Scientometric Indicators Research Articles

An analysis of scientometric data and publication policies of rheumatology journals.

Scientometric indexes, based on citations, may be increased by open access (OA) publishing. We aimed to present the scientometric data of of rheumatology journals and analyze the scientometric data of rheumatology journals according to the OA publication policy. Scientometric indexes and bibliometric data of 22 journals were obtained from Clarivate Analytics InCites, Scopus, and Scimago Journal & Country Rank websites. We included journal impact factor (JIF), CiteScore (CS), Hirsch index (HI), Source Normalized Impact per Paper (SNIP), Eigenfactor score (ES), and Scientific Journal Ranking (SJR). We separated the OA publishing policies into full OA and hybrid OA. The US dollar (USD) was used as the requested fee unit. All pairs of scientometric indexes had positive significant correlations. However, a journal in the first quartile of JIF was observed in the second quartile of CS, SNIP, and SJR, and the last quartile of ES and HI. Scientometric indexes of of full and hybrid OA journals were similar, apart from HI, which was higher in hybrid OA journals (p = 0.03, Mann-Whitney U test). However, full OA journal fees were less expensive by a median of 935 USD (p = 0.007, Mann-Whitney U test). We recommend that the JIF and HI pair or the ES paired with CS or SNIP be used together to evaluate rheumatology journals. We failed to show that the OA model positively affects the scientometric indexes of rheumatology journals; our results contradict the literature reporting that the OA publication model causes an increase in citations. Key Points •Clinicians should understand the scientometric indexes in rheumatology and if open access publishing affects citations (therefore, scientometric indexes). •The JIF and HI pair or the ES paired with CS or SNIP can be used to express different rankings since they are based on different databases and use different calculation methods. •We show that OA publication does not affect citations or scientometric indexes of rheumatology journals. •When choosing a rheumatology journal to publish OA, rheumatologists should consider individual OA citation patterns and APC charges together.

Foreign experience in evaluating the efficiency of scientific and pedagogical research

The article is devoted to the analysis of foreign experience in determining the criteria for assessing the effectiveness of scientific and pedagogical research. Thus, the problems of qualified analysis of the source base and reproducibility of research, the use of formal scientometric indicators, altmetric approaches, and digital libraries are considered. Another conclusion of authors is to ensure the reliability of the results, and, accordingly, for higher evaluation indicators of research performance, peer-reviewed publications indexed in scientometric databases should be used as primary sources. At the same time, the implementation of a digital identifier (first of all DOI), the provision of open data of research results, and the availability of copies in digital institutional repositories also contribute to higher performance indicators of scientific and pedagogical research. Despite the implementation of various new scientometric indicators, still the most used is the citation (H-index). Altmetric indicators receive data from social networks. Articles are published in them have a faster release of the results. But many scientists still doubt whether there is a direct relationship between the publication impact according to the classical and altmetric approaches. The main reason for this is the authors’ ability to artificially influence some impact indicators.

Studies on Relative Growth Rate and Doubling Time of Publications Productivity of Nuclear Medicine Research

Scientometrics is a branch of the library and information science. Scientometric tools can be used to quantify and compare the scientific activities at various levels of collection including institutions, sectors, provinces, and countries. They can also be used to measure research collaborations, map scientific networks, and monitor the evolution of scientific fields. Scientometric indicators give policy-makers objective, reproducible, and therefore verifiable information that goes away from the unreliable. Scientometrics is anxious about the quantitative features and characteristics of science and scientific research. Scientometrics is a restraint, which uses statistical and computational techniques to realize the structure and changing aspects of science. The study shows that the Authorship Pattern in Nuclear Medicine literature fluctuates from single-authored publications to 78 authored publications during the study period 1991-2020. As per the analysis of the table, the highest number of research output by single-authored was 14.06% with 1776 contributions followed by double authored contributions was 13.07% (1651) and three authored contributions were 12.59% (1590).

АНАЛІЗ НАУКОМЕТРИЧНИХ ПОКАЗНИКІВ ЖУРНАЛУ «ТЕХНІЧНА ЕЛЕКТРОДИНАМІКА» 2018–2020 рр.

The directions of development of the journal "Technical Electrodynamics" in recent years are considered, its main scientometric indicators according to Scopus data for 2020 are analyzed, their comparison with the indicators of the previous two years is made. It is noted that indicators such as SJR, percentile, international cooperation decreased, the Hirsch index and quartiles remained at the same level. Ways to improve the performance of the journal are suggested. References 6.

Scientific publications – the bad, the good, for a fistful of dollars

The article is devoted to the problem of assessing the quality of scientific publications. It is emphasized that the formal ranking of an article is currently determined, as a rule, not so much by the data obtained or formulated concepts, as by the scientometric indicators of the corresponding journals. Approaches to determining the ranking of an article based on the analysis of its citation (impact factor and its analogues) and the number of mentions in social networks (so called altmetrics), as well as the number of downloads of the paper from the publisher’s website are considered. The authors emphasize the significant role of the appearance of author-paid articles in the current change in the situation with scientific publications. It is assumed that the thorough commercialization of the process of publishing their works by scientists has led to a serious deterioration in their scientific component due to the reducing requirements for the format and content of manuscripts sent to the editors of paid journals. The authors express the hope that the “informal” approach to the evaluation of scientific articles, which is based on their content, but not the ratings of the editions that published these works, has not lost its relevance even at the present stage.

The knowledge domain of crowd dynamics: Anatomy of the field, pioneering studies, temporal trends, influential entities and outside-domain impact

The literature of pedestrian, crowd and evacuation dynamics is captured in its approximate full scope and is analysed at various levels using scientometric indicators of its underlying articles (N≈6200). The analyses provide new insight into the structural make-up of this field, its distribution across various disciplines, its temporal and historical patterns of development, as well as its pioneering and influential entities (i.e., articles and authors). The analysis establishes that the field has exerted a high degree of influence beyond its borders while identifying these areas of influence. Studies with greatest impact within and beyond the borders of crowd dynamics literature; as well as, pioneering but neglected studies of the field are identified. It is determined that the beginning of the twenty-first century marks the most important milestone of this field, an intellectual turning point that set the field to become a standalone research domain. Temporal analysis indicates certain paradigm shifts in crowed dynamics research during the past decade. It identifies two streams of activities labelled “empirical methods” and “crowd counting/visual crowd analysis” as the two youngest and currently hottest research streams of this field. Outcomes suggest that further interactions and collaborations between the computer vision and the mainstream of crowd researchers could be warranted. This could lead to the next generations of data-driven crowd models and prevent the field from going to a state of stagnation. It is also hoped that these outcomes contribute to enhancing the quality (i.e., specificity and inclusiveness) of document referencing in crowd dynamics papers.

A supervised machine learning approach to author disambiguation in the Web of Science

• Machine learning is used for author name disambiguation in the Web of Science. • Supervised learning via the author identifier of Researcher ID through random forest and logistic regression. • Name Frequency-based, bibliographic, thematic, and address-based features are used and evaluated. • Missing first name data is included to make the machine learning robust to quality changes of new data. • Pairwise paper predictions are clustered into author profiles via infomap graph-community detection method. • Cluster measure of average K-Metric arrives at >0.78 values and suggest reasonable performance of our appraoch. Author-level scientometric indicators are an important tool in individual and institutional-based research assessment and require high-quality author-publication profiles. To address this need, our study developed a robust supervised machine learning approach in combination with graph community detection methods to disambiguate author names in the Web of Science publication database. We used the unique author identifier Researcher ID to retrieve true authorship data of 1,904 scientists and trained a random forest and a logistic regression classifier on 1.2 million corresponding publication pairs with authors that share the same last name and first name initial. To do this, we reviewed a vast set of paper and author characteristics and randomly included missing data to make our machine learning robust to quality changes of new publication data. In the application on an unseen test set, we achieved F1 scores of 0.82 in the random forest and 0.75 in the logistic regression model. Subsequently, we evaluate feature performance and apply the infomap graph community detection algorithm to identify all publications belonging to an author. The community detection results in reasonable cluster metrics (Mean K-Metric in logistic regression-based model = 0.78 and = 0.81 in random forest-based model). Finally, we test our algorithm on a large surname-initial block (“Muller, M.”) and demonstrate speed and predictive performance.

Makerspaces: indicadores cienciométricos e implicaciones para la innovación, la educación y el emprendimiento

Objetivo: identificar temporalidad, áreas temáticas, instituciones, países, publicaciones y conceptos más relevantes en la construcción de los makerspaces como objeto de estudio asociado a la educación, la innovación, el emprendimiento y el aprendizaje.Diseño metodológico: es una investigación exploratoria, a partir de la recopilación de publicaciones en Scopus relacionadas con makerspaces y su conjunción con los conceptos arriba señalados, se derivan indicadores cienciométricos para establecer su importancia como tema de estudio y se crean mapas de conceptos a través del programa VOSviewer para identificar los temas que le son correlativos.Resultados: es un concepto de creciente interés. Involucra 23 áreas temáticas, con predominio de las ciencias sociales; los títulos de publicaciones y temas correlativos refieren a educación STEM y, en menor medida, emprendimiento y negocios.Limitaciones de la investigación: es una investigación exploratoria. Aporta referentes sobre temas y conceptos a partir de los cuales se problematizan los makerspaces; no profundiza en explicaciones, sino que muestra un panorama de temáticas que los estudian, lo que es relevante para encuadrar el tema que ha sido poco estudiado en México.Hallazgos: los makerspaces, surgidos de la premisa “do it yourself”, ofrecen un modelo de aprendizaje informal fuera de los espacios tradicionales formales. Se han vuelto tema de interés creciente para la educación y el emprendimiento. Por lo tanto, pueden entenderse como espacios generadores de nuevas dinámicas de aprendizaje basado en la colaboración, trasladables a los espacios formales de la educación tecnológica, emprendimiento y de complejización de los procesos de innovación.

Do researchers know what the h-index is? And how do they estimate its importance?

The h-index is a widely used scientometric indicator on the researcher level working with a simple combination of publication and citation counts. In this article, we pursue two goals, namely the collection of empirical data about researchers’ personal estimations of the importance of the h-index for themselves as well as for their academic disciplines, and on the researchers’ concrete knowledge on the h-index and the way of its calculation. We worked with an online survey (including a knowledge test on the calculation of the h-index), which was finished by 1081 German university professors. We distinguished between the results for all participants, and, additionally, the results by gender, generation, and field of knowledge. We found a clear binary division between the academic knowledge fields: For the sciences and medicine the h-index is important for the researchers themselves and for their disciplines, while for the humanities and social sciences, economics, and law the h-index is considerably less important. Two fifths of the professors do not know details on the h-index or wrongly deem to know what the h-index is and failed our test. The researchers’ knowledge on the h-index is much smaller in the academic branches of the humanities and the social sciences. As the h-index is important for many researchers and as not all researchers are very knowledgeable about this author-specific indicator, it seems to be necessary to make researchers more aware of scholarly metrics literacy.

A Framework to Assess the Citation Performance of Complex Innovation Systems.

Scientometric indicators are useful to evaluate the relevance of scientific research, to prepare rankings, and to evaluate and inform research policies. That is why the choice of appropriate indicators is a matter of primary concern. This article aims to introduce a framework to decide the appropriate type of indicator for assessing the citation-based performance of complex innovation systems. The framework is two-fold: First, it brings the methodology to decide when the use of standard average based indicators is granted, and when scale-invariant indicators are mandatory. Second, it provides the procedures to build scale-invariant indicators to assess the relative impact of complex innovation systems. The framework is validated empirically through the evaluation of the relative impact of the Chilean science system in 2017. The result suggests that the Chilean science system has characteristics of a complex innovation system such as the distribution of citations fits to a power law with an exponential cutoff and a power-law correlation between the size of the system and its impact . Furthermore, the framework shows to be efficient to compare fields of vastly different sizes.

Current issues and critical tasks of university science

The Moscow State Technical University of Civil Aviation celebrates the 50th anniversary as a well-known scientific and educational center integrated into the national scientific and innovation system. The strategic government initiatives are based on the recognition of scientific and technological achievements as the key factors in the transition of the Russian economy into a qualitatively new development model; the formation of a geopolitical status that determines the country's position in the global economy, the opportunity and conditions for its integration into the world economic system; competitiveness in global high-tech markets. The analysis of the targets results of the State Acts, including the Strategy for Innovative Development of the Russian Federation for the period up to 2020, shows that despite the undertaken efforts, considerable positive changes in state and effectiveness of national science in general as well as university science in particular, have not taken place yet. The planned values of individual indicators (domestic research and development costs, the share of the higher education sector in domestic research costs, scientometric indicators of Russian authors’ publications in the international databases of Scopus and Web of Science, etc.) have not been achieved. The reasons for unsatisfactory dynamics are considered. It is noted that university science is the richest state-resource that means intellectual capital, scientific schools, talented youth, connections with academic research institutes, manufacture and business, which, by means of the appropriate state policy, can make universities the centers for integration of individual subjects of scientific and innovative activity, ensuring a functional connection. The specific aspects of scientific work in industry universities are highlighted. The priority tasks for modernization of research process and innovation activities in MSTUCA are defined in accordance with the University Development Strategy until 2030.

The assessment of the scientific and innovation potential of the Republic of Tatarstan in the global and national contexts: scientometric positioning of the region in the technological paradigms of the Industries 4.0 and 5.0

One of the key priorities of the modern Russian domestic policy lies in gaining competitive advantages in solution of the tasks of global scientific and technological frontiers as the basis for sustainable economic development. Russian economy is oriented towards seeking new growth drivers through technological changes in both traditional and new technology, products and services markets. A breakthrough in the sphere of innovations is possible in the conditions if the applied science would create the system of advanced scientific-technological platform, which is human centered and more resilient for the future. Thus, in the context of drastic technological and structural shifts in the global economic system, Russia’s task of transition towards the new stage of scientific revolution acquires particular relevance. The goal of this article consists in the analysis of scientific and innovation development of the Russian Federation and its regions under the new conditions. Analysis is conducted on the fundamental trends within the framework of transition to a new technological structure, scientometric indicators worldwide, Russia and the Republic of Tatarstan in the context of the prospects for the country’s accomplishment of the new objectives of global scientific and technological agenda. The author determines the central problems in building the integral domestic innovation system in the conditions of external factors; develops the original approach towards assessment of scientific capacity of the universities and academic institutions in the technological paradigms of the Industries 4.0 and 5.0.

Linguistic Diversity Index: A Scientometric Measure to Enhance the Relevance of Small and Minority Group Languages

Current scientometric indexes do not encourage the linguistic diversity of sources cited in academic texts and researchers are not motivated to cite texts written in smaller languages. This diminishes the cultural diversity of the sources cited and limits the representation of small and indigenous cultures. This text proposes a scientometric measure designed to encourage the linguistic diversity of sources cited in articles, books, and papers. The Linguistic Diversity Index is based on two stipulations: (a) the more linguistically diverse the sources, the higher the score, and (b) the rarer the languages cited, the higher the score. If such a metric were used for the evaluation of social science and humanities journals, it would encourage the publication of papers that cite ideas from rarely represented cultural groups such as indigenous nations, ethnic groups from small countries, and other linguistic groups that have been omitted from mainstream scientific discourse. This might help to produce new research, which would help to improve the situation for these groups and create an epistemology that is more just to small cultural groups.

Altmetrics: The awareness and interest

The characteristics of academic users interested in altmetrical infor-mation are defined. The online survey of 302 academic respondents was conduc-ted to reveal the level of awareness and interest of scientific community. The analysis of the responses about altmetrics is supplemented with the data on the respondents' using traditional scientometric information. It was found that with a high degree of interest in traditional scientometric indicators (91.4% of respondents refer to them), altmetrics remained mostly out of the eye of scien-tists. Only 6.6% respondents use altmetrics, while the others are still unfamiliar with altmetrics or do not use them. However, over the half of respondents ex-pressed interest in altmetrics: 11.9% consider the method necessary, and 43% would like to learn more about it. The correlation between academic status and awareness of/or interest in altmetrics was found: applicants and candidates of science and applicants for this degree proved to be more interested in altmetrics information than doctors of science. The correlation between the aware-ness/interest and researcher’s area of studies appeared insignificant. The findings of the study may be used to improve the information support of scientists. The research model can be applied to other groups of library users.

Formation of the scientist image in modern conditions of digital society transformation

The publication considers factors that are influencing formation of scientists image especially: availability to inform scientist or scientific organization about the registration, scientometric indices, use of global identifiers to improve accuracy in calculating indicators, publication of papers in journals with high impact factor, publications in resources that provide visibility in global information space, involvement in global communications system, level of competence. Specialists in various fields of science developed a number of practical recommendations for various techniques and tools that can be used and are helpful to create and to make, both personal image and image of the organization, institution, firm, etc. Also, main directions of using digital technologies to create the image of scientists are identified and substantiated. Scientists formulated recommendations to make their own image using digital systems based on analysis of scientific literature and personal experience: author’s digital identifier ORCID, profiles in international scientometric systems, saved publications in electronic libraries, profiles in social and scientific electronic networks, etc.

Scientometric Data and Open Access Publication Policies of Clinical Allergy and Immunology Journals.

IntroductionThe scientific merit of a paper and its ability to reach broader audiences is essential for scientific impact. Thus, scientific merit measurements are made by scientometric indexes, and journals are increasingly using published papers as open access (OA). In this study, we present the scientometric data for journals published in clinical allergy and immunology and compare the scientometric data of journals in terms of their all-OA and hybrid-OA publication policies.MethodsData were obtained from Clarivate Analytics InCites, Scimago Journal & Country Rank, and journal websites. A total of 35 journals were evaluated for bibliometric data, journal impact factor (JIF), scientific journal ranking (SJR), Eigenfactor score (ES), and Hirsch index (h-index). US dollars (USD) were used for the requested article publishing charge (APC).ResultsThe most common publication policy was hybrid-OA (n = 20). The median OA publishing APC was 3000 USD. Hybrid-OA journals charged a higher APC than all-OA journals (3570 USD vs. 675 USD, p = 0.0001). Very strong positive correlations were observed between SJR and JIF and between ES and h-index. All the journals in the h-index and ES first quartiles were hybrid-OA journals.ConclusionBased on these results, we recommend the use of SJR and ES together to evaluate journals in clinical allergy and immunology. Although there is a wide APC gap between all-OA and hybrid-OA journals, all journals within the first quartiles for h-index and ES were hybrid-OA. Our results conflict with the literature stating that the OA publication model's usage causes an increase in citation counts.

A Scientometric Analysis of Transient Patterns in Recommender System with Soft Computing Techniques

Recommender systems recommend items to users based on their interests and have seen tremendous growth due to the use of internet and web services. Recommendation systems have seen escalating growth rate since late 1990’s. A query on Google Scholar (famous research based search engine) gives 175,000 articles for the query “recommender system”. With such a large database of research/application articles, there arises a need to analyses the data so as to fulfill the basic requirements of effectively understanding the potential of the quantum of literature available so far. The study focuses on the topic of recommender system with various soft computing techniques such as fuzzy logic, neural network and genetic algorithm. The major contribution of this work is the demonstration of progressive knowledge for domain visualization and analysis of recommender system with soft computing techniques. The analysis is supported by various scientometric indicators such as Relative Growth Rate (RGR), Doubling Time (DT), Co-Authorship Index (CAI), AuthorProductivity, Degree of Collaboration, Research Priority Index (RPI), Half Life, Country wise Productivity, Citation Analysis, Page Length Distribution, Source Contributors. This research presents first of its kind scientometric analysis on “recommender system with soft computing techniques”. The present work provides useful parameters for establishing relationships between quantifiable data and intangible contributions in the field of recommender systems.

DEVELOPING AN INTEGRAL INDICATOR OF SCIENTIFIC JOURNALS DEVELOPMENT

Currently, the issue of determining the rating and scientific significance of journals remains very important. It provides a review of the methods for assessing the quality of Russian and foreign journals. Purpose of work. The aim of the study is to develop mathematical models allowing to simulate and predict the dynamics of an integral indicator of the scientific development of a journal. Materials and methods. The paper defines the set of scientometric indicators for assessing the scientific significance of journals. The independence of factors was investigated using a matrix of matching correlation coefficients. A method for obtaining a mathematical dependence that reflects the relationship between the selected scientometric indicators and the integral indicator, based on the application of the multidimensional average method, is proposed. The ranking of factors is performed by the expert method. The weight coefficients were calculated using the Fishburne method. As the source data, we used available information from the scholarly e-library. The results of the study. Using the formula obtained, the values of the integral indicator for 7 years have been calculated from the source data using the example of the Journal 1. Using a similar technique, we derived the dependence of the integral indicator on key indicators of the Journal 2, for which the Science Index indicator has not been defined. The forecast of bibliometric indicators (factors) and the integral index of the journal for the next three years is made. To predict the nature of the change in factors (number of citations), anquadratic and cubic dependence is selected. The influence of joint change of factors on the integral indicator is investigated. Discussion and conclusions. The developed mathematical models can be used to analyze changes in the complex of scientometric indicators over time when designing a development strategy for scientific journals and making managerial decisions.

A bibliometric analysis of measures for controlling slope and watershed erosion from 2010 to 2019

The bibliometric method is a scientific method that uses mathematical and statistical methods to quantitatively analyze all knowledge carriers, which can effectively grasp the subject knowledge context. Controlling slope and watershed erosion has received wide attention from scholars from various countries. So the bibliometric method was employed to evaluate the global scientific production of measures for controlling slope and watershed erosion from 2010 to 2019 and sought the characteristics of publication outputs and tendencies from the articles. The basic data were obtained from the Science Citation Index Expanded from the Web of Science. The several aspects were analysed including document language, annual outputs and distribution of journals, subject, authors, highly cited papers as well as frequency of author keywords. The results showed that annual output of the related scientific articles kept a steady rise from 2013 to 2019. Chinese Academy of Sciences, Northwest A&F University and Ministry Water Resources were mainly research institutes, which have published a lot of articles. In addition, Jean Poesen, from University of Mekelle, was the most productive author who has published 28 articles in the field of controlling slope and watershed erosion. The keywords of articles on controlling slope and watershed erosion were also analysed by using scientometric indexes. By analysing frequency of keywords in 10 periods, the current research emphases were discovered. The result showed that “Soil erosion”, “Runoff” and “Erosion” are the top 3 author keywords in this field. And the “soil-erosion” always was the top 1 keywords in the research of watershed erosion. Through analysis of the keywords, it can be known that soil erosion in the plains, simulation of erosion, and the impact of climate change on erosion are research hotspots.

О ТЕНДЕНЦИЯХ И ПЕРСПЕКТИВАХ РАЗВИТИЯ НАУКИ В РОССИИ

The article deals with the range of problems related to the development, financing and organization of research and innovation sectors of Russia. An analysis on the number of organizations engaged in research and development as well as on the personnel of scientific institutions have been carried out based on the statistical data. It examines a number of indicators of research funding and that of the structure of internal costs for research and development. 
 Special attention is paid to the issue of the financial support of Russian science, a comparative analysis with similar indicators of developed countries. The author has demonstrated and analyzed some scientometric indices. The article substantiates the need to reconsider the organization and management of the development of national science, and to build the system of science and business cooperation. Directions that will contribute to the strengthening and development of the country’s scientific potential have been proposed.