Abstract:

In the last decade, in scientific communities a requirement was established, namely the requirement towards the scientific researchers, lecturers of the academic society to publish their works in books etc., refer to the literature they have used in their works, as well as their publications to be cited by other authors.

The objective of the present work is to create hypotheses to be researched and proven with the assistance of the Data Science and on this basis to establish the science-metric indicators (reference level and publications) and their impact onto universities globally, as well as the universities at the Balkan Peninsula. To this end, the author would be processing data taken from the website https://www.kaggle.com, in which you could find public data sets necessary to the scientists occupied with the data science.

The methods to be used by the author in the report on achieving the main goal is via creating hypotheses to elaborate code in Python via testing it in the open-source platform Anaconda. Thus we outline numerous analyses on evaluating the science-metric indicators in the universities worldwide.

The intended analysis would take part on the grounds of science-metric data taken from the Global Data Bank, and they include information from the UNESCO Statistical Institute.

The results would be prerequisite to evaluate the scientific-metric data in the universities globally and at the Balkan Peninsula. Thus to arrange them, and in particular the ones of the Balkan Peninsula with the highest reference value and publication activity, and the ones of the lowest rate thus to establish the science level of the researched organizations.

Keywords:

Data science, Python, data sets, citation, publishing, monitoring