Introducing metaknowledge : Software for computational research in information science, network analysis, and science of science

McLevey, John; McIlroy-Young, Reid

doi:10.1016/j.joi.2016.12.005

Cited by 39 publications

(26 citation statements)

References 60 publications

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“…The program can be downloaded for free and a comprehensive handbook explaining all functions is available. With the program meta-knowledge (McLevey & McIlroy-Young, 2017) and the web tool RPYS i/o (Comins & Leydesdorff, 2016) two other resources have been developed in recent years for doing cited references analyses, too. However, CRExplorer has a much broader functionality than both other resources.…”

Section: Softwarementioning

confidence: 99%

Discovering seminal works with marker papers

Haunschild

Marx

2020

Scientometrics

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Bibliometric information retrieval in databases can employ different strategies. Commonly, queries are performed by searching in title, abstract and/or author keywords (author vocabulary). More advanced queries employ database keywords to search in a controlled vocabulary. Queries based on search terms can be augmented with their citing papers if a research field cannot be curtailed by the search query alone. Here, we present another strategy to discover the most important papers of a research field. A marker paper is used to reveal the most important works for the relevant community. All papers co-cited with the marker paper are analyzed using reference publication year spectroscopy (RPYS). For demonstration of the marker paper approach, density functional theory (DFT) is used as a research field. Comparisons between a prior RPYS on a publication set compiled using a keyword-based search in a controlled vocabulary and three different co-citation RPYS (RPYS-CO) analyses show very similar results. Similarities and differences are discussed.

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Section: Softwarementioning

confidence: 99%

Discovering seminal works with marker papers

Haunschild

Marx

2020

Scientometrics

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“…The programme is available at www.crexplorer.net (a comprehensive handbook explaining all functions is also available). With the programme Metaknowledge (McLevey and McIlroy-Young 2017), the Bibliometrix R package (Aria and Cuccurullo 2017), and the web tool RPYS i/o (Comins and Leydesdorff 2016), three other tools have been developed in recent years for doing CRs analyses, too. However, CRExplorer has a much broader functionality than the other tools.…”

Section: Methodsmentioning

confidence: 99%

Influential cited references in FEMS Microbiology Letters: lessons from Reference Publication Year Spectroscopy (RPYS)

Haunschild

Bauer

Bornmann

2019

FEMS Microbiology Letters

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The journal FEMS Microbiology Letters covers all aspects of microbiology including virology. On which scientific shoulders do the papers published in this journal stand? Which are the classic papers used by the authors? We aim to answer these questions in this study by applying the Reference Publication Year Spectroscopy (RPYS) analysis to all papers published in this journal between 1977 and 2017. In total, 16 837 publications with 410 586 cited references are analyzed. Mainly, the studies published in the journal FEMS Microbiology Letters draw knowledge from methods developed to quantify or characterize biochemical substances such as proteins, nucleic acids, lipids, or carbohydrates and from improvements of techniques suitable for studies of bacterial genetics. The techniques frequently used for studying the genetic of microorganisms in FEMS Microbiology Letters’ studies were developed using samples prepared from microorganisms. Methods required for the investigation of proteins, carbohydrates, or lipids were mostly transferred from other fields of life science to microbiology.

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“…In addition, bibliometric programming frameworks exist for the programming languages Python (Tethne (github.com/diging/tethne (accessed on 11 June 2021)), Bibliotool [50], metaknowledge [51]), and R (bibliometrix [4]). They can be used to generate bibliometric networks; however, the computation for most of these frameworks is not implemented in parallel.…”

Section: Related Workmentioning

confidence: 99%

Ambalytics: A Scalable and Distributed System Architecture Concept for Bibliometric Network Analyses

et al. 2021

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A deep understanding about a field of research is valuable for academic researchers. In addition to technical knowledge, this includes knowledge about subareas, open research questions, and social communities (networks) of individuals and organizations within a given field. With bibliometric analyses, researchers can acquire quantitatively valuable knowledge about a research area by using bibliographic information on academic publications provided by bibliographic data providers. Bibliometric analyses include the calculation of bibliometric networks to describe affiliations or similarities of bibliometric entities (e.g., authors) and group them into clusters representing subareas or communities. Calculating and visualizing bibliometric networks is a nontrivial and time-consuming data science task that requires highly skilled individuals. In addition to domain knowledge, researchers must often provide statistical knowledge and programming skills or use software tools having limited functionality and usability. In this paper, we present the ambalytics bibliometric platform, which reduces the complexity of bibliometric network analysis and the visualization of results. It accompanies users through the process of bibliometric analysis and eliminates the need for individuals to have programming skills and statistical knowledge, while preserving advanced functionality, such as algorithm parameterization, for experts. As a proof-of-concept, and as an example of bibliometric analyses outcomes, the calculation of research fronts networks based on a hybrid similarity approach is shown. Being designed to scale, ambalytics makes use of distributed systems concepts and technologies. It is based on the microservice architecture concept and uses the Kubernetes framework for orchestration. This paper presents the initial building block of a comprehensive bibliometric analysis platform called ambalytics, which aims at a high usability for users as well as scalability.

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Introducing metaknowledge : Software for computational research in information science, network analysis, and science of science

Cited by 39 publications

References 60 publications

Discovering seminal works with marker papers

Discovering seminal works with marker papers

Influential cited references in FEMS Microbiology Letters: lessons from Reference Publication Year Spectroscopy (RPYS)

Ambalytics: A Scalable and Distributed System Architecture Concept for Bibliometric Network Analyses

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