Datasets Comparison

Citation metrics are widely used and misused. We have created a publicly available database of 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-2017 and to end-of-2018 for comparison.

Code explaining the compilation of the elements and data is provided in the downloadable files; detailed code (PySpark) calculating the metrics can be found in the python file.

Elsevier BV, Stanford University

Bibliometrics

Attribution-NonCommercial 3.0 Unported

Citation metrics are widely used and misused. We have created a publicly available database of 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-2019. 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. In addition to the time period and datacut update, it provides a longer list of authors: it also includes the top 2% for every subfield.

Code is provided with the dataset and runs on the ICSR Lab data sharing platform (https://www.elsevier.com/icsr/icsrlab) using Scopus data. It is written in python (pyspark) and can be used with other datasets on any pyspark platform.

Elsevier BV, Stanford University

Bibliometrics

Attribution-NonCommercial 3.0 Unported