Comparative analysis of Russian and industrialized countries performance on Energy and Fuels, WoS, 2008–2017

Abstract

The selection of basic research priorities plays an important role in efficient science policy. After the economic crisis in 2008 many countries turned its attention to R&D of energy resources. Effective development of R&D could contribute to efficiency of oil and gas processing and improve Russian prosperity. The goal of our study is to examine trends in Russian research performance (RP) and compare them with other leading industrialized countries. More detailed analysis was focused on tracing evolution in the research area (by WoS classification) as Energy&Fuel (E&F), which is invaluable for the Russian economy. Sources of data were Science Citation Index-Expanded (SCI-E) that is the part of Web of Science (WoS), analytical tool InCites and the national database Russian Science Citation Index-Clarivate. World dataset demonstrated the growth rate in total research performance (RP) by 140% (2,006,082 records) in 2017 compared to 2008 (1,416,233 records). Russian RP growth rate was the same as in world dataset in 2008-2017. Our analysis revealed that two of each RA Science Technology and Other Topics, and Energy & Fuels (E&F) demonstrated striking growth rate (in three-fold) comparing with growth rate 140% in the world dataset during 2008-2017. Total amount of Russian RP on E&F consisted of 4237 records indexed in SCI-E and 6300 records indexed in RSCI-C for 10 years. During the last 10 years, Russia significantly improved various citations indicators of RP on E&F. The share of publications in top 1% and top 10% journals increased. Russian RP growth rate on E&F was about 200%. Despite the growth its impact is low compared to leading industrial countries. A significant disparity was revealed in RP distribution by leading organizations in SCI-E and RSCI-C. Powerful Russian oil and gas companies are practically absent among organizations indexed in SCI-E. Contrarily, the national Russian database RSCI-C revealed a network of regional branches of the famous private oil company named "Lukoil". Russian international collaboration (IC) on E&F is significantly less (about 8-10%) than in total Russian RP. The negative factor is low number of IC on E&F with each of traditional Russian partners as Germany and USA. Value of Jaccard index of almost all countries collaborating with Russia (besides Kazakhstan's 0.46) is no higher than 0.2. This indicates significant difference in direction of research. Our data could be useful as a source for effective decision-making. Keywords Bibliometric • Energy and Fuels • Indicators • InCites • WoSThis paper is dedicated to the memory of Judit Bar-Ilan (1958, an outstanding scholar and an inimitable friend and colleague.

Russian Pattern of Altmetrics Usage based on SCI-E Statistics

“…Despite a strong movement of the science community to Open Science, the share of OA journals on chemistry was between 5.2% (Chemistry, Physical) and 8.1% (Chemistry, Inorganic & Nuclear) in the world dataset in 2013. Russian science demonstrated a robust tendency toward "hard sciences" during the studied period (Markusova and et al, 2020). Mathematics is the strongest area of basic research in Russia.…”

“…(see for instance http://www.ras.ru/news/shownews.aspx?id=613a30f8-1475-4d9a-a6a3-75df1501be7a) al, 2018) A few authors described the impact of government's research policy on bibliometric performance (Guskovet.al, 2016,Gilyarevskii et. al, 2019, Moed et.al, 2018, Markusova et. al, 2020.There are further ambitious goals established in Decree N 204 published in December 2018 (http://static.kremlin.ru/media/ acts/files/0001201805070038.pdf).…”

“…Nuclear: 33.4 and 21.2 corre-publications in total Russian RO(Markusova et al, 2020). However, SC Neurosciences has a higher citation impact (TC score) 7.8 compared with 6.1 in SC Biochemistry &Molecular Biology (InCites, 2010-2014).…”

Mapping and Scientometric Measures on Research Publications of Energy Storage and Conversion

“…Duan and Guan [28] they examined the potential motivation for the convergence of knowledge and found law of the convergence of knowledge, using example of solar energy. The authors set up keyword co-occurrence networks from solar energy literature in 2008-2017 [29][30][31]. Van Leeuwen and Tijssen [32] discussed combining bibliometric indicators for publication performance.…”