COVID-19: A scholarly production dataset report for research analysis.
Ontology highlight
ABSTRACT:
SUBMITTER: Santos BS
PROVIDER: S-EPMC7434621 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Scientometrics enables scholars to assess and visualize emerging research trends and hot-spots in the scientific literature from a quantitative standpoint. In the last decades, Africa has nearly doubled its absolute count of scholarly output, even though its share in global knowledge production has dramatically decreased. The still-ongoing COVID-19 pandemic has profoundly impacted the way scholarly research is conducted, published, and disseminated. However, the COVID-19-related research focus, the scientific productivity, and the research collaborative network of African researchers during the ongoing COVID-19 pandemic remain to be elucidated. This study aimed to clarify the COVID-19 research patterns among African researchers and estimate the strength of collaborations and partnerships between African researchers and scholars from the rest of the world during the COVID-19 pandemic, collecting data from electronic scholarly databases such as Web of Science (WoS), PubMed/MEDLINE and African Journals OnLine (AJOL), the largest and prominent platform of African-published scholarly journals. We found that COVID-19-related collaboration patterns varied among African regions. For instance, most of the scholarly partnerships occurred with formerly colonial countries (such as European or North-American countries). In other cases, scholarly ties of North African countries were above all with the Kingdom of Saudi Arabia. In terms of number of publications, South Africa and Egypt were among the most productive countries. Bibliometrics and, in particular, scientometrics can help scholars identify research areas of particular interest, as well as emerging topics, such as the COVID-19 pandemic. With a specific focus on the still-ongoing viral outbreak, they can assist decision- and policy-makers in allocating funding and economic-financial, logistic, organizational, and human resources, based on the specific gaps and needs of a given country or research area.
| S-EPMC8308093 | biostudies-literature
Project description:IntroductionScientometrics is a discipline that allows the analysis of the characteristics of publications in each field of knowledge using different indicators. The aim of this research was to analyse world scientific publication as to COVID-19 related to dentistry.MethodsA specialised search strategy was used to obtain all the documents published in journals indexed in the Scopus database between December 2019 and February 2022. The study variables were exported and analysed in SciVal (Elsevier).ResultsIn all, 2071 documents were retrieved; of those, Oral Diseases has the highest impact with an average of 12.3 citations per publication, and the British Medical Journal was identified as the journal with the highest scientific output (107). India (292) and the UK (287) were the countries with the most published papers. The Universidade de São Paulo in Brazil was the institution with the highest number of published papers (61) and with the highest impact.ConclusionsDuring the pandemic, scientific publications on dentistry and COVID-19 have been increasing considerably. International collaboration has the highest percentage of publications whilst India and the UK are the countries with the highest scientific production.
| S-EPMC9113780 | biostudies-literature
Project description:In many countries, COVID-19 has made it harder for women to study because they are expected to do more housework and care for children. This article encompasses different data sources that can be used to figure out how the early pandemic of COVID-19 affected the number of studies done by females, in comparison with males. This data is add-on metadata that can be used with raw Microsoft Academic Graph (MAG) from 2016 to 2020 of the Feb 6, 2021 dump. We retrieved open-source metadata from various sources, including LinkedIn, the Johns Hopkins Coronavirus Resource Center, and Google's COVID-19 Community Mobility Reports, and linked bibliographic information to characteristics of the author's environments. It consists of published journals and online preprints, including each author's gender and involvement in the publication, their position through time, the h-index of their institutes, and gender equality in the professional labor market at the country level. For each record of papers, the data also includes the information of the papers, e.g., title and field of study. By gathering this evidence, our data can support the fact diversity in science is more than just the number of active members of different groups. It should also examine minority participation in science. Our data may help scholars understand diversity in science and advance it. The article ``The effect of the COVID-19 pandemic on gendered research productivity and its correlates'' uses this data as the principal source (Kwon, Yun & Kang, 2021).
| S-EPMC10156633 | biostudies-literature
Project description:The increasing amount of publicly available research data provides the opportunity to link and integrate data in order to create and prove novel hypotheses, to repeat experiments or to compare recent data to data collected at a different time or place. However, recent studies have shown that retrieving relevant data for data reuse is a time-consuming task in daily research practice. In this study, we explore what hampers dataset retrieval in biodiversity research, a field that produces a large amount of heterogeneous data. In particular, we focus on scholarly search interests and metadata, the primary source of data in a dataset retrieval system. We show that existing metadata currently poorly reflect information needs and therefore are the biggest obstacle in retrieving relevant data. Our findings indicate that for data seekers in the biodiversity domain environments, materials and chemicals, species, biological and chemical processes, locations, data parameters and data types are important information categories. These interests are well covered in metadata elements of domain-specific standards. However, instead of utilizing these standards, large data repositories tend to use metadata standards with domain-independent metadata fields that cover search interests only to some extent. A second problem are arbitrary keywords utilized in descriptive fields such as title, description or subject. Keywords support scholars in a full text search only if the provided terms syntactically match or their semantic relationship to terms used in a user query is known.
| S-EPMC7990268 | biostudies-literature
Project description:Government restrictions to the movement of people due to the COVID-19 pandemic have had a wide range of effects on scientific activity. Here, we show that during the pandemic there has been a reduction in the number of registered non-COVID-19 clinical trials. Furthermore, using the Oxford COVID-19 Government Response Tracker Stringency Index (SI) as an indicator of COVID-19-related workplace adjustment (e.g., restrictions on gatherings, workplace closures, and stay-at-home orders), we demonstrate that this drop in clinical trial registration has been greater in countries with a higher SI. This could have significant consequences for the discovery of treatments that are required to reduce the global burden of disease.
| S-EPMC9115337 | biostudies-literature
Project description:BackgroundThe COVID-19 pandemic has severely affected health systems and medical research worldwide but its impact on the global publication dynamics and non-COVID-19 research has not been measured. We hypothesized that the COVID-19 pandemic may have impacted the scientific production of non-COVID-19 research.MethodsWe conducted a comprehensive meta-research on studies (original articles, research letters and case reports) published between 01/01/2019 and 01/01/2021 in 10 high-impact medical and infectious disease journals (New England Journal of Medicine, Lancet, Journal of the American Medical Association, Nature Medicine, British Medical Journal, Annals of Internal Medicine, Lancet Global Health, Lancet Public Health, Lancet Infectious Disease and Clinical Infectious Disease). For each publication, we recorded publication date, publication type, number of authors, whether the publication was related to COVID-19, whether the publication was based on a case series, and the number of patients included in the study if the publication was based on a case report or a case series. We estimated the publication dynamics with a locally estimated scatterplot smoothing method. A Natural Language Processing algorithm was designed to calculate the number of authors for each publication. We simulated the number of non-COVID-19 studies that could have been published during the pandemic by extrapolating the publication dynamics of 2019 to 2020, and comparing the expected number to the observed number of studies.ResultsAmong the 22,525 studies assessed, 6319 met the inclusion criteria, of which 1022 (16.2%) were related to COVID-19 research. A dramatic increase in the number of publications in general journals was observed from February to April 2020 from a weekly median number of publications of 4.0 (IQR: 2.8-5.5) to 19.5 (IQR: 15.8-24.8) (p < 0.001), followed afterwards by a pattern of stability with a weekly median number of publications of 10.0 (IQR: 6.0-14.0) until December 2020 (p = 0.045 in comparison with April). Two prototypical editorial strategies were found: 1) journals that maintained the volume of non-COVID-19 publications while integrating COVID-19 research and thus increased their overall scientific production, and 2) journals that decreased the volume of non-COVID-19 publications while integrating COVID-19 publications. We estimated using simulation models that the COVID pandemic was associated with a 18% decrease in the production of non-COVID-19 research. We also found a significant change of the publication type in COVID-19 research as compared with non-COVID-19 research illustrated by a decrease in the number of original articles, (47.9% in COVID-19 publications vs 71.3% in non-COVID-19 publications, p < 0.001). Last, COVID-19 publications showed a higher number of authors, especially for case reports with a median of 9.0 authors (IQR: 6.0-13.0) in COVID-19 publications, compared to a median of 4.0 authors (IQR: 3.0-6.0) in non-COVID-19 publications (p < 0.001).ConclusionIn this meta-research gathering publications from high-impact medical journals, we have shown that the dramatic rise in COVID-19 publications was accompanied by a substantial decrease of non-COVID-19 research. META-RESEARCH REGISTRATION: https://osf.io/9vtzp/ .
| S-EPMC8607966 | biostudies-literature
Project description:BackgroundDue to the growing amount of COVID-19 research literature, medical experts, clinical scientists, and researchers frequently struggle to stay up to date on the most recent findings. There is a pressing need to assist researchers and practitioners in mining and responding to COVID-19-related questions on time.MethodsThis paper introduces CoQUAD, a question-answering system that can extract answers related to COVID-19 questions in an efficient manner. There are two datasets provided in this work: a reference-standard dataset built using the CORD-19 and LitCOVID initiatives, and a gold-standard dataset prepared by the experts from a public health domain. The CoQUAD has a Retriever component trained on the BM25 algorithm that searches the reference-standard dataset for relevant documents based on a question related to COVID-19. CoQUAD also has a Reader component that consists of a Transformer-based model, namely MPNet, which is used to read the paragraphs and find the answers related to a question from the retrieved documents. In comparison to previous works, the proposed CoQUAD system can answer questions related to early, mid, and post-COVID-19 topics.ResultsExtensive experiments on CoQUAD Retriever and Reader modules show that CoQUAD can provide effective and relevant answers to any COVID-19-related questions posed in natural language, with a higher level of accuracy. When compared to state-of-the-art baselines, CoQUAD outperforms the previous models, achieving an exact match ratio score of 77.50% and an F1 score of 77.10%.ConclusionCoQUAD is a question-answering system that mines COVID-19 literature using natural language processing techniques to help the research community find the most recent findings and answer any related questions.
| S-EPMC9160513 | biostudies-literature
Project description:In this article, several scholars of nationalism discuss the potential for the COVID-19 pandemic to impact the development of nationalism and world politics. To structure the discussion, the contributors respond to three questions: (1) how should we understand the relationship between nationalism and COVID-19; (2) will COVID-19 fuel ethnic and nationalist conflict; and (3) will COVID-19 reinforce or erode the nation-state in the long run? The contributors formulated their responses to these questions near to the outset of the pandemic, amid intense uncertainty. This made it acutely difficult, if not impossible, to make predictions. Nevertheless, it was felt that a historically and theoretically informed discussion would shed light on the types of political processes that could be triggered by the COVID-19 pandemic. In doing so, the aim is to help orient researchers and policy-makers as they grapple with what has rapidly become the most urgent issue of our times.
| S-EPMC7404753 | biostudies-literature
Project description:ObjectiveSurvey vice chairs of research from academic radiology departments on the impact of COVID-19 on research activities.MethodsThe survey asked respondents to quantify changes in research performed during the shutdown and ramp-up, relative to pre-COVID-19 levels. Respondents estimated research activity changes by overall research type (wet, instrumentation, or core facilities; prospective non-COVID-19 clinical research and computational laboratories) and then by the research activity type (data analysis, grant or manuscript writing, clinician involvement, summer student participation, and international research fellow appointments).The χ2 test was used for comparison between shutdown and ramp-up, with Yates correction when necessary.ResultsOf 105 vice chairs contacted, 46 (43.8%) responded. For 95.5%, wet, instrumentation, or core facilities research decreased to ≤50% during shutdown and for 83.3% during ramp-up (P < .0001). In addition, 89.2% and 46.5% indicated reduction to ≤25% of non-COVID-19 clinical research during shutdown and ramp-up, respectively (P < .0001). Only computational research increased to 120% during shutdown (39.5%) or ramp-up (50%) (P = .8984). For data analysis from closed laboratories, 75% and 86% showed decreased activity during shutdown and ramp-up, respectively (P = .28). Increased grant writing during shutdown and ramp-up was reported by 45.5% and 23.3% (P = .093). For 52.3% and 23.3%, manuscript writing and submission increased during shutdown and ramp-up, respectively (P < .02). Clinician research involvement trended toward relative decreases during shutdown (84.1% versus 60.5%, P = .05). There was similar drop in summer student participation (shutdown: 86.4%, ramp-up: 83.7%, P = .95) and international researcher appointment (shutdown: 85.7%, ramp-up: 86.1%; P = .96).ConclusionMany radiology research activities diminished during the COVID-19 shutdown and to a lesser extent during the ramp-up. Activities that could be done remotely, such as computational analysis and grant and manuscript writing and submission, increased.
| S-EPMC8639392 | biostudies-literature
Project description:This work shows a patent database for Coronaviruses that provides an overview of the patenting activity and trends in focused antiviral therapy with the use of triazole based compounds, glycoprotein, and protease inhibitors as possible treatment. The patent data was obtained from Orbit Intelligence Software using a patent family structure to get a big database that could be used for built patent landscape report (PLR), market analysis, technical and competitive intelligence, and monitoring and survey of a new ideas for the treatment of coronavirus diseases. The raw data is reported in four databases, which were classified according to different items: legal status (alive, dead), 1st application year (after 2015, 2011-2015, 2006-2010, 2001-2005), and Top 5 International Patents Classifications (IPC). The main players, the investment trend, markets, geographical distribution, technology overview, technologies distribution, and patent citation are showed by this analysed data report.
| S-EPMC7176944 | biostudies-literature