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In 2014, a union of German research organisations established Projekt DEAL, a national-level project to negotiate licensing agreements with large scientific publishers. Negotiations between DEAL and Elsevier began in 2016, and broke down without a successful agreement in 2018; in this time, around 200 German research institutions cancelled their license agreements with Elsevier, leading Elsevier to restrict journal access at those institutions. We investigated the effect on researchers' publishing and citing behaviours from a bibliometric perspective, using a dataset of ∼400,000 articles published by researchers at DEAL institutions between 2012-2020. We further investigated these effects with respect to the timing of contract cancellations, research disciplines, collaboration patterns, and article open-access status. We find evidence for a decrease in Elsevier’s market share of articles from DEAL institutions, with the largest year-on-year market share decreases occuring from 2018 to 2020 following the implementation of access restrictions. We also observe year-on-year decreases in the proportion of citations, although the decrease is smaller. We conclude that negotiations with Elsevier and access restrictions have led to some reduced willingness to publish in Elsevier journals, but that researchers are not strongly affected in their ability to cite Elsevier articles, implying that researchers use other methods to access scientific literature. Im Jahr 2014 gründete ein Zusammenschluss deutscher Forschungsorganisationen das Projekt DEAL, ein Projekt auf nationaler Ebene zur Aushandlung von Lizenzverträgen mit großen Wissenschaftsverlagen. Die Verhandlungen zwischen DEAL und Elsevier begannen 2016 und scheiterten 2018 ohne eine erfolgreiche Einigung; in dieser Zeit kündigten rund 200 deutsche Forschungseinrichtungen ihre Lizenzverträge mit Elsevier, was Elsevier dazu veranlasste, den Zeitschriftenzugang für diese Einrichtungen zu beschränken. Die Autor*innen untersuchten die Auswirkungen auf das Publikations- und Zitierverhalten von Forschenden aus bibliometrischer Sicht anhand eines Datensatzes von ∼400.000 Artikeln, die von Forschenden an DEAL-Einrichtungen zwischen 2012-2020 veröffentlicht wurden.

Author affiliations provide key information when attributing academic performance like publication counts. So far, such measures have been aggregated either manually or only to top-level institutions, such as universities. Supervised affiliation resolution requires a large number of annotated alignments between affiliation strings and known institutions, which are not readily available. We introduce the task of unsupervised hierarchical affiliation resolution, which assigns affiliations to institutions on all hierarchy levels (e.g. departments), discovering the institutions as well as their hierarchical ordering on the fly. From the corresponding requirements, we derive a simple conceptual framework based on the subset partial order that can be extended to account for the discrepancies evident in realistic affiliations from the Web of Science. We implement initial baselines and provide datasets and evaluation metrics for experimentation. Results show that mapping affiliations to known institutions and discovering lower-level institutions works well with simple baselines, whereas unsupervised top-level- and hierarchical resolution is more challenging. Our work provides structured guidance for further in-depth studies and improved methodology by identifying and discussing a number of observed difficulties and important challenges that future work needs to address.

National audience; Research activities are generally observed and evaluated through the prism of their production and financial elements or team composition. In addition to standardized management indicators and bibliometrics, the French National Research Institute for Sustainable Development (IRD) has been building new indicators for the last ten years, based on the annual regulatory declarations of the Institute's researchers. Different quality management tools allow the evolution of the different interfaces. This source of data, more "open" and more "useful" through its integration into the Institute's information system, is adapted to the needs of the multi-year management of research at the IRD. The aim is twofold: (1) to make progress in the evaluation of research and in the mastery of information by all actors, (2) to enlighten as many actors as possible via more efficient digital circuits and tools. The purpose of this article is to explain how the IRD is changing the entire production chain and the indicators of researchers' activities to better map scientific activities.; Les activités de la recherche sont généralement observées et évaluées à travers le prisme de leur production et des éléments financiers ou de compositions des équipes. En plus des indicateurs de gestion standardisés et bibliométriques, l’IRD poursuit depuis une dizaine d’années la construction de nouveaux indicateurs, sur la base des déclarations annuelles réglementaires des chercheurs de l’Institut. Différents outils du management qualité permettent l’évolution des différentes interfaces. Cette source de données, plus « ouverte » et plus « utile » par son intégration dans le système d’informations de l’Institut est adaptée aux besoins du pilotage pluriannuel de la recherche à l’IRD. La finalité est double : (1) progresser dans l’évaluation de la recherche et dans la maîtrise de l’information par tous les acteurs, (2) éclairer précisément le plus d’acteurs possibles via des circuits et des outils numériques plus efficients. L’objet du présent article est d’exposer la conduite à l’IRD du changement sur toute la chaîne de production et sur les indicateurs d’activités des chercheurs et chercheuses pour une meilleure cartographie des activités scientifiques.

“Big” digital behavioral data increasingly allows large-scale and high-resolution analyses of the behavior and performance of persons or aggregated identities in whole fields. Often the desired system of study is only a subset of a larger database. The task of drawing a field boundary is complicated because socio-cultural systems are highly overlapping. Here, I propose a sociologically enhanced information retrieval method to delineate fields that is based on the reproductive mechanism of fields, able to account for field heterogeneity, and generally applicable also outside scientometric, e.g., in social media, contexts. The method is demonstrated in a delineation of the multidisciplinary and very heterogeneous Social Network Science field using the Web of Science database. The field consists of 25,760 publications and has a historical dimension (1916–2012). This set has high face validity and exhibits expected statistical properties like systemic growth and power law size distributions. Data is clean and disambiguated. The dataset with 45,580 author names and 23,026 linguistic concepts is publically available and supposed to enable high-quality analyses of an evolving complex socio-cultural system.

A potential motivation for scientists to deposit their scientific work as preprints is to enhance its citation or social impact. In this study we assessed the citation and altmetric advantage of bioRxiv, a preprint server for the biological sciences. We retrieved metadata of all bioRxiv preprints deposited between November 2013 and December 2017, and matched them to articles that were subsequently published in peer-reviewed journals. Citation data from Scopus and altmetric data from Altmetric.com were used to compare citation and online sharing behavior of bioRxiv preprints, their related journal articles, and nondeposited articles published in the same journals. We found that bioRxiv-deposited journal articles had sizably higher citation and altmetric counts compared to nondeposited articles. Regression analysis reveals that this advantage is not explained by multiple explanatory variables related to the articles’ publication venues and authorship. Further research will be required to establish whether such an effect is causal in nature. bioRxiv preprints themselves are being directly cited in journal articles, regardless of whether the preprint has subsequently been published in a journal. bioRxiv preprints are also shared widely on Twitter and in blogs, but remain relatively scarce in mainstream media and Wikipedia articles, in comparison to peer-reviewed journal articles.

With the aim of developing a reflection on the documental level of geography, and to understand how physical and human geography are materially related, this paper analyzes an ample spectrum of indexed literature from a distant reading perspective based on scientometric tools. Moving under a sociology of science lens, the study address (I) the citational relationship between the two fields, and (II) how scientific articles in geography are mobilised and combined with different categories of research journals in a cognate scientific field. The study relies on science mapping techniques to chart, describe, and visualize the citational relationships among journals and fields. Dans le but de développer une réflexion sur la production de publications de la géographie et de comprendre comment la géographie physique et la géographie humaine sont matériellement liées, cet article analyse un large éventail de littérature indexée dans une perspective basée sur des outils scientométriques. Se déplaçant sous le prisme de la sociologie des sciences, l'étude aborde (I) la relation des citations entre les deux domaines et (II) la manière dont les articles scientifiques en géographie sont mobilisés et combinés avec différentes catégories de revues de recherche dans des domaines de recherche apparentés. L'étude s'appuie sur des techniques de cartographie de la science (« science mapping ») pour tracer, décrire et visualiser les relations de référence entre les revues et les domaines.

Au cours du XIXe siècle, et au début du XXe, le recensement et le catalogage des articles s’accompagnent d’une indexation par auteur de la production scientifique. C’est l’utilisation de la citation comme indicateur d’influence, qui ouvrira la voie à la bibliométrie, et aux études quantitatives de la science. Nous présentons les principaux éléments du débat relatif aux taux de citation et des facteurs d’impact, et à l’usage d’indicateurs numériques dans les processus d’évaluation. Le développement de la Science Ouverte ouvre une nouvelle étape, avec l’exigence d’une utilisation responsable de la bibliométrie et des données quantitatives. During the 19th century, and at the beginning of the 20th century, the inventory and cataloging of articles was accompanied by indexes of scientific production by author. It is the use of citation as an indicator of influence, which paves the way for bibliometrics, and for quantitative studies of science. We present the main elements of the debate relating to citation rates and impact factors, and the use of numerical indicators in evaluation processes. The development of Open Science opens a new stage, with the demand for responsible use of bibliometrics and quantitative data.

Unter den vielen positiven Aspekten, die mit internationaler Mobilität assoziiert werden, ist der Wissenstransfer besonders wichtig. Möglich ist dies u. a. über international mobile Forschende, die als Wissensvermittelnde fungieren können, indem sie relevantes Wissen im Ausland erwerben und es in ihr Heimatland transferieren. Es ist jedoch wenig darüber bekannt, wie und welches Wissen übertragen wird, da es an Methoden mangelt, dies zu belegen. In diesem Beitrag wird zum einen das Potenzial bibliometrischer Analysen aufgezeigt, die für die Erfassung des Wissenstransfers international mobiler Forschender entwickelt worden sind. Die bibliometrischen Methoden greifen hierfür auf Autorennetzwerke, Zitationsnetzwerke und lexikalische Verfahren zurück, u. a. zur Bestimmung selten gebrauchter Begriffskombinationen, die explizite Wissensinhalte repräsentieren. Zum anderen werden die mit diesen Methoden gewonnenen Ergebnisse vorgestellt, darunter exemplarisch das im Ausland erworbene Wissen von Forschenden.

Cet article présente les travaux en traductologie à l’université d’Alger. Il montre la naissance d’une nouvelle génération de traductologues en Algérie et nous emmène sur le chemin de la scientométrie qui permet d’analyser et de mesurer les productions scientifiques dans le domaine de la traduction. Cette contribution conclut sur la distinction qui tend à s’imposer graduellement entre traductologie et linguistique dans ce pays.

The 12th iteration of the Bibliometric-enhanced Information Retrieval (BIR) workshop series is a full-day ECIR 2022 workshop. BIR tackles issues related to, for instance, academic search and recommendation, at the intersection of Information Retrieval, Natural Language Processing, and Bibliometrics. As an interdisciplinary scientific event, BIR brings together researchers and practitioners from the Scientometrics/Bibliometrics community on the one hand and the Information Retrieval community on the other hand. BIR is an ever-growing topic investigated by both academia and the industry.

Le libre accès est un processus qui vise à rendre les résultats de recherche disponibles gratuitement en ligne, permettant de lire, télécharger, copier, distribuer, imprimer, rechercher ou partager leur contenu, sans barrière légale ou technique. Le mouvement a récemment gagné de l’ampleur avec l’implémentation de politiques de libre accès par les organismes subventionnaires et le développement de plateformes facilitant la diffusion de la science telles que l’Open Journal System, Érudit et SciELO. Actuellement, des études estiment que près de la moitié des articles scientifiques sont disponibles en ligne gratuitement. À ce jour, plusieurs aspects du libre accès ont été abordés dans la littérature scientifique tels que la disponibilité des articles, l’avantage en termes de citations des articles en libre accès et les effets des politiques de libre accès. Cependant, peu de chercheurs ont abordé l’utilisation du libre accès à l’échelle mondiale. L’objectif de ce mémoire de maîtrise est de fournir un portrait à jour de l’adoption du libre accès à l’échelle globale selon deux indicateurs, soit le nombre de publications en libre accès et le nombre de références faites aux articles en libre accès. Nos résultats montrent que les pays pauvres publient et utilisent davantage la recherche en libre accès que les autres pays, tandis que les pays ayant un revenu intermédiaire de la classe supérieure se comportent d’une façon semblable aux pays riches. Ces résultats démontrent l’importance des initiatives pour la promotion du libre accès à l’échelle locale, nationale et internationale, particulièrement pour les pays de la classe de revenu intermédiaire où les infrastructures et le nombre de mandats de libre accès sont limités., Open Access (OA) is a process that aims to make research output freely available on the public internet, allowing the users to read, download, copy, distribute, print, search or link to the full text without any financial, legal or technical barrier. OA has often been suggested as a potential solution to several problems related to the scientific publishing industry: a minority of for profit editors accounting for half of the entire publishing industry, important budget cuts and rising subscription prices in academic libraries, and access to knowledge in lower-income countries. The OA movement originated from the growing demand to make research more accessible worldwide. It has been gaining a lot of momentum, with the implementation of several OA policies by funding institutions and the development of several new platforms (e.g., Open Journal System, African Journals Online, SciELO, and Érudit) that facilitate the publication of OA content at low cost. Studies have shown that between 20% and 50% of research articles are currently available online at no cost, but only a few have compared the use of OA literature at the country level and from a worldwide perspective. Along these lines, this master’s thesis aims to provide a global picture of the current state of OA adoption by countries, using two indicators: publications in OA and references to articles in OA. We find that, on average, low-income countries are publishing and citing OA at the highest rate, while upper-middle income countries and higher income countries publish and cite OA articles at below world-average rates. These results highlight national differences in OA uptake and suggest that more OA initiatives at the institutional, national and international levels are needed to support a wider adoption of open scholarship.

Citation metrics have value because they aim to make scientific assessment a level playing field, but urgent transparency-based adjustments are necessary to ensure that measurements yield the most accurate picture of impact and excellence. One problematic area is the handling of self-citations, which are either excluded or inappropriately accounted for when using bibliometric indicators for research evaluation. Here, in favor of openly tracking self-citations we report on self-referencing behavior among various academic disciplines as captured by the curated Clarivate Analytics Web of Science database. Specifically, we examined the behavior of 385,616 authors grouped into 15 subject areas like Biology, Chemistry, Science & Technology, Engineering, and Physics. These authors have published 3,240,973 papers that have accumulated 90,806,462 citations, roughly five percent of which are self-citations. Up until now, very little is known about the buildup of self-citations at the author-level and in field-specific contexts. Our view is that hiding self-citation data is indefensible and needlessly confuses any attempts to understand the bibliometric impact of one’s work. Instead we urge academics to embrace visibility of citation data in a community of peers, which relies on nuance and openness rather than curated scorekeeping.

Rapport pour la DGLF sur la publication francophone et sa présence dans les référentiels internationaux

In bibliometrischen Analysen werden häufig Zitationsbeziehungen dazu genutzt thematische Cluster in Forschungsfeldern zu identifizieren. Aufgrund mangelnder Informationen wird dabei nicht zwischen verschiedenen thematischen Bezügen der Zitierungen unterschieden, also ob sich ein Zitat auf etwa eine Theorie, eine Methode, einen Forschungsgegenstand oder anderes bezieht. In thematischen Mappings vermischen sich diese Bezüge und sind nicht mehr zu unterscheiden. Es wurde bisher nicht systematisch untersucht, ob und wie diese Vermischung das Mapping beeinflusst. Die vorliegende Arbeit beschäftigt sich mit (1) der Analyse epistemischer Funktionen von Zitationsbeziehungen und (2) deren Auswirkungen auf das bibliometrische Mapping thematischer Strukturen. Dazu werden im ersten Teil der Analyse die Referenzen einer begrenzten Anzahl an Publikationen nach ihrer Funktion kodiert und ausgewertet und im zweiten Teil der Analyse Netzwerkkarten unter Berücksichtigung der Zitationsfunktionen erstellt und analysiert. Dabei werden Methoden der qualitativen Inhaltsanalyse und netzwerkanalytische Verfahren eingesetzt.

In recent years, increased stakeholder pressure to transition research to Open Access has led to many journals converting, or 'flipping', from a closed access (CA) to an open access (OA) publishing model. Changing the publishing model can influence the decision of authors to submit their papers to a journal, and increased article accessibility may influence citation behaviour. In this paper we aimed to understand how flipping a journal to an OA model influences the journal's future publication volumes and citation impact. We analysed two independent sets of journals that had flipped to an OA model, one from the Directory of Open Access Journals (DOAJ) and one from the Open Access Directory (OAD), and compared their development with two respective control groups of similar journals. For bibliometric analyses, journals were matched to the Scopus database. We assessed changes in the number of articles published over time, as well as two citation metrics at the journal and article level: the normalised impact factor (IF) and the average relative citations (ARC), respectively. Our results show that overall, journals that flipped to an OA model increased their publication output compared to journals that remained closed. Mean normalised IF and ARC also generally increased following the flip to an OA model, at a greater rate than was observed in the control groups. However, the changes appear to vary largely by scientific discipline. Overall, these results indicate that flipping to an OA publishing model can bring positive changes to a journal., 16 pages, 5 figures, Accepted in Scientometrics

Google Scholar (GS) is a free tool that may be used by researchers to analyze citations, to find appropriate literature or to evaluate the quality of an author or a contender for tenure, promotion, a faculty position, funding or research grants. GS has become a major bibliographic and citation database. Following the literature, databases such as PubMed, PsycINFO, Scopus or Web of Science can be used in place of GS because they are more reliable. The aim of this study is to examine the accuracy of citation data collected from GS and provide a comprehensive description of the errors and miscounts identified. For this purpose, 281 documents that cited two specific works were retrieved from the Publish or Perish software and examined. This work studied the false positive issue inherent in the analysis of neuroimaging data. The results reveal an unprecedented error rate: 279 of 281 examined references (99.3%) contain at least one error. The nonacademic documents tend to contain more errors than academic publications (U=5117.0, P, L’objectif de la présente étude est d’explorer les données extraites de Google Scholar via le logiciel Publish or Perish afin de fournir une description détaillée et quantifiée des erreurs rencontrées. Pour ce faire, nous avons examiné les 174 documents citant un poster et un article visant à sensibiliser la communauté scientifique sur la question des faux positifs en neuroimagerie. Les résultats obtenus montrent un taux d’erreur sans précédent : 99,3 % des références examinées contiennent au moins une erreur. En conséquence, le chercheur ne peut raisonnablement pas exploiter les données Google Scholar sans s’exposer à de nombreuses erreurs, générant autant de biais dans les analyses et résultats produits.