RATING SYSTEMS FOR SCIENTOMETRIC INDICES OF UNIVERSITIES: KEY ASPECTS, DEVELOPMENT, IMPLEMENTATION

O. Spivakovsky; M. Vinnyk; M. Poltoratskiy; Y. Tarasich; A. Bystriantseva; K. Panova; Y. Spivakovska

doi:10.14308/ite000678

Authors

O. Spivakovsky Kherson State University, Kherson http://orcid.org/0000-0001-7574-4133
M. Vinnyk Kherson State University, Kherson https://orcid.org/0000-0002-2475-7169
M. Poltoratskiy Kherson State University, Kherson https://orcid.org/0000-0001-9861-4438
Y. Tarasich Kherson State University, Kherson http://orcid.org/0000-0002-6201-4569
A. Bystriantseva Kherson State University, Kherson http://orcid.org/0000-0003-0611-1548
K. Panova Kherson State University, Kherson http://orcid.org/0000-0002-6967-6821
Y. Spivakovska Kherson State University, Kherson http://orcid.org/0000-0001-7574-4133

DOI:

https://doi.org/10.14308/ite000678

Keywords:

scientific activity, information systems, scientometric systems, bibliometric systems, scientometric indicators, automatic ratings

Abstract

Our time is characterized by the phenomenal acceleration of knowledge accumulation and the complication of its structure. Today information technologies are one of main ways to arrange and create effective tools for organizing the interaction and processing large amount of information. Nowadays academic institutions need to rely on special research, analysis of accumulated achievements and, on this basis, to develop forecasts, identify trends and prospects for the development of a scientific or other industry, and evaluate its potential. Today many information systems attempt to create methods and technologies of processing and saving information on the activities of scientists.
The article provides a brief overview of rating systems for scientometric indices of universities. In our opinion, information of university’s scientific activity should be presented in the rating form, which gives an opportunity to analyze development in different directions and changes. The key idea of the article is presenting of our experience in developing system of automatic construction of ratings of scientific organizations based on their scientometric indicators in Scopus, Google Scholar and Web of Science.
The main task of the system is automatic construction of consolidated rating of scientists, research groups, and organizations according to indicators of processed scientometric systems (Scopus, Google Scholar and Web of Science). These indicators are h-index, citations (numbers of total citations of documents that are indexed by the system), total number of scientist’s publications.
The philosophy of the system is providing open data of different scientometric systems, and possibility to deploy our system in other organizations and customize it for individual goals and tasks.

Downloads

Download data is not yet available.

Metrics

Metrics Loading ...

References

<uk>
1. Spivakovsky, A., Vinnik, M., Poltoratskiy, M., Tarasich, Y., Panova, K., Melnychenko, A. (2018). Development of Rating Systems for Scientometric Indices of Universities. ICT in Education, Research and Industrial Applications: Integration, Harmonization and Knowledge Transfer. Proc. of the 14th Int. Conf. ICTERI 2018, vol. 2104, 420 - 430.
2. Elsevier. (2018). The largest database of peer-reviewed literature. Retrieved from https://www.elsevier.com/solutions/scopus.
3. National library of Ukraine (2014). Scientometric databases. Retrieved from http://www.nbuv.gov.ua/node/1367.
4. Regional Center of New Information Technologies (2015). Science Citation Index for scientists. Retrieved from http://index.petrsu.ru/.
5. Spivakovsky, A., Vinnyk, M., & Tarasich, Y. (2015). Web Indicators of ICT Use in the Work of Ukrainian Dissertation Committees and Graduate Schools as Element of Open Science. Information and Communication Technologies in Education, Research, and Industrial Applications. ICTERI 2015. Communications in Computer and Information Science, vol 594, 3 - 19.
6. Spivakovsky, A., Vinnyk, M., Tarasich, Y., Poltoratskiy M. (2016). Design and development of information system of scientific activity indicators. ICT in Education, Research and Industrial Applications: Integration, Harmonization and Knowledge Transfer. Proc. 12th Int. Conf. ICTERI 2016, vol. 1614, 103 - 110.
7. Lowenstein, V. (1965). Binary codes with correction for deletions, insertions and substitutions of character. Reports, USSR Academy of Sciences 163.4.
8. Kherson State University (2017). International Projects. Retrieved from http://www.kspu.edu/.
9. Dell-EMC (2011). World's Data More Than Doubling Every Two Years. Retrieved from https://www.emc.com/about/news/press/2011/20110628- 01.htm.
10. Hartley, R. & Barnden, J. (2013). Semantic Networks: Visualizations of Knowledge. Computer Science: New Mexico State University. Retrieved from https://www.cs.nmsu.edu/~rth/ publications/TICS.pdf.
11. Romanov, A. & Terekhov, A. (1997).The mathematical model of productivity and age-structured scientific community evolution. Scientometrics, 39,3.
12. Index Copernicus (2012). ICI Journals Master List. Retrieved from http://jml2012. indexcopernicus.com/page.php?page=2.
13. ECMA International (2017). Introducing JSON. Retrieved from http://www.json.org/.
14. Spivakovsky, A., Berezovsky, D. & Tityenok, S. (2012). Functionality of the KSU FEEDBACK 3.0. Informational Technologies in Education, 11, 9 - 18.
15. What is ORCID? (2013). Retrieved from https://orcid.org/about/what-isorcid/mission.
16. Redner, S. (1998). How popular is your paper? An empirical study of the citation distribution. The European Physical Journal B-Condensed Matter and Complex Systems, Vol. 4, №. 2, 131 - 134.
</uk>
<en>
1. Spivakovsky, A., Vinnik, M., Poltoratskiy, M., Tarasich, Y., Panova, K., Melnychenko, A. (2018). Development of Rating Systems for Scientometric Indices of Universities. ICT in Education, Research and Industrial Applications: Integration, Harmonization and Knowledge Transfer. Proc. of the 14th Int. Conf. ICTERI 2018, vol. 2104, 420 - 430.
2. Elsevier. (2018). The largest database of peer-reviewed literature. Retrieved from https://www.elsevier.com/solutions/scopus.
3. National library of Ukraine (2014). Scientometric databases. Retrieved from http://www.nbuv.gov.ua/node/1367.
4. Regional Center of New Information Technologies (2015). Science Citation Index for scientists. Retrieved from http://index.petrsu.ru/.
5. Spivakovsky, A., Vinnyk, M., & Tarasich, Y. (2015). Web Indicators of ICT Use in the Work of Ukrainian Dissertation Committees and Graduate Schools as Element of Open Science. Information and Communication Technologies in Education, Research, and Industrial Applications. ICTERI 2015. Communications in Computer and Information Science, vol 594, 3 - 19.
6. Spivakovsky, A., Vinnyk, M., Tarasich, Y., Poltoratskiy M. (2016). Design and development of information system of scientific activity indicators. ICT in Education, Research and Industrial Applications: Integration, Harmonization and Knowledge Transfer. Proc. 12th Int. Conf. ICTERI 2016, vol. 1614, 103 - 110.
7. Lowenstein, V. (1965). Binary codes with correction for deletions, insertions and substitutions of character. Reports, USSR Academy of Sciences 163.4.
8. Kherson State University (2017). International Projects. Retrieved from http://www.kspu.edu/.
9. Dell-EMC (2011). World's Data More Than Doubling Every Two Years. Retrieved from https://www.emc.com/about/news/press/2011/20110628- 01.htm.
10. Hartley, R. & Barnden, J. (2013). Semantic Networks: Visualizations of Knowledge. Computer Science: New Mexico State University. Retrieved from https://www.cs.nmsu.edu/~rth/ publications/TICS.pdf.
11. Romanov, A. & Terekhov, A. (1997).The mathematical model of productivity and age-structured scientific community evolution. Scientometrics, 39,3.
12. Index Copernicus (2012). ICI Journals Master List. Retrieved from http://jml2012. indexcopernicus.com/page.php?page=2.
13. ECMA International (2017). Introducing JSON. Retrieved from http://www.json.org/.
14. Spivakovsky, A., Berezovsky, D. & Tityenok, S. (2012). Functionality of the KSU FEEDBACK 3.0. Informational Technologies in Education, 11, 9 - 18.
15. What is ORCID? (2013). Retrieved from https://orcid.org/about/what-isorcid/mission.
16. Redner, S. (1998). How popular is your paper? An empirical study of the citation distribution. The European Physical Journal B-Condensed Matter and Complex Systems, Vol. 4, №. 2, 131 - 134.
</en>