scholarly journals La cobertura de los índices de citas abiertos se acerca a la de Web of Science y Scopus

2021 ◽  
Author(s):  
Alberto Martín-Martín
Keyword(s):  
Information Sources ◽  
Web Of Science ◽  
Open Data ◽  
Digital Transformation ◽  
Data Sources ◽  
Google Scholar ◽  
Easy Access ◽  
Citation Data ◽  
Microsoft Academic ◽  
New Infrastructure

The information sources that are often used to monitor and to obtain a better understanding of the system of scholarly communication (such as Web of Science, Scopus, and Google Scholar) have historically been distributed under restrictive use licenses. However, in a scenario where science and scientific communication are undergoing a process of digital transformation, these models do not facilitate the development of new infrastructure that is better adapted to current and future needs. At the same time, these models hamper reproducibility. In recent years, a variety of open data sources, such as Microsoft Academic, Crossref, and others, have become available, providing easy access to large collections of metadata that were previously only available from closed sources. Citation data are one type of metadata provided by these open data sources. This study documents the significant growth in coverage of open citation data that has taken place between 2019 and 2021, and the events that have led to this point. These collections of open scholarly metadata have kick-started the development of a new ecosystem of scholarly information services. However, their fragility still poses a risk for downstream applications. Academic libraries could become important allies of open scholarly metadata initiatives. Resumen Históricamente, las fuentes de información utilizadas para observar y comprender el funcionamiento del sistema de comunicación científica han sido distribuidas bajo licencias de uso restrictivas (Web of Science, Scopus, Google Scholar). En el contexto actual, caracterizado por un proceso de transformación digital de la ciencia y de la comunicación científica, estos modelos no facilitan el desarrollo de infraestructuras y herramientas de información científica adaptadas a nuevas necesidades, e impiden la realización de análisis reproducibles. Afortunadamente, en los últimos años han aparecido diversas colecciones de metadatos de investigación distribuidas bajo licencias abiertas, como las ofrecidas por Microsoft Academic, Crossref y otros. Un tipo de metadato ofrecido por estas fuentes abiertas que anteriormente solo estaba disponible desde fuentes cerradas son las relaciones de citación entre documentos académicos. Este trabajo muestra el significativo crecimiento que se ha producido entre 2019 y 2021 en la cobertura de citas disponible en fuentes abiertas, así como los pasos que han sido necesarios para llegar hasta este punto. Estas colecciones de metadatos abiertas han estimulado el desarrollo de un nuevo ecosistema de herramientas de información científica, pero su fragilidad representa un riesgo de cara al futuro. Las bibliotecas académicas podrían convertirse en importantes aliadas de estas iniciativas.

scholarly journals Ranking by Relevance and Citation Counts, a Comparative Study: Google Scholar, Microsoft Academic, WoS and Scopus

2019 ◽  
Vol 11 (9) ◽  
pp. 202 ◽  
Author(s):  
Rovira ◽  
Codina ◽  
Guerrero-Solé ◽  
Lopezosa
Keyword(s):  
Search Engine ◽  
Search Engines ◽  
Web Of Science ◽  
Growth Potential ◽  
Google Scholar ◽  
Unexpected Finding ◽  
Ranking Algorithms ◽  
Microsoft Academic ◽  
Citation Counts ◽  
The Impact

Search engine optimization (SEO) constitutes the set of methods designed to increase the visibility of, and the number of visits to, a web page by means of its ranking on the search engine results pages. Recently, SEO has also been applied to academic databases and search engines, in a trend that is in constant growth. This new approach, known as academic SEO (ASEO), has generated a field of study with considerable future growth potential due to the impact of open science. The study reported here forms part of this new field of analysis. The ranking of results is a key aspect in any information system since it determines the way in which these results are presented to the user. The aim of this study is to analyze and compare the relevance ranking algorithms employed by various academic platforms to identify the importance of citations received in their algorithms. Specifically, we analyze two search engines and two bibliographic databases: Google Scholar and Microsoft Academic, on the one hand, and Web of Science and Scopus, on the other. A reverse engineering methodology is employed based on the statistical analysis of Spearman’s correlation coefficients. The results indicate that the ranking algorithms used by Google Scholar and Microsoft are the two that are most heavily influenced by citations received. Indeed, citation counts are clearly the main SEO factor in these academic search engines. An unexpected finding is that, at certain points in time, Web of Science (WoS) used citations received as a key ranking factor, despite the fact that WoS support documents claim this factor does not intervene.

scholarly journals DIGITAL TRANSFORMATION IN HIGHER EDUCATION: AN INTEGRATIVE REVIEW APPROACH

2021 ◽  
Vol 226 (09) ◽  
pp. 139-146
Author(s):  
Dương Thị Thái ◽  
Hà Trọng Quỳnh ◽  
Phạm Thị Tuấn Linh
Keyword(s):  
Higher Education ◽  
Web Of Science ◽  
Digital Transformation ◽  
Integrative Review ◽  
Google Scholar ◽  
Doi Moi

Chuyển đổi số giúp các trường đại học thay đổi các hoạt động dạy – học, nghiên cứu và vận hành truyền thống với các cách thức đổi mới, sáng tạo và tiết kiệm chi phí hơn. Trên thế giới, các trường đại học đều cố gắng xây dựng và phát triển chiến lược và các hoạt động chuyển đổi số để tìm ra một mô hình phù hợp nhất với từng đơn vị. Nghiên cứu này hệ thống tổng quan tài liệu để cung cấp những thông tin tổng hợp về hoạt động chuyển đổi số trong giáo dục đại học. Nghiên cứu sử dụng các cơ sở dữ liệu như Web of Science (WoS), Google Scholar, Research Gate, ScienceDirect để tiếp cận các bài báo về chuyển đổi số trong giáo dục đại học. Các bài báo được lựa chọn để nghiên cứu tổng quan phải đáp ứng các tiêu chí: có nội dung về chuyển đổi số trong giáo dục đại học, viết bằng tiếng Anh và có thể tiếp cận toàn văn. Tổng cộng có 24 bài báo được sử dụng để nghiên cứu tổng quan. Dựa vào các kết quả của nghiên cứu tổng quan này, nghiên cứu thực nghiệm trong tương lai có thể xác định và đánh giá các yếu tố ảnh hưởng đến công tác triển khai hoạt động chuyển đổi số trong giáo dục đại học.

scholarly journals The prevalence and impact of university affiliation discrepancies between four bibliographic databases – Scopus, Web of Science, Dimensions, and Microsoft Academic

2022 ◽  
pp. 1-47
Author(s):  
Philip J. Purnell
Keyword(s):  
Peer Review ◽  
Web Of Science ◽  
The Other ◽  
Data Sources ◽  
Bibliographic Databases ◽  
Bibliometric Data ◽  
Digital Object ◽  
Manual Examination ◽  
Microsoft Academic ◽  
University Affiliation

Abstract Research managers benchmarking universities against international peers face the problem of affiliation disambiguation. Different databases have taken separate approaches to this problem and discrepancies exist between them. Bibliometric data sources typically conduct a disambiguation process that unifies variant institutional names and those of its sub-units so that researchers can then search all records from that institution using a single unified name. This study examined affiliation discrepancies between Scopus, Web of Science, Dimensions, and Microsoft Academic for 18 Arab universities over a five-year period. We confirmed that digital object identifiers (DOIs) are suitable for extracting comparable scholarly material across databases and quantified the affiliation discrepancies between them. A substantial share of records assigned to the selected universities in any one database were not assigned to the same university in another. The share of discrepancy was higher in the larger databases, Dimensions and Microsoft Academic. The smaller, more selective databases, Scopus and especially Web of Science tended to agree to a greater degree with affiliations in the other databases. Manual examination of affiliation discrepancies showed they were caused by a mixture of missing affiliations, unification differences, and assignation of records to the wrong institution. Peer Review https://publons.com/publon/10.1162/qss_a_00175

scholarly journals Applying Crossref and Unpaywall information to identify gold, hidden gold, hybrid and delayed Open Access publications in the KB publication corpus

2019 ◽  
Author(s):  
Aliakbar Akbaritabar ◽  
Stephan Stahlschmidt
Keyword(s):  
Open Access ◽  
Information Sources ◽  
Web Of Science ◽  
Open Data ◽  
Meta Information

Identifying Open Access (OA) publications might seem a trivial task while practical efforts prove otherwise. In this project, we wanted to assign OA tags to publications in KB database. We queried KB in-house database up to 2017 (including Web of Science (WOS) and Scopus) for all articles and reviews. We then matched the corresponding DOIs to three sources of OA information: Unpaywall, Crossref and Bielefeld list of gold OA journals. This allowed us to define the OA status for publications. We found close to 14 million publications (articles and reviews between 2000 and 2016) from WOS (69.75% of all) and close to 18 million from Scopus (68.67% of all) with an equivalent DOI in Unpaywall. We matched KB publications database with Crossref data (from April 2018) and found 53 distinct licence URLs, which define in many cases the legally binding access status of publications. We found that more than half a million publications have more than one licence record in Crossref (in contrast to near 8 million with only one record and more than 6 million without a licence URL). We evaluated if these licences were open or closed access. We also matched respective journal ISSNs with DOAJ and ROAD databases and presented a categorization of publications to Gold, Hidden Gold, Hybrid and Delayed OA accounting for uncertainty due to missing licence information via a new sub-category Probable Hybrid OA. We validate our findings via manual checks and a crosscheck of OA information from the aforementioned varying sources. While the manual check on a sample of publications revealed a small but noticeable degree of apparently incorrect meta-information on publication’s OA status, the contrast of OA information from the diverse OA information sources highlights the partially unsteady base for an OA monitoring based on open data.

scholarly journals The meaningfulness of open data in Public Health and Healthcare

2019 ◽  
Vol 29 (Supplement_4) ◽  
Author(s):  
J Pita Costa ◽  
F Fuart ◽  
B Cleland ◽  
J Wallace ◽  
A Staines ◽  
...  
Keyword(s):  
Public Health ◽  
Decision Making ◽  
Open Data ◽  
Knowledge Bases ◽  
Data Sources ◽  
Local Context ◽  
Easy Access ◽  
New Information ◽  
Challenges And Opportunities ◽  
Complex Ecosystem

Abstract Background The growing challenges and opportunities of Big Data for Public Health have revealed the potential to improve the efficiency and cost-effectiveness of public policy, for example through better targeting of resources with regard to General Practice (GP) prescribing. Open data has an important role due to its easy access and potential to complement proprietary data sources from, e.g., regional hospitals, and also itself be complemented with social data acquired by specialized approaches. Methods MIDAS pipeline of open source tools aiming integrating, analysing and visualising Open Data enabling health professionals and decision-makers to: (i) improve the usability of open data in combination with proprietary data through combining multiple visualisation tools in an integrated dashboard (ii) to explore the meaning of data in a global/local context based on new information using tone analysis and natural language techniques; and (iii) to have better informed decision-making based on evidence from trusted knowledge-bases. Specific data sources used have included information extracted from the biomedical database MEDLINE, worldwide news and government open data. Social media sources have also been used to gather information from the general public. Results Results include a strong correlation between antidepressant prescribing and economic deprivation, and a wide variation in how individual GP practices respond to demographic conditions. Automated anomaly detection based on the Local Outlier Probability has also been shown to be an easily understood and controllable approach to identifying prescribing outliers. Conclusions MIDAS demonstrates the significant value of open data from heterogeneous sources as basis decision-making in public health and healthcare, particularly when it is combined with proprietary or closed datasets. A key challenge in this regard is the ability to integrate and utilize data from diverse sources in a variety of formats and standards. Key messages MIDAS is exemplar on tackling the need for improved standards of open data, and new software architectures, tools and platforms addressing a complex ecosystem of heterogenous data sources and formats. MIDAS demonstrates the significant value of open data from heterogeneous sources as basis decision-making in public health and healthcare, particularly when combined with proprietary datasets.

scholarly journals The rivalry between Bernini and Borromini from a scientometric perspective

2020 ◽  
Vol 125 (2) ◽  
pp. 1643-1663
Author(s):  
Martin Wieland ◽  
Juan Gorraiz
Keyword(s):  
Impact Assessment ◽  
Core Collection ◽  
Web Of Science ◽  
Point Of View ◽  
Data Sources ◽  
Google Scholar ◽  
Twitter Data ◽  
Baroque Art ◽  
Minimum Number ◽  
The University

AbstractFrom a historical point of view, Rome and especially the University of La Sapienza, are closely linked to two geniuses of Baroque art: Bernini and Borromini. In this study, we analyze the rivalry between them from a scientometric perspective. This study also serves as a basis for exploring which data sources may be appropriate for broad impact assessment of individuals and/or celebrities. We pay special attention to encyclopaedias, library catalogues and other databases or types of publications that are not normally used for this purpose. The results show that some sources such as Wikipedia are not exploited according to the possibilities they offer, especially those related to different languages and cultures. Moreover, analyses are often reduced to a minimum number of data sources, which can distort the relevance of the outcome. Our results show that other sources normally not considered for this purpose, like JSTOR, PQDT, Google Scholar, Catalogue Holdings, etc. can provide more relevant or abundant information than the typically used Web of Science Core Collection and Scopus. Finally, we also contrast opportunities and limitation of old and new (YouTube, Twitter) data sources (particularly the aspects quality and accuracy of the search methods). Much room for improvement has been identified in order to use data sources more efficiently and with higher accuracy.

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