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While output and impact assessments were initially at the forefront of institutional research evaluations, efficiency measurements have become popular in recent years. Research efficiency is measured by indicators that relate research output to input. The additional consideration of research input in research evaluation is obvious, since the output depends on the input. The present study is based on a comprehensive dataset with input and output data for 50 US universities. As input, we used research expenses, and as output the number of highly-cited papers. We employed Data Efficiency Analysis (DEA), Free Disposal Hull (FDH) and two more robust models: the order-m and order-&alpha, approaches. The results of the DEA and FDH analysis show that Harvard University and Boston College can be called especially efficient compared to the other universities. While the strength of Harvard University lies in its high output of highly-cited papers, the strength of Boston College is its small input. In the order-&alpha, and order-m frameworks, Harvard University remains efficient, but Boston College becomes super-efficient. We produced university rankings based on adjusted efficiency scores (subsequent to regression analyses), in which single covariates (e.g., the disciplinary profile) are held constant.

Purpose: The purpose of this paper is to visualize the structure of SCImago Journal & Country Rank (SJR) coverage of the extensive citation network of Scopus journals, examining this bibliometric portal through an alternative approach, applying clustering and visualization techniques to a combination of citation-based links. Design/methodology/approach:Three SJR journal-journal networks containing direct citation, co-citation and bibliographic coupling links are built. The three networks were then combined into a new one by summing up their values, which were later normalized through geo-normalization measure. Finally, the VOS clustering algorithm was executed and the journal clusters obtained were labeled using original SJR category tags and significant words from journal titles. Findings: The resultant scientogram displays the SJR structure through a set of communities equivalent to SJR categories that represent the subject contents of the journals they cover. A higher level of aggregation by areas provides a broad view of the SJR structure, facilitating its analysis and visualization at the same time. Originality/value: This is the first study using Persson’s combination of most popular citation-based links (direct citation, co-citation and bibliographic coupling) in order to develop a scientogram based on Scopus journals from SJR. The integration of the three measures along with performance of the VOS community detection algorithm gave a balanced set of clusters. The resulting scientogram is useful for assessing and validating previous classifications as well as for information retrieval and domain analysis.

"This is a post-peer-review, pre-copyedit version of an article published in Scientometrics. The final authenticated version is available online at: https://doi.org/10.1007/s11192-015-1568-8”., Cuban scientific output is analyzed for the period 2003-2011, in Scopus database. Based on a set of bibliometric indicators, we try to shed light on the evolution of the volume of scientific output in Cuban and foreign journals, and its distribution and visibility by quartiles. Also analyzed is the citation per document received, broken down by language of publication and type of collaboration. The results reveal patterns and strategies of expansion in scientific communication that may be useful for academic and institutional decision-makers, suggesting means of amending editorial policy to improve scientific quality and international diffusion of output. It is hoped that these results will spur debate about research policies and actions to be taken to enhance the quality of research., This work was made possible through the Short-Term Visiting Fellows Program of the CSIC Instituto de Políticas y Bienes Públicos (IPP) Madrid, Spain

Subject classification arises as an important topic for bibliometrics and scientometrics as to develop reliable and consistent tools and outputs. For this matter, a well delimited underlying subject classification scheme reflecting science fields becomes essential. Within the broad ensemble of classification techniques clustering analysis is one of the most successful. Two clustering algorithms based on modularity, namely, VOS and Louvain methods, are presented in order to update and optimise journal classification of SCImago Journal & Country Rank (SJR) platform. We used network analysis and visualization software Pajek to run both algorithms on a network of more than 18,000 SJR journals combining three citation-based measures, that is, direct citation, co-citation and bibliographic coupling. The set of clusters obtained was termed through category labels assigned to SJR journals and significant words from journal titles. Despite of both algorithms exhibiting slight performance differences, the results showed a similar behaviour in grouping journals and, consequently, they seem to be appropriate solutions for classification purposes. The two new generated algorithm-based classifications were compared to other bibliometric classification systems such as the original SJR one and WoS Subject Categories in order to validate their consistency, adequacy and accuracy. Although there are notable differences among the four classification systems analysed, we found a certain coherence and homogeneity among them.

Drawing on social choice theory we derive a rationale in which each reviewer is asked to provide his or her second, third, and fourth choice in addition to his/her first choice recommendation regarding the acceptance/revision/rejection of a given manuscript. All reviewers' hierarchies of alternatives are collected and combined such that an overall ranking can be computed. Consequently, conflicting recommendations are resolved not by asking a third adjudicating reviewer for his/her recommendation as is usual editorial praxis in many scientific journals, but rather by using more information from the available judges. After a brief introduction into social choice theory and a description and justification of the maximum likelihood rule for ranking alternatives, we describe and demonstrate a public available web application that provides easy-to-use tools to apply these methods for aggregating conflicting reviewers' recommendations. This application might be accessed by editors to aid their decision process in case they receive conflicting recommendations by their reviewers., This research was sponsored by the Spanish Board for Science and Technology (MICINN) under grant TIN2010-15157 cofinanced with European FEDER funds

Using data compiled for the SCImago Institutions Ranking, we look at whether the subject area type an institution (university or research-focused institution) belongs to (in terms of the fields researched) has an influence on its ranking position. We used latent class analysis to categorize institutions based on their publications in certain subject areas. Even though this categorization does not relate directly to scientific performance, our results show that it exercises an important influence on the outcome of a performance measurement: Certain subject area types of institutions have an advantage in the ranking positions when compared with others. This advantage manifests itself not only when performance is measured with an indicator that is not field-normalized but also for indicators that are field-normalized.

We propose a method for selecting the research guarantor when papers are co-authored. The method is simply based on identifying the corresponding author. The method is here applied to global scientific output based on the SCOPUS database in order to build a new output distribution by country. This new distribution is then compared with previous output distributions by country but which were based on whole or fractional counting, not only for the total output but also for the excellence output (papers belonging to the 10 % most cited papers). The comparison allows one to examine the effect of the different methodological approaches on the scientific performance indicators assigned to countries. In some cases, there was a very large variation in scientific performance between the total output (whole counting) and output as research guarantor. The research guarantor approach is especially interesting when used with the excellence output where the quantity of excellent papers is also a quality indicator. The impact of excellent papers naturally has less variability as they are all top-cited papers.

In this study we present an application which can be accessed via www.excellence-networks.net and which represents networks of scientific institutions worldwide. The application is based on papers (articles, reviews and conference papers) published between 2007 and 2011. It uses (network) data, on which the SCImago Institutions Ranking is based (Scopus data from Elsevier). Using this data, institutional networks have been estimated with statistical models (Bayesian multilevel logistic regression, BMLR) for a number of Scopus subject areas. Within single subject areas, we have investigated and visualized how successfully overall an institution (reference institution) has collaborated (compared to all the other institutions in a subject area), and with which other institutions (network institutions) a reference institution has collaborated particularly successfully. The "best paper rate" (statistically estimated) was used as an indicator for evaluating the collaboration success of an institution. This gives the proportion of highly cited papers from an institution, and is considered generally as an indicator for measuring impact in bibliometrics., accepted for publication in the Journal of Informetrics

The paper introduces the use of blockmodeling in the micro-level study of the internal structure of co-authorship networks over time. Variations in scientific productivity and researcher or research group visibility were determined by observing authors' role in the core-periphery structure and crossing this information with bibliometric data. Three techniques were applied to represent the structure of collaborative science: (1) the blockmodeling; (2) the Kamada-Kawai algorithm based on the similarities in co-authorships present in the documents analysed; (3) bibliometrics to determine output volume, impact and degree of collaboration from the bibliographic data drawn from publications. The goal was to determine the extent to which the use of these two complementary approaches, in conjunction with bibliometric data, provides greater insight into the structure and characteristics of a given field of scientific endeavour. The paper describes certain features of Pajek software and how it can be used to study research group composition, structure and dynamics. The approach combines bibliometric and social network analysis to explore scientific collaboration networks and monitor individual and group careers from new perspectives. Its application on a small-scale case study is intended as an example and can be used in other disciplines. It may be very useful for the appraisal of scientific developments. © 2012 Akademiai Kiado, Budapest, Hungary., This research was partially funded by the Spanish National Research Council under the project entitled “Generación de herramientas cienciométricas para el análisis de la colaboración científica” (Proyecto Intramural CSIC 200810I210).

Chinchilla-Rodríguez, Z., Vargas-Quesada, B., Hassan-Montero, Y., González-Molina, A., Moya-Anegón, F. New approach to the visualization of international scientific collaboration. Information Visualization, 9 (4): 277-287, Winter 2010. DOI: 10.1057/ivs.2009.31, In this study, visual representations are created in order to analyze different aspects of scientific collaboration at the international level. The main objective is to identify the international facet of research by following the flow of knowledge as expressed by the number of scientific publications, and then establishes the main geographical axes of output, showing the interrelationships of the domain, the intensity of these relations, and how the different types of collaboration are reflected in terms of visibility. Thus, the methodology has a twofold application, allowing us to detect significant differences that help characterize patterns of behaviour of a geographical system of output, along with the generation of representations that serve as interfaces for domain analysis and information retrieval.

[ES] En este trabajo presentamos la estructura de la investigación científica española durante el período comprendido entre 1990 y 2005. Basándonos en la cocitación de categorías ISI, que comprenden las ciencias naturales, las ciencias sociales y el arte y las humanidades, y combinando el análisis de redes sociales (ARS) con algoritmos de poda como pathfindernetorks (Pfnet) y otros algoritmos de representación de la información como el de Kamada–Kawai, mostramos la estructura básica de la ciencia española a través de sus relaciones esenciales. El resultado son unos mapas bibliométricos con forma de neurona y con un gran axón central (cienciogramas) que ponen de manifiesto la macro–estructura, micro– estructura y columna vertebral de la investigación española, que permiten su análisis e interpretación., [EN] This article presents the structure of Spanish science from 1990 to 2005. Based on ISI subject–category co–citation, including natural sciences, social sciences and arts & humanities, and combining both social network analysis (SNA) and pruning algorithms such as pathfinder–networks (Pfnet) and other information layout algorithms like Kamada– Kawai’s, the basic structure of Spanish science is shown through its essential relations. The results are bibliometric– maps (scientograms) revealing the macrostructure, microstructure and the backbone of Spanish science and making possible its analysis and explanation.

Moya-Anegón, F., Vargas-Quesada, B., Chinchilla-Rodríguez, Z., Herrero-Solana, V., Corera-Álvarez, E., Muñoz-Fernández, F. J. Domain analysis and information retrieval through the construction of heliocentric maps based on ISI-JCR category cocitation. Information Processing and Management, 41 (6): 1520-1533, 2005. DOI: 10.1016/j.ipm.2005.03.017, We propose the use of ISI-JCR categories as units of cocitation and measurement for the construction of heliocentric maps. The use of a spatial metaphor allows us to illustrate, analyze and compare domains in terms of the categories and their interconnections or links. We can also move around within the structure of these domains for further analysis, and access the documents associated with the categories and to the links that cocite or relate them., SEJ2004-08358-C02-01/SOCI

Bornmann, Stefaner, de Moya Anegón, and Mutz (2014) have introduced a web application (www.excellencemapping.net) which is linked to both academic ranking lists published hitherto (e.g. the Academic Ranking of World Universities) as well as spatial visualization approaches. The web application visualizes institutional performance within specific subject areas as ranking lists and on custom tile-based maps. The new, substantially enhanced version of the web application and the generalized linear mixed model for binomial data on which it is based are described in this paper. Scopus data are used which have been collected for the SCImago Institutions Ranking. Only those universities and research-focused institutions are considered that have published at least 500 articles, reviews and conference papers in the period 2006-2010 in a certain Scopus subject area. In the enhanced version, the effect of single covariates (such as the per capita GDP of a country in which an institution is located) on two performance metrics (best paper rate and best journal rate) is examined and visualized. A covariate-adjusted ranking and mapping of the institutions is produced in which the single covariates are held constant. The results on the performance of institutions can then be interpreted as if the institutions all had the same value (reference point) for the covariate in question. For example, those institutions can be identified worldwide showing a very good performance despite a bad financial situation in the corresponding country.

Purpose - The web application presented in this paper allows for an analysis to reveal centres of excellence in different fields worldwide using publication and citation data. Only specific aspects of institutional performance are taken into account and other aspects such as teaching performance or societal impact of research are not considered. The purpose of this paper is to address these issues. Design/methodology/approach - Based on data gathered from Scopus, field-specific excellence can be identified in institutions where highly-cited papers have been frequently published. Findings - The web application (www.excellencemapping.net) combines both a list of institutions ordered by different indicator values and a map with circles visualising indicator values for geocoded institutions. Originality/value - Compared to the mapping and ranking approaches introduced hitherto, our underlying statistics (multi-level models) are analytically oriented by allowing the estimation of values for the number of excellent papers for an institution which are statistically more appropriate than the observed values; the calculation of confidence intervals as measures of accuracy for the institutional citation impact; the comparison of a single institution with an >average> institution in a subject area: and the direct comparison of at least two institutions.

Miguel, S., Chinchilla-Rodríguez, Z., Moya-Anegón, F. Open Access and Scopus: A New Approach to Scientific Visibility from the Standpoint of Access. Journal of the American Society for Information Science and Technology, 62 (6): 1130-1145, 2011. DOI: 10.1002/asi.21532, The last few years have seen the emergence of several Open Access (OA) options in scholarly communication, which can broadly be grouped into two areas referred to as gold and green roads. Several recent studies showed how big the extent of OA is, but there have been few studies showing impact of OA in the visibility of journals covering all scientific fields and geographical regions. This research shows the extent of OA from the perspective of the journals indexed in Scopus, as well as influence on visibility, in view of the various geographic and thematic distributions. The results show that in all the disciplinary groups the presence of green road journals widely surpasses the percentage of gold road publications. The peripheral and emerging regions have greater proportions of gold road journals. These journals pertain for the most part to the last quartile. The benefits of open access on visibility of the journals are to be found on the green route, but paradoxically this advantage is not lent by the OA per se, but rather of the quality of the articles/journals themselves, regardless of their mode of access.

Vargas-Quesada, B., Moya-Anegón, F., Chinchilla-Rodríguez, Z., González-Molina, A. Showing the essential science structure of a scientific domain and its evolution. Information Visualization, 9 (4): 288-300, Winter 2010. DOI: 10.1057/ivs.2009.33, Category co-citation and its representation through social networks is proving to be a very adequate technique for the visualization and analysis of great scientific domains. Its combination with pathfinder networks using pruning values r=∞and q=n−1 makes manifest the essence of research in the domain represented, or what we might call the `most salient structure'. The possible loss of structural information, caused by aggressive pruning in peripheral areas of the networks, is overcome by creating heliocentric maps for each category. The depictions obtained with this procedure become tools of great usefulness in view of their capacity to reveal the evolution of a given scientific domain over time, to show differences and similarities between different domains, and to suggest possible new lines for development. This article presents the scientogram of the United States for the year 2002, identifying its essential structure. We also show the scientograms of China for the years 1990 and 2002, in order to study its particular national evolution. Finally, we try to detect patterns and tendencies in the three scientograms that would allow one to predict or flag the evolution of a scientific domain.

Perianes-Rodríguez, A., Chinchilla-Rodríguez, Z., Vargas-Quesada, B., Olmeda-Gómez, C., Moya-Anegón, F. Synthetic hybrid indicators based on scientific collaboration to quantify and evaluate individual research results. Journal of Informetrics, 3 (2): 91-101, April 2009. ISSN: 1751-1577 DOI: 10.1016/j.joi.2008.12.001, Governmental initiatives around scientific policy have progressively raised collaboration to priority status. In this context, a need has arisen to broaden the traditional approach to the analysis and study of research results by descending to the group or even the individual scale and supplementing the output-, productivity-, visibility- and impact-based focus with new measures that emphasize collaboration from the vantage of structural analysis. To this end, the present paper proposes new hybrid indicators for the analysis and evaluation of individual research results, popularity and prestige, that combine bibliometric and structural aspects. A case study was conducted of the nine most productive departments in Carlos III University of Madrid. The findings showed hybridization to be a tool sensitive to traditional indicators, but also to the new demands of modern science as a self-organized system of interaction among individuals, furnishing information on researchers’ environments and the behavior and attitudes adopted within those environments.

Our objective is the generation of schematic visualizations as interfaces for scientific domain analysis. We propose a new technique that uses thematic classification (classes and categories) as entities of cocitation and units of measure, and demonstrate the viability of this methodology through the representation and analysis of a domain of great dimensions. The main features of the maps obtained are discussed, and proposals are made for future improvements and applications, Plan Nacional de I+D+i 2004-2007 “Atlas de la Ciencia Española” (SEJ2004-08358-C02-01/SOCI) subvencionado por el Ministerio de Educación y Ciencia. 2004.