Dataset of international migration among German-affiliated researchers in Scopus over 1996-2020
This dataset contains one of the main outputs of a series of studies on international migration among German-affiliated researchers based on Scopus bibliometric data. The migration flows are inferred from the changes of affiliation addresses in Scopus publications from 1996-2020. Scopus data is owned and maintained by Elsevier.
This dataset is provided under a CC BY-NC-SA Creative Commons v 4.0 license (Attribution-NonCommercial-ShareAlike). This means that other individuals may remix, tweak, and build upon these data non-commercially, as long as they provide citations to this data repository (https://doi.org/10.6084/m9.figshare.18433139) and the two referenced articles listed below, and license the new creations under identical terms.
For more details about the study, please refer to the following two articles.
Zhao, X., Aref, S., Zagheni, E., & Stecklov, G., Return migration of German-affiliated researchers: analyzing departure and return by gender, cohort, and discipline using Scopus bibliometric data 1996–2020. Scientometrics (2022). https://doi.org/10.1007/s11192-022-04351-4
Zhao, X., Aref, S., Zagheni, E., & Stecklov, G., International migration in academia and citation performance: An analysis of German-aﬃliated researchers by gender and discipline using Scopus publications 1996-2020. In: Glänzel W, Heeﬀer S, Chi PS, et al (eds) Proceedings of the 18th International Conference on Scientometrics and Informetrics. ISSI, Leuven, p 1369–1380, (2021) https://arxiv.org/abs/2104.12380, https://kuleuven.app.box.com/s/kdhn54ndlmwtil3s4aaxmotl9fv9s329
The dataset is provided in a comma-separated values file (.csv file). Each row represents the international movement of a Scopus-published researcher from a country (Source) to another country (Target) in a specific year (move_year). The most likely gender and the most likely discipline for each researchers is inferred using data-driven methods as described in Zhao et al. (2022).
Description of variables (columns of the csv file):
"Source": the country where the researcher has moved from
"Target": the country where the researcher has moved to
"move_year": inferred year of the move
"gender": inferred gender
"discipline": inferred discipline
The binary genders inferred and used in our analysis do not refer directly to the sex of the researchers, assigned at birth or self-chosen; nor do they refer to the socially assigned or self-chosen genders of the authors.
The data can be used to produce migration models or possibly other measures, estimates, and analyses.
This study has been funded by the German Academic Exchange Service with funds from the Federal Ministry of Education and Research. This study has received access to the bibliometric data through the project “Kompetenzzentrum Bibliometrie,” and the authors acknowledge their funder BMBF (funding identification number 01PQ17001).
- Sociology not elsewhere classified
- Library and information studies not elsewhere classified
- Applied computing not elsewhere classified
- Social and community informatics
- Cultural geography
- Sociology and social studies of science and technology
- Human geography not elsewhere classified
- Population trends and policies
- Research, science and technology policy
- Science, technology and engineering curriculum and pedagogy