Competence Centre for Bibliometrics

Start of the project: 01-Dec-2008 - End of the project: 31-Dec-2021

Only 20 years ago, bibliometrics were so exotic that at best experts dealt with the field. Today, bibliometric indicators such as the Journal Impact Factor or the h-index are provided by large literature databases as a matter of course, and they have found their way into evaluation, steering, and funding processes. This makes proficient handling and interpretation of such indicators indispensable. However, the development of bibliometric competencies and of advanced methods and indicators has not kept pace with the rapidly growing diffusion of their use.

In 2009 the Competence Centre for Bibliometrics was founded in order to eliminate these deficits and to keep up with the international developments. Funded by the Federal Ministry of Education and Research (BMBF), the Institute for Research Information and Quality Assurance (iFQ – coordinator), the Fraunhofer Institute for Systems and Innovation Research (ISI), Bielefeld University, and the FIZ Karlsruhe – Leibniz Institute for Information Infrastructure all combined their competencies in the form of a consortium. The objective was to construct an in-house database referring to the literature databases Scopus (Elsevier) and Web of Science (Thomson Reuters). Based on quality control, contortion callipers, and unification of author names and addresses, the data stock was corrected and extended. On this basis, the Competence Centre for Bibliometrics started several research projects to define new quality standards in bibliometrics and develop advanced indicators. Furthermore, the consortium members initiated specialised bibliometric projects on collaboration analysis, impact measurement, publication strategies etc.

Since 2014, the GESIS – Leibniz Institute for the Social Sciences, the Max Planck Society, and the Forschungszentrum Jülich have joined the Competence Centre for Bibliometrics. The main objective is now to make the database a permanent research infrastructure which is open to new services and applications. The former iFQ, now Research System and Science Dynamics research area of the DZHW, aims to use the Competence Centre for Bibliometrics to strengthen its research activities in the general field of indicators, methods, and bibliometrics. It focuses on the development of indicators, quality assurance and quality assessment, subject classification, and network analysis.

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Publications

Validation of the Astro dataset clustering solutions with external data.

Donner, P. (2020).
Validation of the Astro dataset clustering solutions with external data. Scientometrics, in print. https://doi.org/10.1007/s11192-020-03780-3
Abstract

We conduct an independent cluster validation study on published clustering solutions of a research testbed corpus, the Astro dataset of publication records from astronomy and astrophysics. We extend the dataset by collecting external validation data serving as proxies for the latent structure of the corpus. Specifically, we collect (1) grant funding information related to the publications, (2) data on topical special issues, (3) on specific journals’ internal topic classifications and (4) usage data from the main online bibliographic database of the discipline. The latter three types of data are newly introduced for the purpose of clustering validation and the rationale for using them for this task is set out.

Comparison of Web of Science, Scopus and Dimensions databases.

Stahlschmidt, S., & Stephen, D. (2020).
Comparison of Web of Science, Scopus and Dimensions databases. Report to Kompetenzzentrum Bibliometrie. Hannover: DZHW.

The implicit preference of bibliometrics for basic research.

Donner, P., & Schmoch, U. (2020).
The implicit preference of bibliometrics for basic research. Scientometrics, 124, 1411-1419. https://doi.org/10.1007/s11192-020-03516-3
Abstract

By individually associating articles to basic or applied research, it is shown that basic articles are cited more frequently than applied ones. Dividing the subject categories of the Web of Science into a basic and an applied part, the mean field-normalization rate is referred to the applied or basic part depending on the research orientation of the paper analysed. By this approach, a distinct difference of the citations for the applied and basic parts of most subject categories is found. However, differences of the citation scores of applied and basic research organisations are found as well, but are less clear. The explanation is that applied and basic research organisations generally publish a mix of basic and applied articles. [...]

Comparing institutional-level bibliometric research performance indicator values based on different affiliation disambiguation systems.

Donner, P., Rimmert, C., & van Eck, N.J. (2020).
Comparing institutional-level bibliometric research performance indicator values based on different affiliation disambiguation systems. Quantitative Science Studies, Volume 1 Issue 1, MIT Press, 150-170.
Abstract

The present study is an evaluation of three frequently used institution name disambiguation systems. The Web of Science normalized institution names and Organization Enhanced system and the Scopus Affiliation ID system are tested against a complete, independent institution disambiguation system for a sample of German public sector research organizations. The independent system is used as the gold standard in the evaluations that we perform. We study the coverage of the disambiguation systems and, in particular, the differences in a number of commonly used bibliometric indicators. The key finding is that for the sample institutions, the studied systems provide bibliometric indicator values that have only a limited accuracy. [...]

Document type assignment accuracy in the journal citation index data of Web of Science.

Donner, P. (2017).
Document type assignment accuracy in the journal citation index data of Web of Science. Scientometrics, 113(1), 219-236.
Abstract

This article reports the results of a study of the correctness of document type assignments in the commercial citation index database Web of Science (SCIE, SSCI, AHCI collections). The document type assignments for publication records are compared to those given on the official journal websites or in the publication full-texts for a random sample of 791 Web of Science records across the four document type categories articles, letters, reviews and others, according to the definitions of WoS. The proportion of incorrect assignments across document types and its influence on document specific normalized citations scores are analysed. It is found that document type data is correct in 94% of records. [...]

Enhanced self-citation detection by fuzzy author name matching and complementary error estimates.

Donner, P. (2016).
Enhanced self-citation detection by fuzzy author name matching and complementary error estimates. Journal of the Association for Information Science and Technology, 662–670.
Abstract

In this article I investigate the shortcomings of exact string match-based author self-citation detection methods. The contributions of this study are twofold. First, I apply a fuzzy string matching algorithm for selfcitation detection and benchmark this approach and other common methods of exclusively author namebased self-citation detection against a manually curated ground truth sample. Near full recall can be achieved with the proposed method while incurring only negligible precision loss. Second, I report some important observations from the results about the extent of latent self-citations and their characteristics and give an example of the effect of improved self-citation detection on the document level self-citation rate of [...].

Presentations

Effect of publication month on citation impact.

Donner, P. (2017, Oktober).
Effect of publication month on citation impact. Vortrag am Science & Technology Policy Research and Information Center, National Applied Research Laboratories, Taipei, Taiwan.
Abstract

A standard procedure in citation analysis is that all papers published in one year are assessed at the same later point in time, implicitly treating all publications as if they were published at the exact same date. This leads to systematic bias in favor of early-months publications and against late-months publications. This contribution analyses the size of this distortion on a large body of publications from all disciplines over citation windows of up to 15 years. It is found that early-month publications enjoy a substantial citation advantage, which arises from citations received in the first three years after publication. [...]

Lead Researcher

Stephan Stahlschmidt
Dr. Stephan Stahlschmidt Lead Researcher +49 30 2064177-18

Researchers

Paul Donner Alex Fenton Marion Schmidt Dr. Dimity Stephen

Project website

http://www.bibliometrie.info

Funded by

Bundesministerium für Bildung und Forschung