Publications

This study introduces an approach to estimate the uncertainty in bibliometric indicator values that is caused by data errors. This approach utilizes Bayesian regression models, estimated from empirical data samples, which are used to predict error-free data. Through direct Monte Carlo simulation—drawing many replicates of predicted data from the estimated regression models for the same input data—probability distributions for indicator values can be obtained which provide the information on their uncertainty due to data errors. [...]

The DZHW Scientists Survey 2023 is an online survey of full-time academic and artistic staff at German universities and equivalent institutions of higher education with the right to award doctorates. It is repeated at regular intervals as a trend study to explore the working and research conditions at German universities and equivalent institutions of higher education. The DZHW Scientists Survey 2023 was conducted from January to March 2023. The respondents therefore take a retrospective look at their working and research conditions during the Covid-19 pandemic and their current post-pandemic situation. The previous Scientists Surveys took place in 2010, 2016 and 2019/2020. [...] Full Abstract: https://doi.org/10.21249/DZHW:scs2023:1.0.0

The presence or absence of publishers in large bibliographic databases highlights tangible and symbolic differences between small and large publishers, underlining their diverging incentive structures. To assess these differences, this contribution explores reference data from small (open access) publishers and their journals in the Web of Science and Scopus. The analysis focuses on references that are not indexed in these databases and examines them from a text-as-data approach. The study frames two dimensions of relevance - visibility and impact - as proxies for assessing the scholarly bibliodiversity represented by small (open access) publishers.