Informetric Methods Research Articles

Towards a Systematic Description of Fault Tree Analysis Studies Using Informetric Mapping

Fault tree analysis (FTA) is one of the important analysis methods of safety system engineering commonly utilized in various industries to evaluate and improve the reliability and safety of complex systems. To grasp the current situation and development trend of FTA research and to further point out FTA’s future development directions, 1469 FTA-related articles from the literature were retrieved from the SCIE and SSCI databases. Informetric methods, including co-authorship analysis, co-citation analysis and co-occurrence analysis, were adopted for analyzing the cooperation relationship, research knowledge base, research hotspots and frontier in the FTA research field. The results show that China has the highest number of publications, and the Loughborough University of England has the highest number of publications of relevant institutions. Dynamic fault tree analysis, fuzzy fault tree analysis and FTA based on binary decision diagrams are recognized as the knowledge bases in FTA studies. “Reliability Engineering and System Safety”, “Safety Science” and “Fuzzy Sets and Systems” are the core journals in this field. Fuzzy fault tree analysis, dynamic fault tree analysis based on Bayesian networks and FTA combined with management factors may be both the main research hotspots and the frontiers. Then, by deriving the above results, this study can help scholars better master the current research status and frontiers of FTA to improve system reliability and safety.

Extracting and Measuring Uncertain Biomedical Knowledge from Scientific Statements

Abstract Purpose Given the information overload of scientific literature, there is an increasing need for computable biomedical knowledge buried in free text. This study aimed to develop a novel approach to extracting and measuring uncertain biomedical knowledge from scientific statements. Design/methodology/approach Taking cardiovascular research publications in China as a sample, we extracted subject–predicate–object triples (SPO triples) as knowledge units and unknown/hedging/conflicting uncertainties as the knowledge context. We introduced information entropy (IE) as potential metric to quantify the uncertainty of epistemic status of scientific knowledge represented at subject-object pairs (SO pairs) levels. Findings The results indicated an extraordinary growth of cardiovascular publications in China while only a modest growth of the novel SPO triples. After evaluating the uncertainty of biomedical knowledge with IE, we identified the Top 10 SO pairs with highest IE, which implied the epistemic status pluralism. Visual presentation of the SO pairs overlaid with uncertainty provided a comprehensive overview of clusters of biomedical knowledge and contending topics in cardiovascular research. Research limitations The current methods didn’t distinguish the specificity and probabilities of uncertainty cue words. The number of sentences surrounding a given triple may also influence the value of IE. Practical implications Our approach identified major uncertain knowledge areas such as diagnostic biomarkers, genetic polymorphism and co-existing risk factors related to cardiovascular diseases in China. These areas are suggested to be prioritized; new hypotheses need to be verified, while disputes, conflicts, and contradictions need to be settled. Originality/value We provided a novel approach by combining natural language processing and computational linguistics with informetric methods to extract and measure uncertain knowledge from scientific statements.

The evolution of LIS research topics and methods from 2006 to 2018: A content analysis

AbstractReplicating a series of studies of LIS research trends performed by Järvelin and colleagues, this content analysis systematically examines the evolution and distribution of LIS research topics and methods at six‐year increments from 2006 to 2018. Bibliographic data was collected for 3,422 articles published in LIS journals for the years of 2006, 2012, and 2018. Using a conceptual research strategy, the researchers identified the central research topics and research method for each article. The findings indicate a shift towards greater emphasis on Scholarly Communications/Informetrics and Information Seeking/Behavior topics, along with a reduction in Information Systems and Library and Information Service topics. Quantitative‐based approaches are predominant across the 3 years examined, with observed growth in the usage of questionnaires and informetric methods from 2006 to 2018. These findings indicate that LIS is a dynamic discipline, with quickly shifting interests/usage of research topics and methods.

Digital humanities research: interdisciplinary collaborations, themes and implications to library and information science

PurposeThe purpose of this paper is to examine the structure, patterns and themes of interdisciplinary collaborations in the digital humanities (DH) research through the application of social network analysis and visualization tools.Design/methodology/approachThe sample includes articles containing DH research in the Web of Science Core Collection as of December 2018. First, co-occurrence data representing collaborations among disciplinary were extracted from the subject category. Second, the descriptive statistics, network indicators and interdisciplinary communities were calculated. Third, the research topics of different interdisciplinary collaboration communities based on system keywords, author keywords, title and abstracts were detected.FindingsThe findings reveal that while the scope of disciplines involved in DH research is broad and evolving over time, most interdisciplinary collaborations are concentrated among several disciplines, including computer science, library and information science, linguistics and literature. The study further uncovers some communities based on closely collaborating disciplines and the evolving nature of such interdisciplinary collaboration communities over time. To better understand the close collaboration ties, the study traces and analyzes the research topics and themes of the interdisciplinary communities. Finally, the implications of the findings for DH research are discussed.Originality/valueThis study applied various informetric methods and tools to reveal the collaboration structure, patterns and themes among disciplinaries in DH research.

Do national funding organizations properly address the diseases with the highest burden?: Observations from China and the UK

Recent years have witnessed an incipient shift in science policy from a focus mainly on academic excellence to a focus that also takes into account “societal impact”. This shift raises the question as to whether medical research has given proper attention to the diseases imposing the greatest burden on society. Therefore, with the aim of identifying correlations between research funding priorities and public demand in health, we examine grants issued by the major medical research funding bodies of China and the UK during 2006–2017 and compare the focus of their funded projects with the diseases that carry the highest burden of death, risk, or loss of health. The results indicate that the funding decisions of both nations do correspond to the illnesses with the highest health impact on their citizens. For both regions, the greatest health concerns surround non-communicable diseases, and neoplasms and cardiovascular disease in particular. In China, national health priorities have remained focused on these illnesses for the benefit of its own population, whereas the UK has funded a wider variety of research, extending to projects with impacts outside its borders to some developing countries. Additionally, despite an increased incidence of mental illness and HIV/AIDs in China, there is evidence that less priority has been given to these conditions. Both of these health areas seem to require more attention from China’s national funding agencies and the society in general. Methodologically, this study can serve as an example of how to conduct analyses related to public health issues by combining informetric methods and data with the tools and data from other fields, thereby inspiring other scientometrics studies.

Cross-national digital humanities research collaborations: structure, patterns and themes

PurposeThe purpose of this paper is to examine the structure, patterns and themes of cross-national collaborations in Digital Humanities research through the application of social network analysis and visualization tools.Design/methodology/approachThe sample includes articles containing Digital Humanities research in the Web of Science Core Collection as of December 2018. First, co-occurrence data representing collaborations among nations were extracted from author affiliations. Second, the descriptive statistics, network indicators and international communities were calculated. Third, the research topics of different cross-national collaboration communities based on ISI keywords, author keywords, title and abstracts were detected.FindingsThe results show that the scope of international collaborations in Digital Humanities research is broad, but the distribution among nations is unbalanced. The USA, Germany and England were identified as the major contributors. Five research communities are identified, led by the USA, Germany, England, Belgium and France. The communities share common research topics such as history, GIS, text mining, visualization, while each has its own research emphasis.Originality/valueThis study applied various informetric methods and tools to reveal the collaboration structure, patterns and themes among nations in Digital Humanities research.

A Survey of Informetric Methods and Technologies

A survey of informetric methods and technologies is presented. Problems and directions of informetrics are defined. The interrelations between the concepts such as scientometrics, bibliometrics, informetrics, webometrics, and altmetrics are shown. The existing informetric models and methods and also topical problems of informetrics are analyzed. Available analytic-and-search scientometric databases and systems are considered and their drawbacks and advantages are revealed. Characteristics of scientometric systems, their components, and factors that affect scientometric indices are determined. Based on the conducted research, promising directions for developing scientometric systems are formulated.

Structure and patterns of cross-national Big Data research collaborations

PurposeThe purpose of this paper is to reveal the structure and patterns of cross-national collaborations in Big Data research through application of various social network analysis and geographical visualization methods.Design/methodology/approachThe sample includes articles containing Big Data research, covering all years, in the Web of Science Core Collection as of December 2015. First, co-occurrence data representing collaborations among nations were extracted from author affiliations. Second, the descriptive statistics, network indicators of collaborations, and research communities were calculated. Third, topological network maps, geographical maps integrated with topological network projections, and proportional maps were produced for visualization.FindingsThe results show that the scope of international collaborations in Big Data research is broad, but the distribution among nations is unbalanced and fragmented. The USA, China, and the UK were identified as the major contributors to this research area. Five research communities are identified, led by the USA, China, Italy, South Korea, and Brazil. Collaborations within each community vary, reflecting different levels of research development. The visualizations show that nations advance in Big Data research are centralized in North America, Europe, and Asia-Pacific.Originality/valueThis study applied various informetric methods and tools to reveal the collaboration structure and patterns among nations in Big Data research. Visualized maps help shed new light on global research efforts.

Cognitive Distances between Evaluators and Evaluees in Research Evaluation: A Comparison between Three Informetric Methods at the Journal and Subject Category Aggregation Level

This article compares six informetric approaches to determine cognitive distances between the publications of panel members and those of research groups in discipline-specific research evaluation. We used data collected in the framework of six completed research evaluations from the period 2009-2014 at the University of Antwerp as a test case. We distinguish between two levels of aggregation – Web of Science subject categories and journals – and three methods: while the barycenter method (2-dimensional) is based on global maps of science, the similarity-adapted publication vector (SAPV) method and weighted cosine similarity (WCS) method (both in higher dimensions) use a full similarity matrix. In total, this leads to six different approaches, all of which are based on the publication profile of research groups and panel members. We use Euclidean distances between barycenters and SAPVs, as well as values of WCS between panel members and research groups as indicators of cognitive distance. We systematically compare how these six approaches are related. The results show that the level of aggregation has minor influence on determining cognitive distances, but dimensionality (two versus a high number of dimensions) has a greater influence. The SAPV and WCS methods agree in most cases at both levels of aggregation on which panel member has the closest cognitive distance to the group to be evaluated, whereas the barycenter approaches often differ. Comparing the results of the methods to the main assessor that was assigned to each research group, we find that the barycenter method usually scores better. However, the barycenter method is less discriminatory and suggests more potential evaluators, whereas SAPV and WCS are more precise.

Emerging medical informatics research trends detection based on MeSH terms

The aim of this study is to analyze the research trends of medical informatics over the last 12 years. A new method based on MeSH terms was proposed to identify emerging topics and trends of medical informatics research. Informetric methods and visualization technologies were applied to investigate research trends of medical informatics. The metric of perspective factor (PF) embedding MeSH terms was appropriately employed to assess the perspective quality for journals. The emerging MeSH terms have changed dramatically over the last 12 years, identifying two stages of medical informatics: the “medical imaging stage” and the “medical informatics stage”. The focus of medical informatics has shifted from acquisition and storage of healthcare data by integrating computational, informational, cognitive and organizational sciences to semantic analysis for problem solving and clinical decision-making. About 30 core journals were determined by Bradford’s Law in the last 3 years in this area. These journals, with high PF values, have relative high perspective quality and lead the trend of medical informatics.

Constructing an information science resource ontology based on the Chinese Social Science Citation Index

Purpose – The purpose of this study is to construct a Chinese information science resource ontology and to explore a new method for semiautomatic ontology construction. Design/methodology/approach – More than 8,290 articles indexed in the Chinese Social Science Citation Index (CSSCI), covering the years 2001 to 2010, were included in this study. Statistical analysis, co-occurrence analysis, and semantic similarity methods were applied to the selected articles. The ontology was built using existing construction principles and methods, as well as categories and hierarchy definitions based on CSSCI indexing fields. Findings – Seven categories were found to be relevant for the Chinese information science resource ontology, which, in this study, consists of a three-tier architecture, 78,291 instances, and 182,109 pairs of semantic relations. These results indicate the following: further improvements are required in ontology construction methods; resource ontology is a breakthrough concept in ontology studies; the combination of semantic similarities and co-occurrence analysis can quantitatively describe relationships between concepts. Originality/value – This study pioneers the resource ontology concept. It is one of the first to combine informetric methods with semantic similarity to reveal deep relationships in textual data.

Quantitative Characterization of the Research Productivity of Interdisciplinary

Interdisciplinary research has been developed so quickly in recent decades and lots of research productivities have been achieved already. To trance the evolution pathway, reveal the research hotspots and obtain the fronts of interdisciplinary research as well as its development characteristics, informetric methods were employed in this study. From the Web of Science database, papers using in the topic word, like interdisciplinary related words from 1950 to 2012 were listed as the research objects. Some characteristics such as publication language, publication trend, publication contributors and knowledge basement for interdisciplinary were also analysed. Then the raw data was visualized in a number of co-citation maps through the knowledge visualization tool Citespace III to identify critical node documents during the evolutionary history of interdisciplinary research. The research hotspot and research front were carefully analysed using Citespace III's keyword clustering and burst terms detecting function. About ten key articles reflected the evolution pathway of interdisciplinary research, more than two main clusters and top twenty burst terms identified the research hotspots and research fronts. It was also found that research perspective and approach are two mainstreams words of interdisciplinary research. Interdisciplinary related keywords are current research hotpots and represent future directions of interdisciplinary development/research. In addition, interdisciplinary are research areas with some promising prospects.

Multidimensional Journal Evaluation of PLOS ONE

PLOS ONE (formerly PLoS ONE) is an international open access online journal published by the Public Library of Science. The periodical covers all science and medicine categories and has published as many as 28,852 documents from 2007 to 2011. PLOS ONE will be used to show the range of journal metrics and informetric methods regarding validity, practicability and informative value. To assess this data as specifically as possible and to address all relevant factors, the evaluation is split into five dimensions, each of which involves distinct metrics. The five dimensions are journal output, journal content, journal perception, journal citations and journal management. Each of them is pointed out in the process of the analyses, and all significant evaluation results are presented. The results show that PLOS ONE has experienced an enormous development. Because of a relatively low rejection rate of 31%, its openness towards a multitude of different research areas, an internationally large peer review community, and its open access, a plurality of documents can be published in comparison with a print-journal or other online periodicals. The results of the evaluation indicate that PLOS ONE should be assessed from numerous perspectives because there are a variety of indicators beyond the impact factor that can be made use of in order to evaluate exhaustively the standing of the journal as well as its prestige and impact.

Applied Informetrics for Digital Libraries: An Overview of Foundations, Problems and Current Approaches

Zur Anwendung von Informetrie fur Digitale Bibliotheken. Ein Uber- blick uber Grundlagen, Probleme und aktuelle Zugange«. The foundation of every research project is a comprehensive literature review. The search for sci- entific literature in information systems is a discipline at the intersection of in- formation retrieval and digital libraries; recent user studies in both fields show two typical weaknesses of the classical IR approach: ranking of retrieved and maybe relevant documents and the language problem during the query formu- lation phase. At the same time the performance of traditional retrieval systems that rely primarily on textual document and query features have been stagnat- ing for years, as could be observed in IR evaluation campaigns such as TREC or CLEF. Therefore alternative approaches to surpass these two problem fields are needed. Recent developments in the area of applied informetrics show very promising effects by using long-known informetric and bibliometric methods like the analysis of power-law distributions described by Lotka's, Zipf's or Brad- ford's laws, or the application of co-occurrences analysis for entities like au- thors, journals or references of scientific literature. This work will concentrate on the description of the open problems and the current approaches to surpass these by using applied informetrics methodologies.

복수 자질에 의한 지적 구조의 계량정보학적 분석연구: 국내 대학도서관 분야 연구논문을 대상으로

The purpose of this study is to identify topic areas of academic library research u: ing two informetric methods: word clustering and Pathfinder network. For the data analysis, 139 article published in major library and information science journals from 2005 to 2009 were collected from the Korean Science Citation Index database. The keywords that represent research topics were gathered from two sections: an abstract and titles in references. Results showed that reference titles usefully represent topics in detail. and combining abstracts and reference tiles can produce an expanded topic map.

Assessing the authoritativeness of Canadian and American health documents: a comparative analysis using informetric methodologies

Government publications have long been considered authoritative sources of information regardless of the format (electronic via the WWW or paper) they are published in, and with little consideration as to how they are researched and written. Given the greater accessibility that the WWW provides the public to this very important source of information on a wide variety of subjects, assessing authoritativeness becomes a bigger and more difficult issue. The research and comparative analysis presented here continues a pilot study that applies informetric methods, especially citation analysis, to assess whether the blind trust afforded government publications is appropriate in such an important area of public policy and to see whether the two different types of health systems in Canada and the United States might have an effect on how these publications are produced.

Commonalities and differences between scholarly and technical collaboration

Co-authorship analysis is a well-established tool in bibliometric analysis. It can be used at various levels to trace collaborative links between individuals, organisations, or countries. Increasingly, informetric methods are applied to patent data. It has been shown for another method that bibliometric tools cannot be applied without difficulty. This is due to the different process in which a patent is filed, examined, and granted and a scientific paper is submitted, refereed and published. However, in spite of the differences, there are also parallels between scholarly papers and patents. For instance, both papers and patents are the result of an intellectual effort, both disclose relevant information, and both are subject to a process of examination. Given the similarities, we shall raise the question as to which extent one can transfer co-authorship analysis to patent data.

Applying informetric methods to empirically assess the authoritativeness of Health Canada electronic documents

Abstract Government publications have long been considered authoritative sources of information regardless of the format [electronic via the World Wide Web (WWW) or paper] they are published in and with little consideration as to how they are researched, written, and published. Given the greater accessibility that the WWW provides the public to this very important source of information on a wide variety of subjects, assessing authoritativeness becomes a bigger and more difficult issue. This preliminary study applies informetric methods, specifically citation analysis, to assess whether the blind trust afforded government publications is appropriate in an important area of public policy that, particularly in Canada, is seen almost as a natural right of citizenship, public health care. The results of this study show that this trust is not misplaced as these publications are well researched and, with or without references, are used without discrimination.

Tracing knowledge flows in innovation systems

This paper gives an overview of quantitative approaches used to study the science/technology linkage. Our discussion is informed by a number of theoretical approaches that have emerged over the past few years in the area of innovation studies emphasizing the exchange of actors in innovation system and a shift in the division of labour between publicly funded basic research and industrial development of technology. We review the more quantitative literature on efforts made to study such linkage phenomena, to which theorizing in the science policy area has attributed great importance. We then introduce a typology of three approaches to study the science/technology linkage - patent citation, industrial science, and university patenting. For each approach, we shall discuss merits and possible disadvantages. In another step we illustrate them using results from studies of the Finnish innovation system. Finally, we list key limitations of the informetric methods and point to possible hybrid approaches that could remedy some of them.

Informetrics and webometrics for measuring impact, visibility, and connectivity in science, politics, and business

The paper reports the application of classical bibliometric methods to evaluate the impact of scientific, political, and business developments. The novel aspect is to regard the Web as a citation network where the traditional information entities (scientific articles and the citations given to and taken from them) are replaced by webpages with external and internal links. The methodological studies are intended to test the usability of large international citation databases and the World Wide Web as feasible and reliable tools in quantitative analyses for gathering useful information for business intelligence. Formerly, the impact of authors and their scientific production was measured by the average citation frequencies of journals publishing their research: the Journal Impact Factor (JIF), calculated by the Institute for Scientific Information (ISI) in the United States and published annually in the Journal Citation Reports (JCR)—the most frequently used quantitative indicator to measure the quality/value/impact of research works published in the core international journals. It has been suggested that, by calculating the number of webpages pointing to a given site, analogously, a Web Impact Factor can be calculated as a way of comparing the attractiveness of sites or domains on the World Wide Web. A key to webometric studies has been the use of large-scale Web search engines such as Alta Vista that allow measurements to be made of the total number of pages in a Web space and links to those Web spaces. These search engines provide similar possibilities for the investigation of links between documents to those provided by the citation databases created by ISI. To illustrate the scope and nature of informetric research methods applied in competitive intelligence analysis, a short presentation is given of samples of research studies carried out at the Centre for Informetic Studies in Copenhagen (CIS). © 2001 John Wiley & Sons, Inc.