Citation metrics are widely used and misused. We have created a publicly available database of over 100,000 top-scientists that provides standardized information on citations, h-index, co-authorship adjusted hm-index, citations to papers in different authorship positions and a composite indicator. Separate data are shown for career-long and single year impact. Metrics with and without self-citations and ratio of citations to citing papers are given. Scientists are classified into 22 scientific fields and 176 sub-fields. Field- and subfield-specific percentiles are also provided for all scientists who have published at least 5 papers. Career-long data are updated to end-of-2020. The selection is based on the top 100,000 by c-score (with and without self-citations) or a percentile rank of 2% or above. The dataset and code provides an update to previously released version 1 data under https://doi.org/10.17632/btchxktzyw.1; The version 2 dataset is based on the May 06, 2020 snapshot from Scopus and is updated to citation year 2019 available at https://doi.org/10.17632/btchxktzyw.2 This version (3) is based on the Aug 01, 2021 snapshot from Scopus and is updated to citation year 2020.

The project goal is to study the Russian digital economy as a new social field, which is a place of interaction of social forces, carried by individual agents, groups, organizations with their aggregate capitals, habitus, and practices. The author has developed an approach to the definition of habitus, combining the actor's character and capital. To classify habitus, a series of studies was carried out and general characteristics of actions were determined depending on disposition and capitals combination. The research was carried out in 4 Russian regions - Kaliningrad, Yaroslavl, Tambov and Kursk region. 48 groups of common habitus characteristics were identified. Each group was given a name, which is projected in the minds of the Russian population into a certain holistic image. More detailed characteristics have been identified for the digital economy. The following data is presented - Description of the population habitus, Description of the digital habitus, Grouping of the Russian population habitus, Grouping of habitus by research area.

Colleccion de prueba para demostracion en taller

The United Nations Sustainable Development Goals (SDGs) challenge the global community to build a world where no one is left behind. Since 2018, Elsevier have generated SDG search queries to help researchers and institutions track and demonstrate progress towards the targets of the United Nations Sustainable Development Goals (SDGs). At the end of 2018, Elsevier worked on 2 versions of the SDG queries. One version was created by the Elsevier Analytical Services group and another by the Science-Metrix group, who had recently become part of Elsevier. At that time Science-Metrix was creating queries for 5 of the 16 SDGs, as part of pro-bono work for UNESCO. In 2020 inspired by the earlier queries, Elsevier, through its Science-Metrix group, used a new approach to mapping publications to the SDGs. Taking customer feedback into account, they significantly increased the number of search terms used to define each SDG. Those queries were then complemented by a machine learning model, which helped increase the recall by approximately 10%. As a result, this year’s “Elsevier 2021 SDG mapping” captures on average twice as many articles as the 2020 version, while keeping precision above 80%. The mapping also has a better overlap with SDG queries from other independent projects. Times Higher Education (THE) are using the “Elsevier 2021 SDG mapping” as part of their 2021 Impact Rankings. The documentation below describes the methods used and shares the queries. For each SDG, you can download the query as a text file, along with an html file that describes the methodology used to create the search query, plus additional information such as the most influential keyphrases and journals. It also breaks down the query into digestable chunks. A separate folder contains the methodology for the machine learning component, along with a sample of the top 100 keyphrases per SDG and a stratified sample of 8,000 EIDs that the model identified arcoss the SDGs.

Compilation of Raw diffraction datasets for proteases

We selected Public health, and societal and psychological impacts datasets indexed by the Mendeley Data Search engine on the 2019-present COVID-19 / Coronavirus pandemic. The aim was to make it easier to find potentially relevant datasets for this specific topic

Ophthalmology Journal Research Data

Los usuarios normales (investigadores) utilizan las colecciones para organizar su material publicado, o para crear colecciones de conjuntos de datos relevantes o útiles, mientras que los gestores de repositorios y los bibliotecarios de datos utilizan las colecciones para organizar y catalogar los contenidos de todo su repositorio.

Human Disease AuthorAid Collection combines information about rare and common diseases in standardized, easy-to-navigate overview templates and tables. It includes clinical, molecular, and pharmacological data from several Elsevier and public sources. Tables are planned to be updated with the latest citations quarterly. AuthorAid Templates can be a helpful guide for authors, researchers, clinicians, and students, especially those interested in rare diseases, because it highlights updates and findings from several sources on one page.