The rate of growth in scientific publication and the decline in coverage provided by Science Citation Index

The growth rate of scientific publication has been studied from 1907 to 2007 using available data from a number of literature databases, including Science Citation Index (SCI) and Social Sciences Citation Index (SSCI). Traditional scientific publishing, that is publication in peer-reviewed journals, is still increasing although there are big differences between fields. There are no indications that the growth rate has decreased in the last 50 years. At the same time publication using new channels, for example conference proceedings, open archives and home pages, is growing fast. The growth rate for SCI up to 2007 is smaller than for comparable databases. This means that SCI was covering a decreasing part of the traditional scientific literature. There are also clear indications that the coverage by SCI is especially low in some of the scientific areas with the highest growth rate, including computer science and engineering sciences. The role of conference proceedings, open access archives and publications published on the net is increasing, especially in scientific fields with high growth rates, but this has only partially been reflected in the databases. The new publication channels challenge the use of the big databases in measurements of scientific productivity or output and of the growth rate of science. Because of the declining coverage and this challenge it is problematic that SCI has been used and is used as the dominant source for science indicators based on publication and citation numbers. The limited data available for social sciences show that the growth rate in SSCI was remarkably low and indicate that the coverage by SSCI was declining over time. National Science Indicators from Thomson Reuters is based solely on SCI, SSCI and Arts and Humanities Citation Index (AHCI). Therefore the declining coverage of the citation databases problematizes the use of this source

Transitive reduction of citation networks

In many complex networks, the vertices are ordered in time, and edges represent causal connections. We propose methods of analysing such directed acyclic graphs taking into account the constraints of causality and highlighting the causal structure. We illustrate our approach using citation networks formed from academic papers, patents and US Supreme Court verdicts. We show how transitive reduction (TR) reveals fundamental differences in the citation practices of different areas, how it highlights particularly interesting work, and how it can correct for the effect that the age of a document has on its citation count. Finally, we transitively reduce null models of citation networks with similar degree distributions and show the difference in degree distributions after TR to illustrate the lack of causal structure in such models

Research assessment in the humanities: problems and challenges

Research assessment is going to play a new role in the governance of universities and research institutions. Evaluation of results is evolving from a simple tool for resource allocation towards policy design. In this respect "measuring" implies a different approach to quantitative aspects as well as to an estimation of qualitative criteria that are difficult to define. Bibliometrics became so popular, in spite of its limits, just offering a simple solution to complex problems. The theory behind it is not so robust but available results confirm this method as a reasonable trade off between costs and benefits. Indeed there are some fields of science where quantitative indicators are very difficult to apply due to the lack of databases and data, in few words the credibility of existing information. Humanities and social sciences (HSS) need a coherent methodology to assess research outputs but current projects are not very convincing. The possibility of creating a shared ranking of journals by the value of their contents at either institutional, national or European level is not enough as it is raising the same bias as in the hard sciences and it does not solve the problem of the various types of outputs and the different, much longer time of creation and dissemination. The web (and web 2.0) represents a revolution in the communication of research results mainly in the HSS, and also their evaluation has to take into account this change. Furthermore, the increase of open access initiatives (green and gold road) offers a large quantity of transparent, verifiable data structured according to international standards that allow comparability beyond national limits and above all is independent from commercial agents. The pilot scheme carried out at the university of Milan for the Faculty of Humanities demonstrated that it is possible to build quantitative, on average more robust indicators, that could provide a proxy of research production and productiivity even in the HSS

Professor Jorge Ambrósio: A tribute on the occasion of his 65th birthday

It is a great pleasure and an immense honor to write this humble and personal tribute to Professor Jorge Ambrósio on the occasion of his 65th birthday. This report is very modest, since the authors cannot summarize all the work and impact of one of the most influential researchers in the field of multibody dynamics. Further, this narrative is quite personal in the measure that it reflects the authors’ knowledge acquired over the last decades of close interaction and cooperation with Jorge Ambrósio. Thus, this work presents his achievements at different levels, namely in what concerns the scientific research, the industrial influence, and the educational impact. Professor Jorge Ambrósio has been an extremely active and highly productive researcher in multibody dynamics, with more than 230 publications, which generated more than 6000 citations, and 45 of his publications receiving more than 45 citations, leading to an extraordinary h-index of 45 according to the Scopus database. This figure is absolutely extraordinary, since multibody dynamics is a relatively new discipline, where much lower author and paper citation rates are the norm compared to other scientific areas. In fact, Professor Jorge Ambrósio’s publications represent a remarkable and highly influential body of knowledge in the multibody dynamics community. In short, Professor Jorge Ambrósio is without any doubt one of the most prominent researcher and academic of his generation

Statistical evaluation of research performance of young university scholars: A case study

The research performance of a small group of 49 young scholars, such as doctoral students, postdoctoral and junior researchers, working in different technical and scientific fields, was evaluated based on 11 types of research outputs. The scholars worked at a technical university in the fields of Civil Engineering, Ecology, Economics, Informatics, Materials Engineering, Mechanical Engineering, and Safety Engineering. Principal Component Analysis was used to statistically analyze the research outputs and its results were compared with factor and cluster analysis. The metrics of research productivity describing the types of research outputs included the number of papers, books and chapters published in books, the number of patents, utility models and function samples, and the number of research projects conducted. The metrics of citation impact included the number of citations and h-index. From these metrics -the variables -the principal component analysis extracted 4 main principal components. The 1st principal component characterized the cited publications in high-impact journals indexed by the Web of Science. The 2nd principal component represented the outputs of applied research and the 3rd and 4th principal components represented other kinds of publications. The results of the principal component analysis were compared with the hierarchical clustering using Ward's method. The scatter plots of the principal component analysis and the Mahalanobis distances were calculated from the 4 main principal component scores, which allowed us to statistically evaluate the research performance of individual scholars. Using variance analysis, no influence of the field of research on the overall research performance was found. Unlike the statistical analysis of individual research metrics, the approach based on the principal component analysis can provide a complex view of the research systems.Web of Science30217716

Inconsistency in Selecting Metrics used for Bibliometric Studies

There are several metrics available for application in bibliometrics. Some of the metrics that have been considered here such as measuring growth of publications, citation impact, authorship pattern, h-index have been widely used to generate statistical analysis with respect to books, articles, publications. Now one must be aware of the pros and cons of each and every metrics used in the research. One has to be certain that there is no information that is getting lost when data about researchers and their institutions are squeezed into a tabular form of metrics. There are certain metrics that have been discussed to be replaced with other metrics to obtain more accurate interpretation of the research performance. If used otherwise it can create a hindrance to the real research performance when misused

Summary of second annual MCBK public meeting: Mobilizing Computable Biomedical Knowledge—A movement to accelerate translation of knowledge into action

The volume of biomedical knowledge is growing exponentially and much of this knowledge is represented in computer executable formats, such as models, algorithms and programmatic code. There is a growing need to apply this knowledge to improve health in Learning Health Systems, health delivery organizations, and other settings. However, most organizations do not yet have the infrastructure required to consume and apply computable knowledge, and national policies and standards adoption are not sufficient to ensure that it is discoverable and used safely and fairly, nor is there widespread experience in the process of knowledge implementation as clinical decision support. The Mobilizing Computable Biomedical Knowledge (MCBK) community formed in 2016 to address these needs. This report summarizes the main outputs of the Second Annual MCBK public meeting, which was held at the National Institutes of Health on July 18‐19, 2019 and brought together over 150 participants from various domains to frame and address important dimensions for mobilizing CBK.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/154970/1/lrh2-sup-0001-supinfo.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154970/2/lrh210222.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154970/3/lrh210222_am.pd

First Author Advantage: Citation Labeling in Research

Citations among research papers, and the networks they form, are the primary object of study in scientometrics. The act of making a citation reflects the citer's knowledge of the related literature, and of the work being cited. We aim to gain insight into this process by studying citation keys: user-chosen labels to identify a cited work. Our main observation is that the first listed author is disproportionately represented in such labels, implying a strong mental bias towards the first author.Comment: Computational Scientometrics: Theory and Applications at The 22nd CIKM 201

Embedding-based Scientific Literature Discovery in a Text Editor Application

Each claim in a research paper requires all relevant prior knowledge to be discovered, assimilated, and appropriately cited. However, despite the availability of powerful search engines and sophisticated text editing software, discovering relevant papers and integrating the knowledge into a manuscript remain complex tasks associated with high cognitive load. To define comprehensive search queries requires strong motivation from authors, irrespective of their familiarity with the research field. Moreover, switching between independent applications for literature discovery, bibliography management, reading papers, and writing text burdens authors further and interrupts their creative process. Here, we present a web application that combines text editing and literature discovery in an interactive user interface. The application is equipped with a search engine that couples Boolean keyword filtering with nearest neighbor search over text embeddings, providing a discovery experience tuned to an author's manuscript and his interests. Our application aims to take a step towards more enjoyable and effortless academic writing. The demo of the application (https://SciEditorDemo2020.herokuapp.com/) and a short video tutorial (https://youtu.be/pkdVU60IcRc) are available online

A Step Forward in Cancer Informatics—It Is Mandatory to Make Guidelines Machine Readable

Clinical guidelines are general recommendations for practicing clinicians regarding prevention, diagnosis and treatment of a given disease. One of the most comprehensive and used guidelines are developed and regularly updated by the National Comprehensive Cancer Network (NCCN). Guidelines are readily available for download in portable document format (PDF). A machine-readable representation of NCCN guidelines is currently not available. In this writing, we argue on the necessity that clinical guidelines should be published in a machine-readable format. After review of the available literature, we describe the most important achievements in the field. Publication of guidelines in a machine-readable form may also be beneficial for other scientific and technical disciplines