five

Dataset of international migration among German-affiliated researchers in Scopus over 1996-2020

收藏
NIAID Data Ecosystem2026-03-13 收录
下载链接:
https://figshare.com/articles/dataset/Dataset_of_international_migration_among_German-affiliated_researchers_in_Scopus_over_1996-2020/18433139
下载链接
链接失效反馈
官方服务:
资源简介:
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.
创建时间:
2022-01-14
二维码
社区交流群
二维码
科研交流群
商业服务