Dataset for "A Case Study Exploring Associations Between Popular Media Attention of Scientific Research and Scientific Citations"Legend: LeadH= Lead author H-index (WoS)InstH= Institutional rank (Shanghai)CorrH= Corresponding author H-index (WoS)Scopus= Scopus citation count WoS=Web of Science citation countFWCit= Field-weighted citation impact (Scopus)AbsViews= Abstract views (Scopus)Mendeley= Mendeley readersJIFPerc= Journal Impact Factor percentile (in WoS Sports sciences category)Impact1= 1 year JIF (WoS)Impact5= 5 year JIF (WoS)Altmetric= Altmetric Attention ScoreSocMedia= Social media mentions (Facebook + Twitter collected via Altmetric)

The study identifies citation predictors of Russian scientific publications on psychology in the Web of Science Core Collection (WoS) and compares them with citation predictors in the Russian Science Citation Index (RSCI). Four groups of indicators of various types are considered: formal attributes of the article (12 parameters), article visibility parameters on the eLibrary (3 parameters) and PsyJournals (2 parameters) internet portals, showing the availability of the article text to potential readers, and attributes of the author’s method of scientific citation (3 parameters). Special attention is paid to citation attributes as qualitative characteristics of the author’s way of working on his own scientific text and constructing a dialogue (in the form of citation) with other researchers.

The all.zip CSV file (zipped) contains citation counts obtained from the November 2018 dump of COCI (https://doi.org/10.6084/m9.figshare.6741422.v3) and some metadata (title, DOI, number of authors, ISBN, ISBN of the container, type of the bibliographic resource) of the related citing and cited entities obtained by using the Crossref dump downloaded in October 2018 – which is the same dump used to create the COCI data.

In addition, it contains all the Library of Congress Classification (LCC) categories associated with each ISBN in the previous dataset (file isbn_cat_lcc.csv), according to the data retrieved using the services at http://classify.oclc.org/classify2/api_docs/index.html. Two ancillary mapping files have been also added: one (ddc_to_lcc_mapping.csv) for converting a Dewey Decimal Classification (DDC) categories into LCC categories, in the case the service mentioned above returned only DDC categories for some ISBN; the other (lcc_to_wos_mapping.csv) to map each LCC category into the related Web of Science research area.

Direct enzyme activity analysis using tandem mass spectrometry (MS/MS), fluorometry, or immunoassays, as well as biomarker measurements are currently available techniques for screening for lysosomal storage diseases (LSDs). The presented study aims to provide a bibliometric analysis of the published literature on methods used for LSD screening assays and to identify future research trends in this field. We performed a systematic search for articles in the Web of Science Core Collection (WoS CC), covering the period 1982 to 2024 (June). A total of 901 articles written by 5303 authors, published in 389 journals, with 24,934 citations in 15,256 citing articles, with an average citation rate of 27.67 per article and an h-index of 78 were retrieved from WoS CC. The indicators presented in the article describe the network structure of the scientific community in the study area at the level of countries, institutions, authors, articles, sources, and keywords, as well as evaluate their productivity, collaboration, and citations. The most relevant current and future areas of interest were identified: “development of more accurate, sensitive, reliable and accessible tests”, “increasing the use of next-generation sequencing”, “ethical issues related to LSD screening”, “metabolomic and proteomic approaches” and “pathogenic variants of LSD genotypes”.

Hipsley, C. A. & Sherratt, E. Literature and survey data for: Psychology, not technology, is our biggest challenge to open digital morphology data. Excel file containing 3 worksheets:1) Literature summary: Data accompanying Figure 1a. Number of publications per year retrieved through Web of Science’s Science Citation Index Expanded using the topic search terms: x-ray comput* tomograph* OR CT; magnetic resonance imag* OR MRI; synchrotron; photogrammetr*. Articles were limited to the Web of Science categories Anatomy Morphology, Evolutionary Biology, Paleontology, and Zoology. Results for 2018 are not shown. Only three articles prior to 1980 were recovered. Search performed on 25 June 2018.2) CT papers: Data accompanying Figure 1b. 50 publications including CT data published in the past 5 years in Anatomical Record, Journal of Anatomy, Journal of Morphology, Journal of Vertebrate Paleontology, and Zoological Journal of the Linnean Society (10 papers each). These journals were among the top 10% of publishers including CT data recovered in our literature search.3) Survey responses: Includes data accompanying Figure 2. Responses to an online survey generated in Google Docs and posted to the MORPHMET and geomorph discussion groups. Results can also be found here:https://docs.google.com/forms/d/1hZr2QyN3a7Sh1BlaXOPumnUlqLm_MN-SkwmyuQLsO3c/edit#responses

BackgroundParkinson’s disease (PD) is a prevalent neurodegenerative disorder affecting millions globally. It encompasses both motor and non-motor symptoms, with a notable impact on patients’ quality of life. Electroencephalogram (EEG) is a non-invasive tool that is increasingly utilized to investigate neural mechanisms in PD, identify early diagnostic markers, and assess therapeutic responses.MethodsThe data were sourced from the Science Citation Index Expanded within the Web of Science Core Collection database, focusing on publications related to EEG research in PD from 2004 to 2023. A comprehensive bibliometric analysis was conducted using CiteSpace and VOSviewer software. The analysis began with an evaluation of the selected publications, identifying leading countries, institutions, authors, and journals, as well as co-cited references, to summarize the current state of EEG research in PD. Keywords are employed to identify research topics that are currently of interest in this field through the analysis of high-frequency keyword co-occurrence and cluster analysis. Finally, burst keywords were identified to uncover emerging trends and research frontiers in the field, highlighting shifts in interest and identifying future research directions.ResultsA total of 1,559 publications on EEG research in PD were identified. The United States, Germany, and England have made notable contributions to the field. The University of London is the leading institution in terms of publication output, with the University of California closely following. The most prolific authors are Brown P, Fuhr P, and Stam C In terms of total citations and per-article citations, Stam C has the highest number of citations, while Brown P has the highest H-index. In terms of the total number of publications, Clinical Neurophysiology is the leading journal, while Brain is the most highly cited. The most frequently cited articles pertain to software toolboxes for EEG analysis, neural oscillations, and PD pathophysiology. Through analyzing the keywords, four research hotspots were identified: research on the neural oscillations and connectivity, research on the innovations in EEG Analysis, impact of therapies on EEG, and research on cognitive and emotional assessments.ConclusionThis bibliometric analysis demonstrates a growing global interest in EEG research in PD. The investigation of neural oscillations and connectivity remains a primary focus of research. The application of machine learning, deep learning, and task analysis techniques offers promising avenues for future research in EEG and PD, suggesting the potential for advancements in this field. This study offers valuable insights into the major research trends, influential contributors, and evolving themes in this field, providing a roadmap for future exploration.

Most productive journals with at least 600 COVID-19 publications indexed in the Web of Science 2020–2023.

This study aims to analyze the adoption of Open Access (OA) publishing in social sciences within central universities in India, focusing on various aspects such as the growth of OA literature, the utilization of different OA routes, and collaboration patterns in OA publications.Ten central universities were selected based on their rankings in the National Institute Ranking Framework (NIRF) 2022. Data on OA publishing in social sciences were collected from the Social Science Citation Index of the Web of Science database using the advanced search query "(CU=India OR AD=India) AND PY=(2003-2022) NOT PY=(2023)". Data analysis was conducted using MS Excel (v16.0), BibExcel (version - 2017), Biblioshiny (version 4.1.2), and Google Open Refine (version 3.7).

This database is a subset of a bigger dataset on fish richness data extracted from published studies used to perform a meta-analysis on the impacts of dams and reservoirs on fish biodiversity and fish assemblages https://doi.org/10.6084/m9.figshare.7938167.v1. The studies were compiled from journal indexed in Web of Science Core collection, BIOSIS citation index, Current Content Connect, Data citation Index, SciELO Citation index and Zoological records databases from Thomson ISI's Web of Science and Google Scholar (peer-reviewed articles, textbooks and reports). This EXCEL file contains 1 sheet with the metadata and 1 sheet with observed fish richness over time with the associated reference.

The “failed/fragile/collapsed state” refers to state authority's complete or partial collapse, such as Somalia and Bosnia. According to Fragile States Index 2020 annual report, approximately 116 countries among 178 countries were in warning or alerting state quo, which hurts three-quarters of the world's population. A systematic scientometric interpretation of failed/fragile/collapsed state analysis would be helpful but is presently absent in the academic community. This review makes three donations by evaluating the 2,417 articles published in the Web of Science (WoS) Social Science Citation Index (SSCI) Collection between 1990 and 2020. First, it provides a unique prospect in failed/fragile/collapsed state studies through a detailed, systematic, and objective analysis. Second, the author has quantitatively tracked the progression of failed/fragile/collapsed state studies from 1990 to 2020. Finally, the author associated evolutionary trajectory analysis with future research directions, offering new pathways for failed/fragile/collapsed state studies. It also helps novice “failed/fragile/collapsed state” researchers and veteran scholars identify future research trends.

Definitions and taxonomy used for the classification of health-related claims. Column headings used for data extraction. Search strategies used for MEDLINE, EMBASE, PsychINFO, CAB abstracts, Business Source Complete, and Web of Science/Science Citation Index & Social Science Citation Index. Data extracted for the risk of bias assessment. Completed PRISMA systematic review checklist. (ZIP 90 kb)

Comprehensive and visual assessments utilizing Geographic Information Systems (GIS) offer an empirical foundation for the planning, construction, and optimization of Urban Green Infrastructure (UGI), effectively promoting its sustainable development. A comprehensive review of this field clarifies the research methods, application scope, trends, and challenges associated with using GIS to advance UGI development. This study synthesizes research findings from the Science Citation Index (SCI) and Social Science Citation Index (SSCI) within the Web of Science (WOS) database, as well as from the Scopus database, for the period from January 1, 2020, to June 30, 2024. The initial dataset included 640 articles from WOS and 952 articles from Scopus. After removing 1,572 duplicates and irrelevant studies, the final selection consisted of 20 articles. The integration of both WOS and Scopus databases ensures a comprehensive capture of current trends and limitations in GIS-based UGI assessments. This study centers on the scope, data sources, theoretical models, analyses, and objectives of GIS-based UGI assessments. The research indicates that over the past five years, GIS-based UGI assessments have primarily focused on areas such as accessibility, ecosystem service potential, resilience, and environmental justice, in addition to non-ecological aspects such as social benefits and aesthetics. While the integration of diverse data and analytical indicators into GIS has enhanced assessment comprehensiveness, and AI technologies have deepened data analysis, field research with urban residents remains crucial, underscoring the importance of inclusiveness in the study. This study also reveals a significant increase in interdisciplinarity in GIS-based assessments of UGI. The integration of assessment methods from ecology, computer science, urban planning, sociology, aesthetics, and other disciplines demonstrates that research in this field has fully considered ecological, social, economic, and humanistic factors, thereby more comprehensively reflecting the integrated needs of sustainable urban development.

These databases contain information from published studies used to perform a meta-analysis on the impacts of dams and reservoirs on fish biodiversity and fish assemblages. The studies were compiled from journal indexed in Web of Science Core collection, BIOSIS citation index, Current Content Connect, Data citation Index, SciELO Citation index and Zoological records databases from Thomson ISI's Web of Science and Google Scholar (peer-reviewed articles, textbooks and reports). This EXCEL file contains two databases; one longitudinal studies (LD) database and associated metadata and one cross-sectional (CS) database with associated metadata.

Global maps of science can be used as a reference system to chart career trajectories, the location of emerging research frontiers, or the expertise profiles of institutes or nations. This paper details data preparation, analysis, and layout performed when designing and subsequently updating the UCSD map of science and classification system. The original classification and map use 7.2 million papers and their references from Elsevier’s Scopus (about 15,000 source titles, 2001–2005) and Thomson Reuters’ Web of Science (WoS) Science, Social Science, Arts & Humanities Citation Indexes (about 9,000 source titles, 2001–2004)–about 16,000 unique source titles. The updated map and classification adds six years (2005–2010) of WoS data and three years (2006–2008) from Scopus to the existing category structure–increasing the number of source titles to about 25,000. To our knowledge, this is the first time that a widely used map of science was updated. A comparison of the original 5-year and the new 10-year maps and classification system show (i) an increase in the total number of journals that can be mapped by 9,409 journals (social sciences had a 80% increase, humanities a 119% increase, medical (32%) and natural science (74%)), (ii) a simplification of the map by assigning all but five highly interdisciplinary journals to exactly one discipline, (iii) a more even distribution of journals over the 554 subdisciplines and 13 disciplines when calculating the coefficient of variation, and (iv) a better reflection of journal clusters when compared with paper-level citation data. When evaluating the map with a listing of desirable features for maps of science, the updated map is shown to have higher mapping accuracy, easier understandability as fewer journals are multiply classified, and higher usability for the generation of data overlays, among others.

Analysis of literature performance metrics for the field of bioinformatics, across countries (up to 31-Dec-2019).Data supplement for the manuscript "The bioinformatics wealth of nations" by Anastasia Chasapi, Vasilis J. Promponas, Christos A. Ouzounis (bioinformatics/btaa132 Bioinformatics: 36, 2963) (2020).Legends:

Table S1

List of countries and territories (column A) with their output in terms of publications (B), citations (C), citations/publication (D) and the H-index (E) for bioinformatics (WoS query: 'all fields'). Reported by sorting values in column E.

Table S2

List of 40 top-producer countries (A) for bioinformatics, with 7 indices: - four primary indices: publications (B, and rank: C), citations (D, and rank: E), citations/ publication (F, and rank: G), H-index (H, and rank: I) - rank of countries with top 1% highly cited publications (J) - two population (K, in thousand inhabitants) normalized indices: publications per million (L=1000*B/K, and rank: M) H-index per million (N=1000*H/K, and rank: O)

Background: Myofascial trigger points (MTrPs) are a common feature of musculoskeletal pain, and dry needling (DN) has emerged as a widely used non-pharmacological treatment since 1979. This study aimed to conduct a comprehensive bibliometric analysis of DN research related to MTrPs.Methods: Data from Scopus and Web of Science (1979–2024) were analyzed using ScientoPy, Biblioshiny, VOSviewer, and Microsoft Excel to assess publication trends, authorship, keyword patterns, and institutional contributions.Results: A total of 618 documents with 14,733 citations were identified. Journal articles were the most common publication type (n = 487; 10,067 citations). Research activity peaked in 2021 (72 publications). The United States of America (USA) (191 publications) and Spain (155 publications) were the most prolific countries. Universidad Rey Juan Carlos led institutional output (80 publications), and Fernandez-De-Las-Peñas was the most productive author (48 publications). The Journal of Bodywork and Movement Therapies published the most articles (n = 62), while the Archives of Physical Medicine and Rehabilitation had the highest citation impact (961 citations). The most cited article was Hong’s 1994 study comparing lidocaine injection with dry needling (500 citations). Frequently used keywords included “dry needling,” “trigger point,” and “myofascial pain syndrome.”Conclusion: DN research has grown steadily, particularly since 2010, with significant contributions from the USA and Spain. Expanding geographic diversity and cross-cultural research will be essential to strengthening the global evidence base and improving clinical applications of dry needling.

BackgroundPrevious systematic reviews have identified the benefits of exercise for chronic neck pain on subjective reports of pain, but not with objective measures such as quantitative sensory testing (QST). A systematic review was conducted to identify the effects of neck specific exercise on QST measures in adults with chronic neck pain to synthesise existing literature and provide clinical recommendations.MethodsThe study protocol was registered prospectively with PROSPERO (PROSPERO CRD42021297383). For both randomised and non-randomised trials, the following databases and trial registries were searched: AMED, CINAHL, Embase, Google Scholar, Medline, PEDro, PubMed, Scopus, SPORTDiscus, Science Citation Index and Social Science Citation Index from Web of Science Core Collection, clinicaltrials.gov, GreyOpen, and ISRCTN registry. These searches were conducted from inception to February 2022 and were updated until September 2023. Reference lists of eligible studies were screened. Study selection was performed independently by two reviewers, with data extraction and quality appraisal completed by one reviewer and independently ratified by a second reviewer. Due to high heterogeneity, narrative synthesis was performed with results grouped by exercise type.FindingsThree trials were included. Risk of bias was rated as moderate and the certainty of evidence as low or moderate for all studies. All exercise groups demonstrated statistically significant improvement at an intermediate-term follow-up, with progressive resistance training combined with graded physical training demonstrating the highest certainty of evidence. Fixed resistance training demonstrated statistically significant improvement in QST measures at a short-term assessment.InterpretationFixed resistance training is effective for short-term changes in pain sensitivity based on low-quality evidence, whilst moderate-quality evidence supports progressive resistance training combined with graded physical training for intermediate-term changes in pain sensitivity.

BackgroundThe beneficial effects of cardiac rehabilitation (CR) have been challenged in recent years and there is now a need to investigate whether current CR programmes, delivered in the context of modern cardiology, still benefit patients.MethodsA systematic review of non-randomised controlled studies was conducted. Electronic searches of Medline, Embase, CINAHL, science citation index (web of science), CIRRIE and Open Grey were undertaken. Non-randomised studies investigating the effects of CR were included when recruitment occurred from the year 2000 onwards in accordance with significant CR guidance changes from the late 1990’s. Adult patients diagnosed with acute myocardial infarction (AMI) were included. Non-English articles were considered. Two reviewers independently screened articles according to pre-defined selection criteria as reported in the PROSPERO database (CRD42015024021).ResultsOut of 2,656 articles, 8 studies involving 9,836 AMI patients were included. Studies were conducted in 6 countries. CR was found to reduce the risk of all-cause and cardiac-related mortality and improve Health-Related Quality of Life (HRQOL) significantly in at least one domain. The benefits of CR in terms of recurrent MI were inconsistent and no significant effects were found regarding re-vascularisation or re-hospitalisation following AMI.ConclusionRecent observational evidence draws different conclusions to the most current reviews of trial data with respect to total mortality and re-hospitalisation, questioning the representativeness of historic data in the modern cardiological era. Future work should seek to clarify which patient and service level factors determine the likelihood of achieving improved all-cause and cardiac mortality and reduced hospital re-admissions.

BackgroundAnesthesiology research is growing at a rapid pace. It is essential to understand the scope and trends over time to identify gaps and future areas for growth. Systematic reviews and meta-analyses (SRMA) are summaries of the best available evidence to address a specific research question via a comprehensive literature search, in-depth analyses, and synthesis of results. High-quality SRMA are increasingly used and play an essential role in medical research.ObjectiveWe aimed to explore the trends of SRMA in indexed anesthesia journals.MethodsSRMA published in indexed anesthesia journals from 2013 to 2023 were retrieved from the Web of Science database. Data were presented via descriptive statistics. We used CiteSpace 6.1.R6 to analyze countries, institutions, journals, authors, and keywords through visual maps to explore the research hotspots and trends. The journal’s Journal Citation Reports partition, impact factor, annual publications, journals H-index, and a number of highly-cited papers were calculated in the WoS database.ResultsA total of 34 indexed anesthesia journals and 3,004 SRMA were included. The year 2021 was the year with the most SRMA (385/3,004). Out of the 3,004 SRMAs, 36 (0.03%) were highly cited papers, and 22 of the 36 highly cited papers focused on “pain management.” BRITISH JOURNAL OF ANAESTHESIA had the highest 5-year impact factor (9.6) in 2022 Journal Citation Reports, the most significant number of publications (268/3,004), the highest total number of citations (13,173/86,145), and the most significant number of SRMAs cited more than 100 (36/160). ANAESTHESIA achieved the highest impact factor in the 2022 Journal Citation Reports (10.7) and the highest average annual citations (58.82). PAIN had the highest number of highly cited papers (15/36). The United States of America was the most productive country, with 823/3,004 SRMAs. University Toronto had the highest number of publications (245/3,004). The most frequent of keywords was the topic “Pain Management” (1,622/29.1%).ConclusionThis present study would be valuable to practitioners, academics, researchers, and students in understanding the dynamics of progress in anesthesiology.

CrossDI-DatasetCrossDI(Cross-source Disruption Indexes) Dataset1.OverviewPython tools and curated data to compute disruption-style metrics in yearly windows. Only the citing side is time-truncated. Metrics are produced per target paper and per window, with multi-source support and parallel processing.2.DomainsFile names use an ID 1-4:1.Synthetic Biology2.Astronomy & Astrophysics3.Blockchain-based Information System Management4.Socio-Economic Impacts of Biological Invasions3.Data File Layoutdataset├─ doi/│ ├─ dois-1.csv│ ├─ dois-2.csv│ ├─ dois-3.csv│ └─ dois-4.csv│ └─ dois-multi-1.csv│ └─ dois-multi-2.csv│ └─ dois-multi-3.csv│ └─ dois-multi-4.csv├─ target/│ ├─ target-1.csv│ ├─ target-2.csv│ ├─ target-3.csv│ └─ target-4.csv├─ citations/│ ├─ citations-1-DIMENSIONS.csv│ ├─ citations-1-OPEN_CITATIONS.csv│ ├─ citations-1-WEB_OF_SCIENCE.csv│ ├─ citations-2-DIMENSIONS.csv│ ├─ citations-2-OPEN_CITATIONS.csv│ ├─ citations-2-WEB_OF_SCIENCE.csv│ ├─ citations-3-DIMENSIONS.csv│ ├─ citations-3-OPEN_CITATIONS.csv│ ├─ citations-3-WEB_OF_SCIENCE.csv│ ├─ citations-4-DIMENSIONS.csv│ ├─ citations-4-OPEN_CITATIONS.csv│ └─ citations-4-WEB_OF_SCIENCE.csv└─ result/ ├─ results-1-DIMENSIONS.xlsx ├─ results-1-OPEN_CITATIONS.xlsx ├─ results-1-WEB_OF_SCIENCE.xlsx └─ same pattern for domains 2–44.File DefinitionsArticle list: doi/dois-{ID}.csv (TSV: doi, year). Only citing articles must have a valid year; cited references may have blank year.Citation edges: citations/citations-{ID}-{SOURCE}.csv (TSV: cited_doi, citing_doi). Direction is cited → citing.Target articles: target/target-{ID}.csv (TSV: doi). Focal papers to be evaluated.Results: result/results-{ID}-{SOURCE}.xlsxMulti-DOI consolidation (doi/dois-multi-{ID}.csv): each line lists a group of normalized DOIs determined to refer to the same work; the first DOI is taken as the canonical identifier (subsequent DOIs are aliases).5.WindowingFor a target published in year y, window Y includes citing papers with year ≤ y + Y.6.DI MetricsFor each (Source, Target, Y) the script reports: DI, mDI, DI5, DInoR, DI3%, DEP, invDEP, Origbase, Destabilization (D), Consolidation (C).7.Output columnsN_F, N_B, N_R, DI, mDI, N_B^5, DI_5, DI^noR, N_F_new, N_B_new, DI_3%, DEP, Orig_base, Destabilization(D), Consolidation(C), DOI, Publication year, Y, Source, invDEP8.References[1] Shuo Xu, Congcong Wang, Xin An, and Jianhua Liu, 2025. CrossDI: A Comprehensive Dataset Crossing Three Databases for Calculating Disruption Indexes. Scientific Data. (Under review)[2] Shuo Xu, Congcong Wang, Xin An, Yunkang Deng, and Jianhua Liu, 2025. Do OpenCitations and Dimensions Serve as an Alternative to Web of Science for Calculating Disruption Indexes? Journal of Informetrics, Vol. 19, No. 3, pp. 101685.[3] Shuo Xu, Liyuan Hao, Xin An, Dongsheng Zhai, and Hongshen Pang, 2019. Types of DOI Errors of Cited References in Web of Science with a Cleaning Method. Scientometrics, Vol. 120, No. 3, pp. 1427-1437.