DSJournalsCS2023
Description
This work is the continuity of the data set called DSrevistasCS2022(Torres Londoño, Carlos Ignacio; Bejarano Segura, Daniel; Caicedo, Rosa Maria; Molina Parra, Maria Clemencia (2023), "DSrevistasCS2022", Mendeley Data, V1, doi: 10.17632/5yv8bdmvjr.1), it was decided to continue with the theme and extend it for the year 2023. The overview of the Scimago Journal & Country Rank results for computer science journals in the years 2018-2023 reveals valuable information about the performance and relevance of scientific journals in this field. To get a more complete picture, we have analyzed the data in two subsets: all journals and open access journals (OAJs). In the full set of journals, which includes both open-access and other journals, we observed descriptive statistics that provide an overall picture of the data set. The number of journals, citations, and impact factors are found to vary significantly over the years analyzed. The mean values, dispersion, and percentiles provide information on the distribution of results and variability among journals. On the other hand, the subset of open-access journals (OAJ) stands out for its focus on the open availability of scientific research. By limiting the analysis to these journals, we can specifically examine how they perform in terms of citations and impact factors compared to the full group. Descriptive statistics allow us to better understand the distribution and distinguishing characteristics of these particular journals. It is important to note that the description of the results is an initial part of the analysis and does not provide a complete picture of each journal individually. For a more comprehensive and meaningful analysis, it is advisable to perform additional analyses and consider other relevant factors, such as research scope, article quality, and trends over time.
Files
Steps to reproduce
In the Scimago Journal & Country Rank page (https://www.scimagojr.com/journalrank.php) in rankings filter by Computer Science and by year, then export the results to different files with all the documents as well as with the open ones. With the files you must make a concatenation by Sourceid, this can be done in google colab with the pandas library.