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Computation
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Bibliometrics
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Special Issue "Bibliometrics"

A special issue of Computation (ISSN 2079-3197). This special issue belongs to the section "Computational Engineering".

Deadline for manuscript submissions: closed (20 December 2021) | Viewed by 26928

Special Issue Editor

Dr. Robin Haunschild

E-Mail Website
Guest Editor
Max Planck Institute for Solid State Research, Heisenbergstr. 1, 70569 Stuttgart, Germany
Interests: scientometrics; bibliometrics; altmetrics; social network analysis

Special Issue Information

Dear Colleagues,

Bibliometric methods are potentially relevant for all other disciplines. Therefore, the field of bibliometrics has a strong interdisciplinary nature. Research within bibliometrics encompasses studies of citation and reference patterns. Normalization procedures are proposed to compare citation scores across fields, and new classification schemes are introduced. With the advent of increasing computer power and availability of large, machine-usable bibliographic databases, bibliometrics has developed in the direction of big data science. Besides research within the field of bibliometrics, bibliometric methods are applied to other disciplines in various ways. The state of the art, significant achievements, and historical roots of scientific fields are analyzed.

In a very closely related subdiscipline, altmetrics (short for alternative metrics), impact assessment of recent publications (one or two years old) is attempted. Such young publications represent a problem for traditional bibliometric methods because citations take a few years, even many years in some disciplines, to accumulate. Altmetrics consist of manifold sources (Mendeley reader information, Twitter data, etc.) that open the possibility to tell the story behind the research rather than performing only impact measurements.

The present Special Issue aims to present the possibilities offered by bibliometrics and altmetrics. Contributions with a connection to computational engineering are especially welcome. In addition to original research papers, review papers and short communications are invited.

Dr. Robin Haunschild
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Computation is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • bibliometrics
  • scientometrics
  • altmetrics
  • RPYS
  • citation impact
  • research trends
  • historical roots
  • publication classification
  • network analysis

Published Papers (5 papers)

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Research

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Article
Applying Bibliometric Techniques: Studying Interdisciplinarity in Higher Education Curriculum
by
Patricia Snell Herzog
,
Jin Ai
and
Julia Ashton
Computation 2022, 10(2), 26; https://doi.org/10.3390/computation10020026 - 10 Feb 2022
Viewed by 2151
Abstract
Bibliometric methods are relevant for a range of applications and disciplines. The majority of existing scholarship investigating citation and reference patterns focuses on studying research impact. This article presents a new approach to studying the curriculum using bibliometric methods. Through a review of [...] Read more.
Bibliometric methods are relevant for a range of applications and disciplines. The majority of existing scholarship investigating citation and reference patterns focuses on studying research impact. This article presents a new approach to studying the curriculum using bibliometric methods. Through a review of existing definitions and measures of interdisciplinary research and standardization procedures for comparing disciplinary citations, three measures were considered: variety, balance and dissimilarity. Bibliometric algorithms for assessing these measures were adopted and modified for a curriculum context, and three interdisciplinary programs were investigated that span undergraduate and graduate degrees. Data objects were course syllabi, and required references were coded for disciplinary affiliations. The results indicated that—despite purportedly pursuing a singular goal in the same academic unit—the programs employed distinct citation patterns. Variety was highest in the master’s program, and balance was highest in the doctoral program. Dissimilarity was highest in the doctoral program, yet a novel technique for disambiguating disciplinary composition was implemented to improve interpretation. The analysis yielded unexpected findings, which underscore the value of a systematic approach in advancing beyond discourse by harnessing bibliometric techniques to reveal underlying curricula structure. This study contributed a well-grounded bibliometric method that can be replicated in future studies. Full article
(This article belongs to the Special Issue Bibliometrics)
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Article
Characteristics and Research Techniques Associated with the Journal Impact Factor and Other Key Metrics in Pharmacology Journals
by
Mingkwan Na Takuathung
,
Wannachai Sakuludomkan
,
Supanimit Teekachunhatean
and
Nut Koonrungsesomboon
Computation 2021, 9(11), 116; https://doi.org/10.3390/computation9110116 - 05 Nov 2021
Viewed by 1791
Abstract
In the present age, there is intense pressure on researchers to publish their research in ‘high-impact factor’ journals. It would be interesting to understand the trend of research publications in the field of pharmacology by exploring the characteristics of research articles, including research [...] Read more.
In the present age, there is intense pressure on researchers to publish their research in ‘high-impact factor’ journals. It would be interesting to understand the trend of research publications in the field of pharmacology by exploring the characteristics of research articles, including research techniques, in relation to the journal’s key bibliometrics, particularly journal impact factor (JIF), the seemingly most mentioned metric. This study aimed to determine the characteristics and research techniques in relation to research articles in pharmacology journals with higher or lower JIF values. A cross-sectional study was conducted on primary research journals under the ‘Pharmacology and Pharmacy’ category. Analysis of 768 original research articles across 32 journals (with an average JIF of 2.565 ± 0.887) demonstrated that research studies involving molecular techniques, in vivo experiments on animals, and bioinformatics and computational modeling were significantly associated with a higher JIF value of the journal in which such contributions were published. Our analysis suggests that research studies involving such techniques/approaches are more likely to be published in higher-ranked pharmacology journals. Full article
(This article belongs to the Special Issue Bibliometrics)
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Article
Field Programmable Gate Array Applications—A Scientometric Review
by
Juan Ruiz-Rosero
,
Gustavo Ramirez-Gonzalez
and
Rahul Khanna
Computation 2019, 7(4), 63; https://doi.org/10.3390/computation7040063 - 11 Nov 2019
Cited by 32 | Viewed by 12343
Abstract
Field Programmable Gate Array (FPGA) is a general purpose programmable logic device that can be configured by a customer after manufacturing to perform from a simple logic gate operations to complex systems on chip or even artificial intelligence systems. Scientific publications related to [...] Read more.
Field Programmable Gate Array (FPGA) is a general purpose programmable logic device that can be configured by a customer after manufacturing to perform from a simple logic gate operations to complex systems on chip or even artificial intelligence systems. Scientific publications related to FPGA started in 1992 and, up to now, we found more than 70,000 documents in the two leading scientific databases (Scopus and Clarivative Web of Science). These publications show the vast range of applications based on FPGAs, from the new mechanism that enables the magnetic suspension system for the kilogram redefinition, to the Mars rovers’ navigation systems. This paper reviews the top FPGAs’ applications by a scientometric analysis in ScientoPy, covering publications related to FPGAs from 1992 to 2018. Here we found the top 150 applications that we divided into the following categories: digital control, communication interfaces, networking, computer security, cryptography techniques, machine learning, digital signal processing, image and video processing, big data, computer algorithms and other applications. Also, we present an evolution and trend analysis of the related applications. Full article
(This article belongs to the Special Issue Bibliometrics)
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Review

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Review
Science Mapping the Academic Knowledge on Business Improvement Districts
by
Diogo Gaspar Silva
,
Herculano Cachinho
and
Kevin Ward
Computation 2022, 10(2), 29; https://doi.org/10.3390/computation10020029 - 13 Feb 2022
Cited by 1 | Viewed by 2361
Abstract
Business Improvement Districts (BIDs) are a contemporary urban revitalization policy that has been set in motion through international policymaking circuits. They have been presented as a panacea to the economic and social challenges facing many cities and traditional shopping districts. However, a comprehensive [...] Read more.
Business Improvement Districts (BIDs) are a contemporary urban revitalization policy that has been set in motion through international policymaking circuits. They have been presented as a panacea to the economic and social challenges facing many cities and traditional shopping districts. However, a comprehensive overview of the academic literature on this form of local governance remains to be conducted. Drawing on bibliometric methods and bibliometrix R-tool, this paper maps and examines the state-of-the-art of academic knowledge on BIDs published between 1979 and 2021. Findings suggest that (i) scientific production has increased since the early 2000s, has crossed US borders but remains highly Anglo-Saxon-centered; (ii) academic knowledge on BIDs is multidisciplinary and has been published in high-impact journals; (iii) influential documents on BIDs have centered on three issues: urban governance/politics, policy mobilities–mutation and impacts assessment and criticisms; (iv) while author collaboration networks exist, the interaction between them is limited; (v) the conceptualization of BIDs has changed over time, both in thematic and geographical focus. These results constitute the first science mapping on the academic literature on BIDs, and we argue they should inform future scientific debates about the studying of this form of local governance. Full article
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Review
RFID Applications and Security Review
by
Cesar Munoz-Ausecha
,
Juan Ruiz-Rosero
and
Gustavo Ramirez-Gonzalez
Computation 2021, 9(6), 69; https://doi.org/10.3390/computation9060069 - 10 Jun 2021
Cited by 24 | Viewed by 6320
Abstract
Radio frequency identification (RFID) is widely used in several contexts, such as logistics, supply chains, asset tracking, and health, among others, therefore drawing the attention of many researchers. This paper presents a review of the most cited topics regarding RFID focused on applications, [...] Read more.
Radio frequency identification (RFID) is widely used in several contexts, such as logistics, supply chains, asset tracking, and health, among others, therefore drawing the attention of many researchers. This paper presents a review of the most cited topics regarding RFID focused on applications, security, and privacy. A total of 62,685 records were downloaded from the Web of Science (WoS) and Scopus core databases and processed, reconciling the datasets to remove duplicates, resulting in 40,677 unique elements. Fundamental indicators were extracted and are presented, such as the citation number, average growth rate, and average number of documents per year. We extracted the top topics and reviewed the relevant indicators using a free Python tool, ScientoPy. The results are discussed in the following sections: the first is the Applications Section, whose subsections are the Internet of Things (IoT), Supply Chain Management, Localization, Traceability, Logistics, Ubiquitous Computing, Healthcare, and Access Control; the second is the Security and Privacy section, whose subsections are Authentication, Privacy, and Ownership Transfer; finally, we present the Discussion section. This paper intends to provide the reader with a global view of the current status of trending RFID topics and present different analyses from different perspectives depending on motivations or background. Full article
(This article belongs to the Special Issue Bibliometrics)
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