Bibliometrics

The Web of Science Core Collection database (Clarivate) serves as the basis for this data.

The Scimago Journal Rank (SJR) shows the reputation of a journal by measuring the average number of citations taking account of the Page Rank algorithm. The Scorpus database (Elsevier) serves as the basis for this data.

The Eigenfactor score is a rating of the total scientific influence of journals according to the number of citations of articles from the respective journal (network analysis). Using existing citation data (Web of Science), two scores are calculated with the Page Rank algorithm: the Eigenfactor Score (ES) and the Article Influence Score (AIS). Both are freely accessible.

Science is a competitive field and including an author’s affiliation to an institution in publications is of key importance. Universities and their researchers are frequently ranked in national and international comparisons according to their publication output, with third-party funding often awarded on the basis of these rankings. Clear and, above all, complete details are also important for other studies evaluating data on affiliation, e.g. analyses of inter-institutional cooperation.

In light of this, TU Berlin approved a set of guidelines for standardizing statements of affiliation in German and English-language publications in October 2019. These guidelines apply to all members of TU Berlin. They determine the use of a standardized name for the University (Technische Universität Berlin) as well as a standardized abbreviation (TU Berlin) and establish the procedures to be followed in the event of affiliation to more than one institution.

The guidelines ensure that all publications produced by researchers at TU Berlin are clearly, correctly, and fully assigned to Technische Universität Berlin. As such, they serve to increase the visibility of TU Berlin's research strengths and help ensure that the University’s research attracts funding. They also have a positive impact on national and international rankings.

You can read more about TU Berlin’s affiliation guidelines in our blog article: "TU Berlin beschließt Affiliationsrichtlinie” (german only)

Bibliometric analyses are useful for quantitatively measuring, evaluating, and comparing academic publications. They are increasingly used in science management, for example as an instrument to identify research trends or awarding merit-based funds.

Bibliometric analyses are solely an instrument of research management. They are never a replacement for a qualitative evaluation of research content. This is possible through peer review, the review of research by independent experts, for example.

The most important bibliometric data sources are the multidisciplinary literature and citation databases Web of Science and Scopus. It is important to note that the validity and meaningfulness of a bibliometric evaluation strongly depend on the quality and focus of the database. A researcher’s h-index can vary depending on which data source was used as a basis.

Individual scores should never be interpreted in isolation. Rather, the entirety of all indicators is to be considered and reasonably evaluated. For example, the number of publications (output) says nothing about the quality of the publications. Someone who publishes frequently is not necessarily publishing at a better qualitative level, just as someone who publishes less often is not necessarily publishing at a lesser qualitative level.

As the publication activities of academics strongly differ in individual disciplines, bibliometric indicators are not suitable for cross-disciplinary comparison.