Challenges of scholarly communication: bibliometric transparency and impact

CHALLENGES OF SCHOLARLY COMMUNICATION: BIBLIOMETRIC TRANSPARENCY AND IMPACT

Analysing self-citations in a large bibliometric database
By Philipp Mayr-Schlegel 

Presentation slides

Citation metrics have value because they aim to make scientific assessment a level playing field, but urgent transparency-based adjustments are necessary to ensure that measurements yield the most accurate picture of impact and excellence. One problematic area is the handling of self-citations, which are either excluded or inappropriately accounted for when using bibliometric indicators for research evaluation. In this talk, in favour of openly tracking self-citations, I reported on a study of self-referencing behaviour among various academic disciplines as captured by the curated bibliometric database Web of Science. Specifically, I examined the behaviour of thousands of authors grouped into 15 subject areas like Biology, Chemistry, Science and Technology, Engineering, and Physics. I focused on the methodological set-up of the study and discussed data science related problems such as author name disambiguation and bibliometric indicator modelling. This talk was based on the following publication: Kacem, A., Flatt, J. W., & Mayr, P. (2020). Tracking self-citations in academic publishing. Scientometrics, 123(2), 1157–1165. https://doi.org/10.1007/s11192-020-03413-9

Research impact beyond scholarly communication: the big challenge of Scientometrics 2.0
By Pei-Shan Chi & Wolfgang Glänzel

Presentation Slides

The last two decades in the evolution of bibliometrics mark a significant turn towards the quantification and measurement of scientific communication beyond the scholarly one and towards a broader assessment of its various impacts on science and society. We summarized the background and the main characteristics of this evolution, referred to latest results in our related studies, and focused on the latent and real challenges in the use of the new metrics designed for the measurement of the broader impact of research. In addition to the critical review several examples were given to illustrate the large potential and added value of the new metrics when used judiciously and correctly. In conclusion we addressed and elaborated the framework of preconditions essential for improving coverage and reliability of both data sources and the metrics derived from those.