Data retrieval, data cleaning and data merging
creating a database for bibliometric analyses
DOI:
https://doi.org/10.15291/pubmet.4758Ključne riječi:
bibliometrics, data cleaning, data merging, data retrieval, database mergingSažetak
Introduction: Bibliometric analyses have become fairly frequent in today's science (Donthu et al., 2021; Klarin, 2024; Öztürk et al., 2024). They help map out research areas and evaluate the quality of scientific research. Most bibliometric analyses today gather their data from Web of Science or Scopus. Yet, the methodology sections on obtaining that data often leave us wanting, especially in the few cases where datasets from both databases were merged (Echchakoui, 2020).
The aim of our research was to create a comprehensive database of all publications by Croatian clinicians, regardless of the research area, so we could map their areas of interest during the period 2005-2022, as well as study potential effects of Croatia’s European Union (EU) membership. Our focus on publications by clinicians rather than publications in clinical medicine led us to create a more complex data retrieval strategy, using affiliations instead of research areas.
Reference
Donthu, N., Kumar, S., Mukherjee, D., Pandey, N., & Lim, W. M. (2021). How to conduct a bibliometric analysis: An overview and guidelines. Journal of Business Research, 133, 285– 296. https://doi.org/10.1016/j.jbusres.2021.04.070
Echchakoui, S. (2020). Why and how to merge Scopus and Web of Science during bibliometric analysis: The case of sales force literature from 1912 to 2019. Journal of Marketing Analytics, 8(3), 165–184. https://doi.org/10.1057/s41270-020-00081-9
Klarin, A. (2024). How to conduct a bibliometric content analysis: Guidelines and contributions of content co-occurrence or co-word literature reviews. International Journal of Consumer Studies, 48(2), e13031. https://doi.org/10.1111/ijcs.13031
Öztürk, O., Kocaman, R., & Kanbach, D. K. (2024). How to design bibliometric research: An overview and a framework proposal. Review of Managerial Science. https://doi.org/10.1007/s11846-024-00738-0



