Bibliometrics

Bibliometrics refers to the quantitative analysis of scholarly publications and their citations. Using bibliometric methods, it is possible to show how scientific publications are perceived within the academic community, how certain topics develop, or which publication venues are used most frequently. Bibliometrics is also used to make structures, trends, and influences in research visible.

The ZHB is a signatory of the DORA Declaration (San Francisco Declaration on Research Assessment), which calls for research assessment to go beyond metrics and to recognize the quality and diversity of scholarly contributions.
In its bibliometric analyses and consultations, ZHB Lucerne also follows the Leiden Manifesto. This manifesto states that metrics should only complement, not replace, the qualitative assessment of research, and that disciplinary differences must be taken into account.

Bibliometric analyses provide only quantitative approximations and do not allow for definitive or comprehensive statements about research quality. Since there is no single clear way to assess scholarly performance, qualitative methods (peer review) and quantitative methods (bibliometrics) are combined.

The validity of bibliometric analyses depends largely on the quality and completeness of the data used — which rely primarily on English-language journal articles. Publications in other languages and formats, such as books, are less well represented, meaning that bibliometric data and analyses are often incomplete, especially in the humanities and social sciences.
The data for bibliometric analyses come from specialized citation databases. The most important among them are the multidisciplinary sources Web of Science (Clarivate Analytics), Scopus (Elsevier), and the open database OpenAlex.

There are various indicators used to measure the visibility of publications:

• Impact Factor (IF): Measures how often articles in a journal are cited on average. The Impact Factor does not refer to an individual article.
Data source: Web of Science (Thomson Reuters)

• H-Index: Combines the number of publications and citation frequency of an individual researcher. For example, a researcher has an H-Index of 10 if they have published 10 papers that have each been cited at least 10 times.
Data source: Varies

• SNIP (Source Normalized Impact per Paper): Weighs citations according to the citation practices of a specific field in order to account for disciplinary differences.
Data source: Scopus (Elsevier)

• SJR (SCImago Journal Rank): Rates journals based on both the number and prestige of citations received; citations from highly regarded journals carry more weight.
Data source: Scopus (Elsevier)

To improve the accuracy of publication data and analyses, researchers can do the following:

• Use ORCID: Create an ORCID iD and include it in all publications. ORCID is integrated into the HSLU’s CRIS (FIS) and PPDB systems (see ORCID FIS Guide).

• Avoid name variations: Use a consistent form of your name and the same institutional affiliation across all publications.

• Check publication lists: Regularly review and, if necessary, correct your profiles in databases such as Scopus, Web of Science, or OpenAlex.

ZHB Lucerne is currently developing services in the field of bibliometrics.
For questions or inquiries, please contact: bibliometrie@zhbluzern.ch