Mapping of Dyslexia Research Output: The Global Perspective

The aim of this article is to examine the bibliometric analysis of global publication output on coronavirus, as covered in Web of Science during the period from 2000 to 2019. A total of 10,861 documents were found during a 20-year period spanning from 2000 to 2019 published in the ISI Web of Science. The study analyses annual productivity, most productive source titles, prolific countries, eminent institutions, linguistic analysis and productivity of authors and their contribution in the subject area. The findings reveal that the most productive year of publication was 2004 that included 782 publications with the majority published in the Journal of Virology. The result further indicates that the USA, China and Germany are the most productive countries in the field of Coronavirus research output. In terms of institutional output, University of Hong Kong emerged as the most productive institution; Yuen KY from Hong Kong is the most prolific author. In the subject category type, the most prominent subject field is Virology, Infectious Disease and Veterinary Science. The findings of the study are limited to the data harvested from ‘Web of Science’. This study is of immense relevance to researchers and academicians who are searching for answers to this pandemic. This will provide insights to academicians to collaborate with other researchers based on the quality of the research produced by other countries and institutes. The study is useful for researchers, immunologists and epidemiologists who are interested in the field of Coronavirus and serves as a base for future research.

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Global Research Output in Occupational Health From 1998–2018

Advances in Library and Information Science - Handbook of Research on Information and Records Management in the Fourth Industrial Revolution ◽

10.4018/978-1-7998-7740-0.ch009 ◽

2021 ◽

pp. 121-140

Author(s):

Senthamilselvi A.

Keyword(s):

Occupational Health ◽

Research Productivity ◽

Web Of Science ◽

Research Output ◽

Publication Output ◽

Global Level ◽

Online Database ◽

Global Research

An analysis of 12,317 publications published by Research Productivity on Occupational Health during 1998-2018 and indexed by Web of Science online database indicates the publication output in the global level research productivity of the publication. The highest numbers of papers were published during the year 2018 with 1,237 records followed by the year 2016 with 1,189 records. Overall, 31,498 authors contributed 2,866 publications in the journal and global cited scores with 149,345 records of the articles. A total of 138 countries have contributed in publications of the output of total research productivity. In this research, it is found that articles have been written using 25 languages.

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Open access levels: a quantitative exploration using Web of Science and oaDOI data

10.7287/peerj.preprints.3520v1 ◽

2018 ◽

Cited By ~ 16

Author(s):

Jeroen Bosman ◽

Bianca Kramer

Keyword(s):

Open Access ◽

Policy Development ◽

Web Of Science ◽

Research Output ◽

Research Field ◽

Open Access Publishing ◽

Pure Gold ◽

Research Fields ◽

Institutional Contexts ◽

Status Data

Across the world there is growing interest in open access publishing among researchers, institutions, funders and publishers alike. It is assumed that open access levels are growing, but hitherto the exact levels and patterns of open access have been hard to determine and detailed quantitative studies are scarce. Using newly available open access status data from oaDOI in Web of Science we are now able to explore year-on-year open access levels across research fields, languages, countries, institutions, funders and topics, and try to relate the resulting patterns to disciplinary, national and institutional contexts. With data from the oaDOI API we also look at the detailed breakdown of open access by types of gold open access (pure gold, hybrid and bronze), using universities in the Netherlands as an example. There is huge diversity in open access levels on all dimensions, with unexpected levels for e.g. Portuguese as language, Astronomy & Astrophysics as research field, countries like Tanzania, Peru and Latvia, and Zika as topic. We explore methodological issues and offer suggestions to improve conditions for tracking open access status of research output. Finally, we suggest potential future applications for research and policy development. We have shared all data and code openly.

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Open access levels: a quantitative exploration using Web of Science and oaDOI data

10.7287/peerj.preprints.3520 ◽

2018 ◽

Author(s):

Jeroen Bosman ◽

Bianca Kramer

Keyword(s):

Open Access ◽

Policy Development ◽

Web Of Science ◽

Research Output ◽

Research Field ◽

Open Access Publishing ◽

Pure Gold ◽

Research Fields ◽

Institutional Contexts ◽

Status Data

Across the world there is growing interest in open access publishing among researchers, institutions, funders and publishers alike. It is assumed that open access levels are growing, but hitherto the exact levels and patterns of open access have been hard to determine and detailed quantitative studies are scarce. Using newly available open access status data from oaDOI in Web of Science we are now able to explore year-on-year open access levels across research fields, languages, countries, institutions, funders and topics, and try to relate the resulting patterns to disciplinary, national and institutional contexts. With data from the oaDOI API we also look at the detailed breakdown of open access by types of gold open access (pure gold, hybrid and bronze), using universities in the Netherlands as an example. There is huge diversity in open access levels on all dimensions, with unexpected levels for e.g. Portuguese as language, Astronomy & Astrophysics as research field, countries like Tanzania, Peru and Latvia, and Zika as topic. We explore methodological issues and offer suggestions to improve conditions for tracking open access status of research output. Finally, we suggest potential future applications for research and policy development. We have shared all data and code openly.

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A Scientometric Study on Yoga Research during 1989-2018

Asian Journal of Information Science and Technology ◽

10.51983/ajist-2019.9.2.284 ◽

2019 ◽

Vol 9 (2) ◽

pp. 17-22

Author(s):

A. Poornima ◽

M. Surulinathi

Keyword(s):

Web Of Science ◽

Research Output ◽

Publication Output ◽

Present Moment ◽

Online Database ◽

Yogic Breathing ◽

Unique Method ◽

Prolific Authors ◽

The Mind ◽

Scientometric Study

Yoga is a mind-body exercise. Yogic breathing is a unique method for balancing the autonomic nervous system and influencing psychological and stress-related disorders. Yoga breathing (pranayama) can rapidly bring the mind to the present moment and reduce stress. This article presents the highly cited papers from yoga research output using different scientometric approach both quantitative and qualitative methods. Scientometric data for the study has been collected from Web of Science online database. A search was conducted with the phrase ‘yoga’ in the address field. An analysis of 4090 publications published by scientists during 1989 to 2018 and indexed by Web of Science online Database indicates that the publication output. Most of the prolific authors are from the highly productive institutions. This work is to provide a profile of Research Publication at global level. This includes tracking the number of papers, scatter of papers over journals, and its effect on publication output, authors’ institutional affiliations and authorship patterns.

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Mapping the Research Output of University of Kashmir

International Journal of Knowledge Management and Practices ◽

10.21863/ijkmp/2015.3.2.009 ◽

2015 ◽

Vol 3 (2) ◽

Author(s):

Asifa Jan ◽

Suhail Ahmed ◽

Nahida Tun Nisa ◽

Asiya Ahmed

Keyword(s):

Biological Sciences ◽

Research Output ◽

Publication Output ◽

Regional Research Laboratory ◽

Medical Sciences ◽

Joint Research ◽

Document Type ◽

H Index ◽

Search Feature ◽

Sciverse Scopus

The study maps the research output from University of Kashmir, one of the premier higher education institutes of Jammu&Kashmir state, India. Elseviers SciVerse Scopus one of the leading indexing abstracting services was queried for a period of 1963- February 2015 using the affiliation search feature for University of Kashmir. The works of the authors affiliated with University of Kashmir have been analyzed. Statistical analysis of the retrieved data was performed. The publication output from University of Kashmir has shown a promising growth expect for some years in 1990s which can be attributed to the political instability in the state. The highest contributing authors are from Science disciplines with authors from Chemistry, Botany, Electronics, Biochemistry, and Centre of Research for Development departments having a higher rate of h-Index. Majority of papers are published in Indian sources followed by the sources from US, Germany and China. Majority of the authors are affiliated with University of Kashmir followed by Indian Institute of Integrative Medicine (Earlier Regional Research Laboratory, Sanat Nagar), Sher-i-Kashmir Institute of Medical Sciences (SKIMS) and Aligarh Muslim University. Articles have remained a prime document type for publishing by the authors from University of Kashmir followed by conference proceedings and review articles. Agricultural and Biological Sciences outscore other disciplines followed by Biochemistry, Genetics & Molecular Biology and Medicine. Future emphasis on joint research, international collaboration, and publishing in indexed journals is needed.

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Questions to the Article of research output and international cooperation among countries during the COVID-19 pandemic (Preprint)

10.2196/preprints.26576 ◽

2020 ◽

Author(s):

Shu-Chun Kuo ◽

Tsair-Wei Chien ◽

Willy Chou

Keyword(s):

Citation Analysis ◽

International Cooperation ◽

Web Of Science ◽

Research Output ◽

Visual Representations ◽

Scientometric Analysis ◽

Medical Subject Headings ◽

Pubmed Central ◽

The Us ◽

Circle Diagram

UNSTRUCTURED We read with great interest the study by Grammes et al. on research output and international cooperation among countries during the COVID-19 pandemic. The paper is a quantitative study using scientometric analysis instead of a qualitative research using citation analysis. A total of 7,185 publications were extracted from Web of Science Core Collection (WoS) with keywords of “covid19 OR covid-19 OR sarscov2 OR sars-cov-2” as of July 4, 2020. We replicated a citation analysis study to extract abstracts from Pubmed Central(PMC) with similar keywords mentioned above and obtained 35,421 articles relevant to COVID-10 matching their corresponding number of citation in PMC. one hundred top-cited atricles were selected and compared on diagrams. Social network analysis combined with citation numbers in articles was performed to analyze international cooperation among countries. The results were shown on a world map instead of the circle diagram in the previous study. A Sankey diagram was applied to highlight entities(e.g., countries, article types, medical subject headings, and journals) with the most citations. Authors from Chian dominated citations in these 100 top-cited articles rather than the US in publications addressed in the previous study. Both visual representations of the world map and Sankey diagram were provided to readers with a better understanding of the research output and international cooperation among countries during the COVID-19 pandemic

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End-To-End Computer Vision Framework: An Open-Source Platform for Research and Education

Sensors ◽

10.3390/s21113691 ◽

2021 ◽

Vol 21 (11) ◽

pp. 3691

Author(s):

Ciprian Orhei ◽

Silviu Vert ◽

Muguras Mocofan ◽

Radu Vasiu

Keyword(s):

Machine Learning ◽

Image Processing ◽

Computer Vision ◽

Open Source ◽

Visual Processing ◽

Research Field ◽

Learning Models ◽

Research Activity ◽

End To End ◽

Machine Learning Models

Computer Vision is a cross-research field with the main purpose of understanding the surrounding environment as closely as possible to human perception. The image processing systems is continuously growing and expanding into more complex systems, usually tailored to the certain needs or applications it may serve. To better serve this purpose, research on the architecture and design of such systems is also important. We present the End-to-End Computer Vision Framework, an open-source solution that aims to support researchers and teachers within the image processing vast field. The framework has incorporated Computer Vision features and Machine Learning models that researchers can use. In the continuous need to add new Computer Vision algorithms for a day-to-day research activity, our proposed framework has an advantage given by the configurable and scalar architecture. Even if the main focus of the framework is on the Computer Vision processing pipeline, the framework offers solutions to incorporate even more complex activities, such as training Machine Learning models. EECVF aims to become a useful tool for learning activities in the Computer Vision field, as it allows the learner and the teacher to handle only the topics at hand, and not the interconnection necessary for visual processing flow.

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