Data Citation and the Citation Graph

The citation graph is a computational artifact that is widely used to represent the domain of published literature. It represents connections between published works, such as citations and authorship. Among other things, the graph supports the computation of bibliometric measures such as h-indexes and impact factors. There is now an increasing demand that we should treat the publication of data in the same way that we treat conventional publications. In particular, we should cite data for the same reasons that we cite other publications. In this paper we discuss what is needed for the citation graph to represent data citation. We identify two challenges: (i) to model the evolution of credit appropriately (through references) over time and (ii) to model data citation not only to a dataset treated as a single object but also to parts of it. We describe an extension of the current citation graph model that addresses these challenges. It is built on two central concepts: citable units and reference subsumption. We discuss how this extension would enable data citation to be represented within the citation graph and how it allows for improvements in current practices for bibliometric computations both for scientific publications and for data.

Journal flipping to Open Access: The Perception of Spanish Journal Managers

There is a growing interest in determining the factors that influence a journal’s flipping to Open Access (OA). Using semi-structured interviews combined with bibliometric indicators, this paper uncovers the perception of Spanish managers related to OA and the decision to flip. The key research questions are twofold: How well do bibliometric measures reflect the changes in the status of the journal? How do journal managers perceive the flipping process? In order to answer these, twelve semi-structured interviews were conducted with journal managers of Spanish Journals. The findings suggest the great majority of managers are aware of the indicators, but only two considered they reflect their reality. The results indicate as the main motivations to flip to OA: being imposed by the host institution, economic reasons, and increase visibility and internationalization. An increase in the number of submissions, visibility, or internationalization since the transition is perceived as a benefit while the loss of interchanges with other institutions is seen as the major drawback. Although flipping to OA is perceived by the managers to have many advantages, it raises some challenges too, especially the need for funding, lack of resources capacity for technical support, and the creation of alliances.

The impact of Economics and Finance research published in Central and Eastern Europe

Research quality dictates the reputation of faculty, colleges, and universities, regardless of their location. In order to shed some light on the quality construct, this research reports on the scholarly impact of economics and finance journals published in countries of Central and Eastern Europe. A comparison of coverage by Web of Science (WoS), Scopus, and Cabell’s, three scholarly databases, reveals the lesser coverage of CEE journals within WoS and Scopus. Examination of E&F journals published in Poland, Romania, and the remainder of CEE, as defined by the Journal of Eastern European and Central Asian Research, discloses that the level of quality varies by nation. There are variations across the popular CiteScore, SJR, SNIP, and percentage of articles cited bibliometric measures. Furthermore, this research documents the existence of impact variation between journals focused on Eastern Europe published in Eastern Europe and published elsewhere in the world.

Bibliometric Analysis of Fuzzy Logic Research in International Scientific Databases

The purpose of this study is to explore the Web of Science Database (WOS) and review the significant contributions to the research of Fuzzy Logic or Fuzzy Sets theory from the beginning to the present. This study analyzes the most eminent authors, institutions, countries, and journals in Fuzzy Logic research by applying science mapping methods and bibliometric measures. Also, we paid attention to link strength and h-index to represent the visibility, influence, and link between the representative authors. Moreover, we added descriptive statistics to highlight strong linearity and a connection between fuzzy publications and Fuzzy Logic research. Also, we applied regression analyses and prevision functions to predict the evolution of the Fuzzy Logic topic. The results showed a significant increase in the number of papers published annually in a portfolio of internationally representative journals. This leads us to the idea that Fuzzy Logic research is now a transdisciplinary topic that continually develops. Therefore, it can be found in more and more related areas such as artificial intelligence, IoT, medicine, economics, or the environment. Most of the results are consistent with other bibliometric studies. Still, some results are different, results related to the current cited works that show a polarization in the Asia area and the top journals that is continuously changing depending on the number of papers and the quotations of scientific personalities that publish. We used the VOS Viewer software to map the main trends in the field. The results indicate that the use of concepts has long exceeded traditional boundaries.

Becoming Open Knowledge Institutions: Divergence, Dialogue and Diversity

The Curtin Open Knowledge Initiative (COKI) is an innovative research project that collects and analyses publicly available research output data to assist and encourage researchers, academics, administrators and executives to understand the actual and potential reach of openness in research, and to assess their progress on the path towards open knowledge institutions. By taking a broad global approach and using multiple data sources, the project diverges from existing approaches, methods and bibliometric measures in the scholarly research environment. It combines analysis of research output, citations, publication sources and publishers, funders, social media events, open and not open access to provide overviews of research output and performance at institutional, funder, consortial and country levels. The project collects and analyses personnel diversity data such as gender, focusing on widening the reach of data analysis to emphasise the importance and value of diversity in research and knowledge production. Interactive visual tools present research output and performance to encourage understanding and dialogue among researchers and management. The path towards becoming open knowledge institutions involves a process of cultural change, moving beyond dominant publishing and evaluation practices. This paper discusses how through divergence, diversity and dialogue the COKI project can contribute to this change, with examples of applications in understanding and embracing openness.

The multidisciplinary nature of COVID-19 research

Objective. We analyzed the scientific output after COVID-19 and contrasted it with studies published in the aftermath of seven epidemics/pandemics: Severe Acute Respiratory Syndrome (SARS), Influenza A virus H5N1 and Influenza A virus H1N1 human infections, Middle East Respiratory Syndrome (MERS), Ebola virus disease, Zika virus disease, and Dengue. Design/Methodology/Approach. We examined bibliometric measures for COVID-19 and the rest of the studied epidemics/pandemics. Data were extracted from Web of Science, using its journal classification scheme as a proxy to quantify the multidisciplinary coverage of scientific output. We proposed a novel Thematic Dispersion Index (TDI) for the analysis of pandemic early stages. Results/Discussion. The literature on the seven epidemics/pandemics before COVID-19 has shown explosive growth of the scientific production and continuous impact during the first three years following each emergence or re-emergence of the specific infectious disease. A subsequent decline was observed with the progressive control of each health emergency. We observed an unprecedented growth in COVID-19 scientific production. TDI measured for COVID-19 (29,4) in just six months, was higher than TDI of the rest (7,5 to 21) during the first three years after epidemic initiation. Conclusions. COVID-19 literature showed the broadest subject coverage, which is clearly a consequence of its social, economic, and political impact. The proposed indicator (TDI), allowed the study of multidisciplinarity, differentiating the thematic complexity of COVID-19 from the previous seven epidemics/pandemics. Originality/Value. The multidisciplinary nature and thematic complexity of COVID-19 research were successfully analyzed through a scientometric perspective.

The multidisciplinary nature of COVID-19 research

ABSTRACTObjectiveWe analyzed the scientific output after COVID-19 and contrasted it with studies published in the aftermath of seven epidemics/pandemics: Severe Acute Respiratory Syndrome (SARS), Influenza A virus H5N1 and Influenza A virus H1N1 human infections, Middle East Respiratory Syndrome (MERS), Ebola virus disease, Zika virus disease, and Dengue.Design/Methodology/ApproachWe examined bibliometric measures for COVID-19 and the rest of studied epidemics/pandemics. Data were extracted from Web of Science, using its journal classification scheme as a proxy to quantify the multidisciplinary coverage of scientific output. We proposed a novel Thematic Dispersion Index (TDI) for the analysis of pandemic early stages.Results/DiscussionThe literature on the seven epidemics/pandemics before COVID-19 has shown explosive growth of the scientific production and continuous impact during the first three years following each emergence or re-emergence of the specific infectious disease. A subsequent decline was observed with the progressive control of each health emergency. We observed an unprecedented growth in COVID-19 scientific production. TDI measured for COVID-19 (29,4) in just six months, was higher than TDI of the rest (7,5 to 21) during the first three years after epidemic initiation.ConclusionsCOVID-19 literature showed the broadest subject coverage, which is clearly a consecuence of its social, economic, and political impact. The proposed indicator (TDI), allowed the study of multidisciplinarity, differentiating the thematic complexity of COVID-19 from the previous seven epidemics/pandemics.Originality/ValueThe multidisciplinary nature and thematic complexity of COVID-19 research were successfully analyzed through a scientometric perspective.

Unequal internationalisation and the emergence of a new epistemic community: gender and migration

In this contribution to the formation of an epistemic community and its knowledge production developed in the Paper Between fragmentation and institutionalisation: the rise of migration studies as a research field, I seek to go beyond the bibliometric analysis, and in particular explore the nature of its internationalisation, the connections authors have across the globe and the unequal valuation of differently located research. These aspects underpin networks in the formation and evolution of epistemic communities. I shall illustrate my points through an epistemic community which has grown significantly in the past two decades, but scarcely gains a mention in the Paper. Gender and migration can be placed within the much broader cluster of globalisation, and especially in more recent years, transnationalism. My analysis does not start from bibliometric measures, which I do not have, but is based on selected reviews at different stages of the emergence of this field and my own involvement in it since the early 1990s.

Peer review versus the h-index for evaluation of individual researchers in the biological sciences

Past performance is a key consideration when rationalising the allocation of grants and other opportunities to individual researchers. The National Research Foundation of South Africa (NRF) has long used a highly structured system of ‘rating’ the past performance of individual researchers. This system relies heavily on peer review, and has seldom been benchmarked against bibliometric measures of research performance such as Hirsch’s h-index. Here I use data for about 600 rated researchers in the biological sciences to evaluate the extent to which outcomes of peer review correspond to bibliometric measures of research performance. The analysis revealed that values of the h-index based on the Scopus database are typically 5–20 for researchers placed in the NRF’s C rating category (‘established’), 20–40 for those in the B rating category (‘considerable international recognition’) and >40 for those in the A rating category (‘leading international scholars’). Despite concerns that citation patterns differ among disciplines, the mean h-index per rating category was remarkably consistent across five different disciplines in the biological sciences, namely animal sciences, plant sciences, ecology, microbiology and biochemistry/genetics. This observation suggests that the NRF rating system is equitable in the sense that the outcomes of peer review are generally consistent with bibliometric measures of research performance across different disciplines in the biological sciences. However, the study did reveal some notable discrepancies which could reflect either bias in the peer-review process or shortcomings in the bibliometric measures, or both.