Computer Science

This study considers the expressiveness (that is the expressive power or expressivity) of different types of Knowledge Organization Systems (KOS) and discusses its potential to be machine-processable in the context of the Semantic Web. For this purpose, the theoretical foundations of KOS are reviewed based on conceptualizations introduced by the Functional Requirements for Subject Authority Data (FRSAD) and the Simple Knowledge Organization System (SKOS); natural language processing techniques are also implemented. Applying a comparative analysis, the dataset comprises a thesaurus (Eurovoc), a subject headings system (LCSH) and a classification scheme (DDC). These are compared with an ontology (CIDOC-CRM) by focusing on how they define and handle concepts and relations. It was observed that LCSH and DDC focus on the formalism of character strings (nomens) rather than on the modelling of semantics; their definition of what constitutes a concept is quite fuzzy, and they comprise a large number of complex concepts. By contrast, thesauri have a coherent definition of what constitutes a concept, and apply a systematic approach to the modelling of relations. Ontologies explicitly define diverse types of relations, and are by their nature machine-processable. The paper concludes that the potential of both the expressiveness and machine processability of each KOS is extensively regulated by its structural rules. It is harder to represent subject headings and classification schemes as semantic networks with nodes and arcs, while thesauri are more suitable for such a representation. In addition, a paradigm shift is revealed which focuses on the modelling of relations between concepts, rather than the concepts themselves.

Efforts to combat continuing gender inequalities in academia need to be informed by evidence about where differences occur. Citations are relevant as potential evidence in appointment and promotion decisions, but it is unclear whether there have been historical gender differences in average citation impact that might explain the current shortfall of senior female academics. This study investigates the evolution of gender differences in citation impact 1996-2018 for six million articles from seven large English-speaking nations: Australia, Canada, Ireland, Jamaica, New Zealand, UK, and the USA. The results show that a small female citation advantage has been the norm over time for all these countries except the USA, where there has been no practical difference. The female citation advantage is largest, and statistically significant in most years, for Australia and the UK. This suggests that any academic bias against citing female authored research cannot explain current employment inequalities. Nevertheless, comparisons using recent citation data, or avoiding it altogether, during appointments or promotion may disadvantage females in some countries by underestimating the likely impact of their work, especially in the long term.

Different kinds of "gender gap" have been reported in different walks of the scientific life, almost always favouring male scientists over females. In this work, for the first time, we present a large-scale empirical analysis to ask whether female scientists with the same level of scientific accomplishment are as likely as males to be recognised. We particularly focus on Wikipedia, the open online encyclopedia that its open nature allows us to have a proxy of community recognition. We calculate the probability of appearing on Wikipedia as a scientist for both male and female scholars in three different fields. We find that women in Physics, Economics and Philosophy are considerable less likely than men to be recognised on Wikipedia across all levels of achievement.

Understanding the nature and organization of scientific communities is of broad interest. The `Invisible College' is a historical metaphor for one such type of community and the search for such `colleges' can be framed as the detection and analysis of small groups of scientists working on problems of common interests. Case studies have previously been conducted on individual communities with respect to their scientific and social behavior. In this study, we introduce, a new and scalable community finding approach. Supplemented by expert assessment, we use the convergence of two different clustering methods to select article clusters generated from over two million articles from the field of immunology spanning an eleven year period with relevant cluster quality indicators for evaluation. Finally, we identify author communities defined by these clusters. A sample of the article clusters produced by this pipeline was reviewed by experts, and shows strong thematic relatedness, suggesting that the inferred author communities may represent valid communities of practice. These findings suggest that such convergent approaches may be useful in the future.

The present paper wishes to extend the theoretical reflections that we're currently working on: the "satellite intellectuals". This concept points a new "repertoire" of intellectuals that critics have not studied thoroughly and that is emerging with the amplification of the archives' digitalization of archives and their digital edition. Today, it is necessary to rethink and reevaluate the criteria we used to apply to define, integrate or exclude works and authors from, or in, a "canon". At the same time, it suggests new methods to process and deal with some concepts of computer tools and science.

Co-citation measurements can reveal the extent to which a concept representing a novel combination of existing ideas evolves towards a specialty. The strength of co-citation is represented by its frequency, which accumulates over time. Of interest is whether underlying features associated with the strength of co-citation can be identified. We use the proximal citation network for a given pair of articles (x, y) to compute theta, an a priori estimate of the probability of co-citation between x and y, prior to their first co-citation.Thus, low values for theta reflect pairs of articles for which co-citation is presumed less likely. We observe that co-citation frequencies are a composite of power-law and lognormal distributions, and that very high co-citation frequencies are more likely to be composed of pairs with low values of theta, reflecting the impact of a novel combination of ideas. Furthermore, we note that the occurrence of a direct citation between two members of a co-cited pair increases with co-citation frequency. Finally, we identify cases of frequently co-cited publications that accumulate co-citations after an extended period of dormancy.

In recent years, increased stakeholder pressure to transition research to Open Access has led to many journals "flipping" from a toll access to an open access publishing model. Changing the publishing model can influence the decision of authors to submit their papers to a journal, and increased article accessibility may influence citation behaviour. The aim of this paper is to show changes in the number of published articles and citations after the flipping of a journal. We analysed a set of 171 journals in the Web of Science (WoS) which flipped to open access. In addition to comparing the number of articles, average relative citation (ARC) and normalized impact factor (IF) are applied, respectively, as bibliometric indicators at the article and journal level, to trace the transformation of flipped journals covered. Our results show that flipping mostly has had positive effects on journal's IF. But it has had no obvious citation advantage for the articles. We also see a decline in the number of published articles after flipping. We can conclude that flipping to open access can improve the performance of journals, despite decreasing the tendency of authors to submit their articles and no better citation advantages for articles.

CRISPR/Cas has the potential to revolutionize medicine, agriculture, and biology. Understanding the trajectory of innovation, how it is influenced and who pays for it, is an essential research policy question, especially as US government support for research experiences a relative decline. We use a new method -- based on funding sources identified in publications' funding acknowledgements -- to map the networks involved in supporting key stages of highly influential research, namely basic biological research and technology development. We present a model of co-funding networks at the two most prominent institutions for CRISPR/Cas research, the University of California and the Harvard/MIT/Broad Institute, to illuminate how philanthropic and charitable organizations have articulated with US government agencies to co-finance the discovery and development of CRISPR/Cas. We mapped foundational US government support to both stages of CRISPR/Cas research at both institutions, while philanthropic organizations have concentrated in co-funding CRISPR/Cas technology development as opposed to basic biological research. This is particularly true for the Broad/Harvard/MIT system, where philanthropic investment clustered around particular technological development themes. These network models raise fundamental questions about the role of the state and the influence of philanthropy over the trajectory of transformative technologies.

Despite the limitations of funding acknowledgment (FA) data in Web of Science (WoS), studies using FA information have increased rapidly over the last several years. Considering this WoS'recent practice of updating funding data, this paper further investigates the characteristics and distribution of FA data in four WoS journal citation indexes. The research reveals that FA information coverage variances persist cross all four citation indexes by time coverage, language and document type. Our evidence suggests an improvement in FA information collection in humanity and social science research. Departing from previous studies, we argue that FA text (FT) alone no longer seems an appropriate field to retrieve and analyze funding information, since a substantial number of documents only report funding agency or grant number information in respective fields. Articles written in Chinese have a higher FA presence rate than other non-English WoS publications. This updated study concludes with a discussion of new findings and practical guidance for the future retrieval and analysis of funded research.

In this research, we examine the hypothesis that gender disparities in international research collaboration differ by collaboration intensity, academic position, age, and academic discipline. The following are the major findings: (1) while female scientists exhibit a higher rate of general, national, and institutional collaboration, male scientists exhibit a higher rate of international collaboration, a finding critically important in explaining gender disparities in impact, productivity, and access to large grants. (2) An aggregated picture of gender disparities hides a more nuanced cross-disciplinary picture of them. (3) An analysis of international research collaboration at three separate intensity levels (low, medium, and high) reveals that male scientists dominate in international collaboration at each level. However, at each level, there are specific disciplines in which females collaborate more than males. Further (4), gender disparities are clearly linked with age. Until about the age of 40, they are marginal and then they begin to grow. Finally, we estimate the odds of being involved in international research collaboration using an analytical linear logistic model. The examined sample includes 25,463 internationally productive Polish university professors from 85 universities, grouped into 27 disciplines, who authored 159,943 Scopus-indexed articles.