Most research evaluation still rewards papers, not the work that makes them possible. Yet researchers say up to 75% of a project can be data work: collecting, cleaning, curating, documenting.
https://doi.org/10.1093/reseval/rvag008
Maybe it's time to stop pretending that publications alone represent research.
#OpenScience #ResearchEvaluation #DataCitation #ResponsibleMetrics #Scientometrics
New paper in Research Evaluation explores how researchers actually cite data. Key insight: data citations are far more complex than simple indicators of data reuse.
https://doi.org/10.1093/reseval/rvag008
They reflect scientific practice, community norms, attribution, and even reputation-building. A timely reminder: metrics alone cannot capture the real value of data work.
#OpenScience #DataCitation #ResearchEvaluation #ResponsibleMetrics #Scientometrics
Where do bibliometricians come from? 🤔 A new international study suggests a simple answer: mostly from academic libraries. Around 60% of people doing bibliometric work at universities are based there.
https://doi.org/10.1177/01655515261417634
The catch? Over 70% say they never had formal training in bibliometrics. People simply grow into the role while working with databases, indicators and research analytics.
#bibliometrics #scientometrics #researchmetrics #responsiblemetrics #openscience
New commentary published in #Scientometrics: “Scientific collaboration without flights: Ukraine’s wartime adaptation.”
https://doi.org/10.1007/s11192-026-05576-3
Since 2022, #Ukraine has had no civilian air travel, severely limiting academic mobility. Yet, international co-authorship involving Ukrainian institutions has not declined — it has increased. A small piece on resilience, digital collaboration, and global academic solidarity.
#ResearchCollaboration #OpenScience #ScienceResilience #GlobalScience
#Scientometrics & #Bibliometrics researchers!
#DidYouKnow the #OpenAIREGraph dataset is publicly accessible on #GoogleCloud #BigQuery with full tutorials & use-cases available?
Ready for you to explore, analyze, and discover insights!
✅ Query millions of publications, datasets, software, projects & their relationships
✅ Build custom analytics
✅ Track research impact & collaboration networks
🔗 Learn more https://graph.openaire.eu/docs/cloud-access/
#OpenScience #OpenData #BigQuery #ScholarlyComms #ResearchMetrics
The authors show that European collaboration networks 🇪🇺 remain strongly clustered, largely along geographical and historical lines:
https://doi.org/10.1007/s11192-025-05499-5
While the total volume of international collaboration has grown exponentially, cross-cluster collaboration remains below expectations, even after major EU policy initiatives such as the European Research Area.
#Scientometrics #Collaboration #SciencePolicy #OpenAlex #OpenScience
The study explores a dynamic co-authorship network among European countries between 1990 and 2023 that arose from an interplay of geographical, linguistic, and historical factors which influenced the scientific collaboration. In the analysis, bibliometric data from OpenAlex are used in Indirect Blockmodeling (IB) and Dynamic Stochastic Blockmodeling (DSBM) to examine patterns in three critical periods: rise of the Internet (1994–2003), enlargement of the EU (2004–2013), and the European Research Area (ERA) initiatives (2014–2023). The findings reveal exponential growth in the number of co-authored publications, an overall increase in intra-cluster collaboration, notably in the Balkan, Scandinavian, and Western clusters, coupled with persistent regional disparities. Despite EU policy interventions, collaborations between Western and non-Western regions remain limited. The study shows the need for targeted measures to ensure scientific networks across Europe are more inclusive and balanced.
#Scientometrics & #Bibliometrics researchers!
Did you know the #OpenAIREGraph dataset is publicly accessible on #GoogleCloud #BigQuery, with full tutorials & use-cases available?
Ready for you to explore, analyse, and discover insights!
✅ Query millions of publications, datasets, software, projects & their relationships
✅ Build custom analytics
✅ Track research impact & collaboration networks
Visit https://graph.openaire.eu/docs/cloud-access/
#OpenScience #OpenData #BigQuery #ScholarlyComms #ResearchMetrics
Today at my alma mater, I spoke about how research evaluation is quietly shifting from citations to ChatGPT-style predictions.
👉 https://doi.org/10.13140/RG.2.2.30585.12642
AI can already “detect quality” from text alone, and sometimes performs better than classic metrics. But it doesn’t evaluate science: it rewards what sounds like good science. We may be heading from “publish or perish” to the new absurdity: “write ChatGPT-friendly or perish.”
#AI #ChatGPT #ResearchEvaluation #Scientometrics #LLM #OpenScience
Interestingly, one archival witness remembered Zinaida Mulchenko as a "PhD student from #Kyiv" – an unconfirmed but intriguing Ukrainian thread in the story of a scholar who helped shape global scientometrics.
👉 https://doi.org/10.1162/QSS.a.397
@QSS_ISSI #Scientometrics #MatildaEffect #HistoryOfScience #WomenInScience #Bibliometrics #Ukraine
Abstract. This article revisits the early history of Soviet scientometrics, examining the role of Zinaida Mulchenko in writing Naukometriya – the foundational book in this field. While Vasily V. Nalimov is widely regarded as the sole author of the book, the influence of Mulchenko remains mostly unknown. We argue that her involvement in writing Naukometriya was also significant. To support this claim, we first reveal the key aspects of her biography obtained through the archival research and informants’ testimonies. Then, we compare the content of Naukometriya with Mulchenko’s Ph.D. dissertation, i.e. the first doctoral thesis in scientometrics defended in the Soviet Union, underlying the structural, systematic and content overlaps that question the commonly held view of sole authorship. Such analysis is further accompanied with the track-record of Nalimov-Mulchenko co-authorship reconstruction preceding the years of Naukometriya publication. Finally, we propose that Mulchenko’s diminished positionality as the co-author of the book can be understood through the lens of the Matilda Effect – a systematic under-recognition of women’s contributions to science. Drawing from multi-level analysis, we reconstruct her role in writing the book and identify the reasons that eventually led to Mulchenko’s erasure from the history of Soviet scientometrics.Peer Review. https://www.webofscience.com/api/gateway/wos/peer-review/10.1162/QSS.a.397
#Scientometrics is a direct translation of the Soviet term naukometriya, introduced through the 1969 monograph by Vasily Nalimov and Zinaida Mulchenko. A new paper in @QSS_ISSI reveals that around 15% of that monograph consists of fragments from Mulchenko’s PhD thesis on information flows in science — meaning that many core ideas of Soviet scientometrics were actually hers. Yet she almost disappeared from the historical record = #MatildaEffect
Serhii Nazarovets
The OpenAIRE Graph