Skip to main content
SpringerLink
Log in

Publication Activity as a Research Efficiency Indicator by the Example of Chemical Organizations

  • Organization of Research
  • Published:
Herald of the Russian Academy of Sciences Aims and scope Submit manuscript

Abstract—

The results of a scientometric analysis of publications of scientific chemical organizations for 2015–2019, presented in the Web of Science database, are given. Seven groups of scientific categories are considered in the analysis: chemistry, electrochemistry, green & sustainable science & technology, materials sciences, nanotechnology, polymers, and quantum calculations. For each group, the contribution of articles published in journals of different quartiles has been estimated. It is shown that the role of international cooperation in the creation of articles depends significantly on the subject area. Keywords characterizing each of the subject areas analyzed have been determined.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1.
Fig. 2.
Fig. 3.
Fig. 4.
Fig. 5.
Fig. 6.
Fig. 7.
Fig. 8.
Fig. 9.

Similar content being viewed by others

REFERENCES

  1. A. Martín-Martín, E. Orduna-Malea, M. Thelwall, and E. D. López-Cózar, “Google Scholar, Web of Science, and Scopus: A systematic comparison of citations in 252 subject categories,” J. Informetrics 12 (4), 1160–1177 (2018).

    Article  Google Scholar 

  2. J. Zhu and W. Liu, “A tale of two databases: The use of Web of Science and Scopus in academic papers,” Scientometrics 123 (1), 321–335 (2020).

    Article  Google Scholar 

  3. I. V. Zibareva, L. Yu. Ilina, and B. L. Alperin, “Russian Science Citation Index: Areas for development identified by active users,” Sci. Tech. Inf. Process. 45 (2), 106–109 (2018).

    Article  Google Scholar 

  4. M.-A. Sicilia, S. Sánchez-Alonso, and E. García-Barriocanal, “Comparing impact factors from two different citation databases: The case of Computer Science,” J. Informetrics 5 (4), 698–704 (2011).

    Article  Google Scholar 

  5. G. Ennas and M. C. Di Guardo, “Features of top-rated gold open access journals: An analysis of the Scopus database,” J. Informetrics 9 (1), 79–89 (2015).

    Article  Google Scholar 

  6. O. E. Sala, C. G. Boone, B. L. Turner, and C. M. Currier, “The sustainability publication gap and its implications,” Curr. Opin. Environ. Sustain. 39, 39–43 (2019).

    Article  Google Scholar 

  7. H. Hottenrott and C. Lawson, “A first look at multiple institutional affiliations: A study of authors in Germany, Japan, and the UK,” Scientometrics 111 (1), 285–295 (2017).

    Article  Google Scholar 

  8. Y. Reingewertz and C. Lutmar, “Academic in-group bias: An empirical examination of the link between author and journal affiliation,” J. Informetrics 12 (1), 74–86 (2018).

    Article  Google Scholar 

  9. M. Walther and B. Melsheimer, “Automated author affiliation processing using Scopus data,” Procedia Comp. Sci. 146, 53–59 (2019).

    Article  Google Scholar 

  10. X. Lu, S. Kataria, W. J. Brouwer, et al., “Automated analysis of images in documents for intelligent document search,” Int. J. Doc. Anal. Recog. 12 (2), 65–81 (2009).

    Article  Google Scholar 

  11. D. Tkaczyk, P. Szostek, M. Fedoryszak, et al., “CERMINE: Automatic extraction of structured metadata from scientific literature,” Int. J. Doc. Anal. Recog. 18 (4), 317–335 (2015).

    Article  Google Scholar 

  12. Z. Nasar, S. W. Jaffry, and M. K. Malik, “Information extraction from scientific articles: A survey,” Scientometrics 117 (3), 1931–1990 (2018).

    Article  Google Scholar 

  13. N. Milosevic, C. Gregson, R. Hernandez, and G. Nenadic, “A framework for information extraction from tables in biomedical literature,” Int. J. Doc. Anal. Recog. 22 (1), 55–78 (2019).

    Article  Google Scholar 

  14. M. Bukowski, S. Geisler, T. Schmitz-Rode, and R. Farkas, “Feasibility of activity-based expert profiling using text mining of scientific publications and patents,” Scientometrics 123 (2), 579–620 (2020).

    Article  Google Scholar 

  15. W. Liu, L. Tang, and G. Hu, “Funding information in Web of Science: An updated overview,” Scientometrics 122 (3), 1509–1524 (2020).

    Article  Google Scholar 

  16. R. Long, A. Crawford, M. White, and K. Davis, “Determinants of faculty research productivity in information systems: An empirical analysis of the impact of academic origin and academic affiliation,” Scientometrics 78 (2), 231–260 (2008).

    Article  Google Scholar 

  17. C. A. D’Angelo and N. J. van Eck, “Collecting large-scale publication data at the level of individual researchers: A practical proposal for author name disambiguation,” Scientometrics 123 (2), 883–907 (2020).

    Article  Google Scholar 

  18. Z. Xie, “Predicting the number of coauthors for researchers: A learning model,” J. Informetrics 14 (2), 1–16 (2020).

    Google Scholar 

  19. Y. Zhou, H. Cheng, Q. Li, and W. Wang, “Diversity of temporal influence in popularity prediction of scientific publications,” Scientometrics 123 (1), 383–392 (2020).

    Article  Google Scholar 

  20. L. Y. Il’ina, I. V. Zibareva, and A. A. Vedyagin, “Reflection of reflections: Scientist’s activity in the mirror of bibliometrics,” Kinet. Catal. 59 (5), 652–666 (2018).

    Article  Google Scholar 

  21. I. V. Zibareva, L. Y. Ilina, B. L. Alperin, and A. A. Ve-dyagin, “The scientometric profile of Boreskov Institute of Catalysis,” Herald Russ. Acad. Sci. 89 (3), 259–270 (2019).

    Article  Google Scholar 

  22. I. V. Zibareva, L. Y. Ilina, B. L. Alperin, and A. A. Ve-dyagin, “Boreskov Institute of Catalysis: Sixty years of research and development,” React. Kinet. Mech. Catal. 127 (1), 3–17 (2019).

    Article  CAS  Google Scholar 

  23. I. V. Zibareva, A. A. Vadyagin, and L. Y. Ilina, “ Bibliometric performance of a scientific organization in retrospect and in perspective,” Tr. GPNTB SO RAN, No. 12-1, 337–346 (2017).

  24. I. V. Zibareva, A. A. Vedyagin, and V. I. Bukhtiyarov, “Kinetika i Kataliz: 55 years in the bibliometric dimension,” Kinet. Catal. 57 (1), 1–16 (2016).

    Article  CAS  Google Scholar 

  25. B. L. Alperin, I. V. Zibareva, and A. A. Vedyagin, “Analysis of scholarly articles’ publication speed with SciAct CRIS system,” Bibliosfera, No. 1, 83–92 (2020).

    Google Scholar 

  26. I. V. Zibareva, L. Y. Ilina, and A. A. Vedyagin, “Catalysis by nanoparticles: The main features and trends,” React. Kinet. Mech. Catal. 127 (1), 19–24 (2019).

    Article  CAS  Google Scholar 

  27. P. T. Anastas and J. C. Warner, Green Chemistry: Theory and Practice (Oxford Univ. Press, New York, 1998).

    Google Scholar 

Download references

Funding

This article was supported by the Russian Ministry of Science and Education, subsidy agreement no. 05.601.21.0020 of November 8, 2019 (unique identifier of the agreement RFMEFI60119X0020), Study of the Mechanisms of Adaptive Formation of Human Resources for Carrying Out Various-Scale Research Programs in Priority Areas of the Scientific and Technological Development of the Russian Federation.

Author information

Authors and Affiliations

  1. Lebedev Institute of Physics, Russian Academy of Sciences, Moscow, Russia

    V. V. Koroleva, O. V. Ivanov, A. A. Vedyagin, A. S. Lyadov, A. V. Leonidov & A. V. Kolobov

  2. Boreskov Institute of Catalysis, Siberian Branch, Russian Academy of Sciences, Novosibirsk, Russia

    A. A. Vedyagin

  3. Topchiev Institute of Petrochemical Synthesis, Russian Academy of Sciences, Moscow, Russia

    A. S. Lyadov

Authors
  1. V. V. Koroleva
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. O. V. Ivanov
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. A. A. Vedyagin
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. A. S. Lyadov
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. A. V. Leonidov
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. A. V. Kolobov
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to V. V. Koroleva, O. V. Ivanov, A. A. Vedyagin, A. S. Lyadov, A. V. Leonidov or A. V. Kolobov.

Additional information

Translated by B. Alekseev

Valentina Vladimirovna Koroleva is an Engineer of the Laboratory of Complex Systems Mathematical Modeling of the Lebedev Physical Institute, RAS (FIAN). Oleg Viktorovich Ivanov, Cand. Sci. (Phys.‒Math.), is a Senior Researcher of the FIAN Laboratory of Superconductivity Theory and Statistical Physics of Complex Systems and the FIAN Laboratory of Complex Systems Mathematical Modeling and Deputy Director for Development of the same institute. Alexei Anatol’evich Vedyagin, Cand. Sci. (Chem.), is Head of the Laboratory of Nanostructured Catalysts and Sorbents and Deputy Director for Science of the Boreskov Institute of Catalysis of the RAS Siberian Branch (IC SB RAS) and a Leading Researcher of the FIAN Laboratory of Complex Systems Mathematical Modeling. Anton Sergeevich Lyadov, Cand. Sci. (Chem.), is Head of the Sector of Petroleum Chemistry of the Topchiev Institute of Petrochemical Synthesis (TIPS RAS) and a Senior Researcher of the FIAN Laboratory of Complex Systems Mathematical Modeling. Andrei Vladimirovich Leonidov, Dr. Sci. (Phys.‒Math.), is a Leading Researcher of the FIAN Laboratory of High Energies. Andrei Vladimirovich Kolobov, Cand. Sci. (Phys.‒Math.), is a Senior Researcher of the FIAN Laboratory of Complex Systems Mathematical Modeling and Deputy Director for Science of this institute.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Koroleva, V.V., Ivanov, O.V., Vedyagin, A.A. et al. Publication Activity as a Research Efficiency Indicator by the Example of Chemical Organizations. Her. Russ. Acad. Sci. 90, 607–617 (2020). https://doi.org/10.1134/S1019331620050147

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1134/S1019331620050147

Keywords:

Search

Navigation