INFRASTRUCTURE FOR LARGE SCALE HARVESTING OF WEBOMETRIC INDICATORS
https://doi.org/10.20913/2618-7515-2020-1-86-97
Abstract
The main purpose of scientific rankings is not only comparison, but also stimulating the development of universities and research institutes, improving the effectiveness of their educational and research processes. However, existing webometric ratings are not suitable for this task because of the lack of the possibility of their analysis and verification. The solution is to change the approach to webometric measurements, to perform them based on the principles of regular collection and openness of source data. The article discusses the indicators used in the tasks of academic webometrics, their reliability and stability, substantiates the need for regular collection of the values of these indicators to improve the quality of data and analyze their dynamics. Based on the experience of implementing a project to research the Russian academic web space (http://www. webometrix.ru), problems are analyzed that arise when collecting the values of webometric indicators of sites of research organizations and institutions of higher education on a global scale with a frequency of at least 1 time per month.
The author describes a distributed system for collecting values of webometric indicators and evaluates the necessary degree of parallelization of the process. The developed approach is universal for the tasks of collecting large amounts of information by the method of extracting data from website pages, and the collection of webometric data is also relevant for the tasks of analyzing other thematic segments of web space, such as library websites.
About the Author
D. V. Kosyakov
State Public Scientific Technological Library of the Siberian Branch of the Russian Academy of Sciences (SPSTL SB RAS); Trofimuk Institute of Petroleum Geology and Geophysics of the Siberian Branch of the Russian Academy of Sciences (IPGG SB RAS)
Russian Federation
Russian Federation
Kosyakov Denis Viktorovich – Deputy Director for Development, State Public Scientific Technological Library of the Siberian Branch of the Russian Academy of Sciences (SPSTL SB RAS), Trofimuk Institute of Petroleum Geology and Geophysics of the Siberian Branch of the Russian Academy of Sciences (IPGG SB RAS), Novosibirsk
References
1. Björneborn L., Ingwersen P. Toward a basic framework for webometrics // Journal of the American Society for Information Science and Technology. 2004. V. 55, N14. P. 1216–1227. DOI: 10.1002/asi.20077.
2. Faba-Pérez P. и др. Comparative analysis of webometric measurements in thematic environments // Journal of the American Society for Information Science and Technology. 2005. V. 56, N8. P. 779–785. DOI:10.1002/asi.20161.
3. Payne N., Thelwall M. A longitudinal study of academic webs: Growth and stabilisation // Scientometrics. Springer Netherlands, 2007. V. 71, N3. P. 523–539. DOI: 10.1007/s11192-007-1695-y.
4. Aguillo I. F., Granadino B., Ortega J. L., Prieto J. A. Scientific research activity and communication measured with cybermetrics indicators // Journal of the American Society for Information Science and Technology. 2006. V. 57, N10. P. 1296–1302. DOI: 10.1080/03797720802254031.
5. Aguillo I. F., Ortega J. L., Fernández M. Webometric Ranking of World Universities: Introduction, Methodology, and Future Developments // Higher Education in Europe. 2008. V. 33, N2–3. P. 233–244. DOI: 10.1080/03797720802254031.
6. Vargas-Quesada B. и др. Web structure and influence of the Arab universities of the MENA zone (Middle East and North Africa): Visualization and analysis. 2013. V. 65, N6. P. 623–643. DOI: 10.1108/AP-10-2012-0082.
7. Tafaroji R. и др. Webometric analysis of Iranian medical universities according to visibility, size and rich files // Webology. University of Tehran, 2014. V. 11, N1.
8. Ma F., Qiu J. Study on web performance of Chinese universities // Wuhan Daxue Xuebao (Xinxi Kexue Ban)/ Geomatics and Information Science of Wuhan University. 2010. V. 35, N SPECIAL ISSUE2. P. 146–151.
9. Shokin Yu.I., Klimenko O. A., Rychkova E. V., Shabalnikov I. V. Рейтинг сайтов научных организаций СО РАН // Вычислительные технологии. 2008. V. 13, N3.P. 128–135.
10. Antopolsky A., Polyak Yu., Usanov V. Development of a vebometric index of scientific and educational institutions of Russia // Information resources of Russia. 2013. V. 4. P. 16–24.
11. Khanchuk A. I., Naumova V. V. Information Space of the Far East Branch of the Russian Academy of Sciences. // Herald of the FEB RAS. 2009. N4. P. 122–129.
12. Jati H., Dominic D. D. A New Approach of Indonesian University Webometrics Ranking Using Entropy and PROMETHEE II // Procedia Computer Science. Elsevier B. V., 2017. V. 124. P. 444–451. DOI: 10.1016/j.procs.2017.12.176.
13. Bar-Ilan J., Levene M., Mat-Hassan M. Dynamics of search engine rankings - A case study // CEUR Workshop Proceedings. 2004. V. 703. P. 3–13.
14. Font-Julian P. I., Ontalba-Ruipérez J. A., OrduñaMalea E. Hit count estimate variability for website-specific queries in search engines: The case for rare disease association websites // Aslib Journal of Information Management. Emerald Group Publishing Ltd., 2018. V. 70, N2. P. 192–213. DOI: 10.1108/AJIM-10-2017-0226.
15. Van den Bosch A., Bogers T., de Kunder M. Estimating search engine index size variability: a 9-year longitudinal study // Scientometrics. Springer Netherlands, 2016. N April. DOI: 10.1007/s11192-016-1863-z.
16. Uyar A. Investigation of the accuracy of search engine hit counts // Journal of Information Science. 2009. V. 35, N4. P. 469–480. DOI: 10.1177/0165551509103598.
17. Thelwall M. Extracting accurate and complete results from search engines: Case study windows live // Journal of the American Society for Information Science and Technology. 2008. V. 59, N1. P. 38–50. DOI:10.1002/asi.20704.
18. Pechnikov A. A. About the webometric indicator «size of a website» // Applied and Industrial Mathematics Review. 2013. V. 20, N4. P. 568.
19. Kosyakov D., Guskov A., Bykhovtsev E. S. Russia's academic institutes as mirrored by webometrics // Herald of the Russian Academy of Sciences. 2016. V. 86, N6. P. 490–499. DOI:10.1134/S1019331616050063.
20. Kosyakov D., Guskov A., Bykhovtsev E. Webometric analysis of Russian scientific and education web // CEUR Workshop Proceedings. 2017. V. 1839.
Review
For citations:
Kosyakov D.V. INFRASTRUCTURE FOR LARGE SCALE HARVESTING OF WEBOMETRIC INDICATORS. Proceedings of SPSTL SB RAS. 2020;(1):86-97. (In Russ.) https://doi.org/10.20913/2618-7515-2020-1-86-97
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