Dimensions was introduced as an alternative bibliometric database to the well-established Web of Science (WoS) and Scopus, however all three databases have fundamental differences in coverage and content, resultant from their owners’ indexation philosophies. In light of these differences, we explore here, using a citation network analysis and assessment of normalized citation impact of overlapping publications indexed in all three databases, whether the three databases offer structurally different perspectives of the bibliometric landscape or if they are essentially homogenous substitutes. Our citation network analysis of core and exclusive 2016–2018 publications revealed a large set of core publications indexed in all three databases that are highly self-referential. In comparison, each database selected a set of exclusive publications that appeared to hold similarly low levels of relevance to the core set and to one another, with slightly more internal communication between exclusive publications in Scopus and Dimensions than WoS. Our comparison of normalized citations for 41,848 publications indexed in all three databases found that German sectors were valuated as more impactful in Scopus and Dimensions compared to WoS, particularly for sectors with an applied research focus. We conclude that the databases do present structurally different perspectives, although Scopus and Dimensions with their additional circle of applied research vary more from the more base research-focused WoS than they do from one another.

Objective Foodborne illnesses in Australia, including salmonellosis, are estimated to cost over $A1.25 billion annually. The weather has been identified as being influential on salmonellosis incidence, as cases increase during summer, however time series modelling of salmonellosis is challenging because outbreaks cause strong autocorrelation. This study assesses whether switching models is an improved method of estimating weather–salmonellosis associations. Design We analysed weather and salmonellosis in South-East Queensland between 2004 and 2013 using 2 common regression models and a switching model, each with 21-day lags for temperature and precipitation. Results The switching model best fit the data, as judged by its substantial improvement in deviance information criterion over the regression models, less autocorrelated residuals and control of seasonality. The switching model estimated a 5°C increase in mean temperature and 10 mm precipitation were associated with increases in salmonellosis cases of 45.4% (95% CrI 40.4%, 50.5%) and 24.1% (95% CrI 17.0%, 31.6%), respectively. Conclusions Switching models improve on traditional time series models in quantifying weather–salmonellosis associations. A better understanding of how temperature and precipitation influence salmonellosis may identify where interventions can be made to lower the health and economic costs of salmonellosis.

Despite the growth in the number of bibliometric analyses published in the peer-reviewed literature, few articles provide guidance on methods and reporting to ensure reliability, robustness, and reproducibility. Consequently, the quality of reporting in existing bibliometric studies varies greatly. In response, we are developing a preliminary Guidance List for the repOrting of Bibliometric AnaLyses (GLOBAL), a reporting guideline for bibliometric analyses. This paper outlines a scoping review that aims to identify and categorize bibliometric recommendations from the literature to develop an initial list of candidate items for GLOBAL. Five bibliographic databases, three preprint servers, and gray literature were systematically searched. Twenty-three out of 48,750 records fulfilled the inclusion criteria. Six documents contained bibliometric reporting recommendations based on a complete or partial literature review; all other sources (n = 17) contained opinion-based recommendations. A 32-item recommendation list that will inform the development of GLOBAL was created. A paucity of evidence-based studies on bibliometric reporting exists in the literature, supporting the need to create a reporting guideline for bibliometric analyses. The next step in GLOBAL project will focus on conducting a two-round Delphi study to achieve consensus on which of the 32 items should be included in GLOBAL.

This educational article explores the utility of bibliometrics and altmetrics in evaluating traditional, complementary, and integrative medicine (TCIM) research. We introduce the concept of bibliometrics and altmetrics, provide an overview of the opportunities and challenges in using these analytical techniques, and highlight their future potential in TCIM research. Bibliometrics, based on publication and citation information, offer insights into TCIM research activity, output, scholarly influence, field structure, and collaboration practices. Altmetrics, including social media mentions, downloads, and online bookmarks, can capture the broader societal engagement with TCIM research beyond traditional academic circles. We discuss challenges and opportunities in utilizing these metrics effectively, such as addressing biases, incorporating cultural nuances, and exploring emerging trends. Additionally, we issue a call to action for researchers, policymakers, and practitioners to collaborate and leverage bibliometric and altmetric data to advance evidence-based healthcare practices to promote integrative approaches to health and wellness. By embracing a multidimensional approach to research evaluation, stakeholders can harness the potential of bibliometrics and altmetrics to improve TCIM research and healthcare delivery worldwide.

The primary aims of peer review are to detect flaws and deficiencies in the design and interpretation of studies, and ensure the clarity and quality of their presentation. However, it has been questioned whether peer review fulfils this function. Studies have highlighted a stronger focus of reviewers on critiquing methodological aspects of studies and the quality of writing in biomedical sciences, with less focus on theoretical grounding. In contrast, reviewers in the social sciences appear more concerned with theoretical underpinnings. These studies also found the effect of peer review on manuscripts’ content to be variable, but generally modest and positive. I qualitatively analysed 1430 peer reviewers’ comments for a sample of 40 social science preprint-publication pairs to identify the key foci of reviewers’ comments. I then quantified the effect of peer review on manuscripts by examining differences between the preprint and published versions using the normalised Levenshtein distance, cosine similarity, and word count ratios for titles, abstracts, document sections and full-texts. I also examined changes in references used between versions and linked changes to reviewers’ comments. Reviewers’ comments were nearly equally split between issues of methodology (30.7%), theory (30.0%), and writing quality (29.2%). Titles, abstracts, and the semantic content of documents remained similar, although publications were typically longer than preprints. Two-thirds of citations were unchanged, 20.9% were added during review and 13.1% were removed. These findings indicate reviewers equally attended to the theoretical and methodological details and communication style of manuscripts, although the effect on quantitative measures of the manuscripts was limited.

Academic data infrastructures facilitate bibliometric research and reporting, as they link bibliometric data with research interests. In Germany, the Kompetenznetzwerk Bibliometrie (KB), a national consortium of 22 institutions, serves this purpose by hosting, probing, and curating large-scale bibliometric raw data from commercial and open providers. Users at partner institutions regularly apply the data infrastructure in workflows. Due to its former focus on commercial data, the KB’s infrastructure has not been detailed transparently to date. However, as an increasing number of bibliometric publications and reports rely upon it, this article provides a comprehensive documentation of the KB’s infrastructure specifically designed for bibliometric applications. It explains the conceptual considerations employed to define the infrastructure’s technical characteristics and procedures. Descriptions are provided regarding (1) the technical infrastructure, (2) the KB’s own database schema consistently applied across several bibliometric databases, (3) processing bibliometric raw data, (4) multi-dimensional quality assurance processes, and (5) additional data curation. By making these procedures transparent and open to scrutiny, we aim to bolster the reliability of our infrastructure and facilitate reproducible research while contributing to the broader discourse on transparency in the field of bibliometrics and providing input to other organisations developing similar infrastructures. Peer Review: https://www.webofscience.com/api/gateway/wos/peer-review/10.1162/qss.a.20