The primary article search was carried out by using selected keywords. These keywords were jointly selected by the authors, with criteria that were based on the frequently used authors' keywords found in most of the related articles. For example, the list of keywords such as “blockchain” combined with “education”, or “lifelong learning” or “life-long learning” or “digital certificate” or “academic record” or “e-learning” was used to conduct the search. 

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A collection of about 30K images that represents figures and tables from each track of the IEEE Visualization conference series (Vis, SciVis, InfoVis, VAST).

Instructions: 

These files are in PNG format. Due to upload size limit, these files are divided into five zip files organized by year. 

The full collection in one-file is about 21.2G and can also be found online at http://www.cse.osu.edu/~chen.8028/VIS30K/VIS30K.tar.gz. 

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File contains "r bibliometrix" library documentation code for R software (source: Aria, M. & Cuccurullo, C. (2017) bibliometrix: An R-tool for comprehensive science mapping analysis, Journal of Informetrics, 11(4), pp 959-975, Elsevier/ https://github.com/massimoaria/bibliometrix) for bibligraphy analysis of Urban carrying capacity related researches and Web of Science data records. In total 307 data record of Web of Science database was extracted and cleaned (n=307).

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Machine learning is becoming increasingly important for companies and the scientific community. It allows us to generate solutions for several problems faced by society. In this study, we perform a science mapping analysis on the machine learning research, in order to provide an overview of the scientific work during the last decade in this area and to show trends that could be the basis for future developments in the field of computer science. This study was carried out using the CiteSpace and SciMAT tools based on results from Scopus and Clarivate Web of Science.

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