician Staff"}],"canonical_url":null,"category":"computerAndInformationSciences","community_id":"f5c1522e-c8de-4681-a317-e32ddb61b26a","created_at":1751825546.966006,"current_feed_url":null,"description":"Comment & practical guidance from the LIS-Bibliometrics community","doi":null,"doi_as_guid":false,"favicon":"https://rogue-scholar.org/api/communities/f5c1522e-c8de-4681-a317-e32ddb61b26a/logo","feed_format":"application/atom+xml","feed_url":"https://thebibliomagician.wordpress.com/feed/atom","filter":null,"funding":null,"generator":"WordPress.com","generator_raw":"WordPress.com","home_page_url":"https://thebibliomagician.wordpress.com/","id":"1068bf8a-6a20-4514-8a34-ff61a63d6d43","indexed":true,"issn":null,"language":"en","license":"https://creativecommons.org/licenses/by/4.0/legalcode","mastodon":null,"prefix":"10.59350","registered_at":0,"relative_url":null,"ror":null,"secure":true,"slug":"bibliomagician","status":"active","subfield":"3309","subfield_validated":null,"title":"The Bibliomagician","updated_at":1778833877.067921,"use_api":null,"use_mastodon":false,"user_id":null},"blog_name":"The Bibliomagician","blog_slug":"bibliomagician","content_html":"When: Thursday 24 September 2026
Where: Lancaster University, UK
The LIS Bibliometrics Conference 2026 invites researchers, practitioners, librarians, information professionals, and policymakers to explore the evolving intersections between AI, bibliometrics, scholarly communication, and research evaluation.
\nAs AI technologies increasingly influence scholarly communication, research assessment, and knowledge production, the conference aims to critically examine both the opportunities and challenges AI presents for bibliometric research and practice.
\nWe are pleased to announce the following keynote speakers:
\nThe conference welcomes submissions related to, but not limited to, the following themes:
\nWe welcome proposals for:
\nFor submission, please use the link below:
Oxford Abstracts
For enquiries, please contact:
lisbibliometricsconference2026@gmail.com
For further information please see the LIS Bibliometrics Conference Webpage and the Call for Contributions.
\n\nWe look forward to welcoming you to Lancaster University (or online) for the LIS Bibliometrics Conference 2026.
\n\nUnless it states other wise, the content of the Bibliomagician is licensed under a Creative Commons Attribution 4.0 International License.
","doi":"https://doi.org/10.59350/k5x2r-xsp29","funding_references":null,"guid":"http://thebibliomagician.wordpress.com/?p=5456","id":"91535190-6eba-4b69-8f8a-9ab578e6582b","image":null,"images":[],"indexed":true,"indexed_at":1778756619,"language":"en","parent_doi":null,"published_at":1778754859,"reference":[],"registered_at":0,"relationships":[],"rid":"68vmx-be074","status":"active","summary":"\n AI Meets Bibliometrics: Advancing Metrics for a Complex Research World\n\n\n When:\n\nThursday 24 September 2026\n\n Where:\n\nLancaster University, UK The LIS Bibliometrics Conference 2026 invites researchers, practitioners, librarians, information professionals, and policymakers to explore the evolving intersections between AI, bibliometrics, scholarly communication, and research evaluation.","tags":["LIS-Bibliometrics Conference","Conference","Lis-Bibliometrics Annual Event","LIS-Bibliometrics Conference 2026"],"title":"First Call for Papers \u2013 LIS Bibliometrics Conference 2026 \u2013 AI Meets Bibliometrics","updated_at":1778755480,"url":"https://thebibliomagician.wordpress.com/2026/05/14/first-call-for-papers-lis-bibliometrics-conference-2026-ai-meets-bibliometrics/","version":"v1"}],"out_of":50152,"page":1,"per_page":10,"total-results":50152}