As dedicated data curators, we’re excited to showcase curated data collections that will hopefully ignite your research interests. Today we present you:
Thematic Data Collection on Replication Material
The credibility of scientific findings depends on the reproducibility and replicability of the evidence. Reproducibility refers to reproducing scientific findings using the original data, while replication involves testing the robustness of a previous finding using different data.1 However, challenges to credibility have been recognized in different disciplines such as psychology2, sociology3, and political science4. Various reasons underpin this issue, with methodological shortcomings in procedure, measurement, and statistical analysis, as well as questionable research practices and publication bias, often being discussed.
This has led to initiatives calling for a credibility revolution, which include transparency in reporting and data sharing at the heart of open science practices.5 A lack of transparency in reporting and concealment of original data is a major obstacle to scientific credibility. Findings reported with low transparency are difficult to reproduce and replicate simply because it is hard to understand what was done in the original study. Therefore, sharing all aspects of the methodology, including field reports, questionnaires, and analysis codes, is important to understanding the methodological and analytical decisions made.6 Another crucial aspect to ensure greater transparency is to share the original data on which scientific conclusions are based.
GESIS supports researchers in implementing open science practices and offers various options for archiving and sharing data and materials. This enables researchers to adhere to good research data management practices, such as complying with the FAIR principles (making research data findable, accessible, interoperable, and reusable), which makes data easier to discover and reuse. In collaboration with leading German social science journals, GESIS has launched a special service for providing social science data for reproduction and replication purposes.
GESIS has curated a thematic data collection on “replication material” linked to published articles, providing the opportunity to replicate studies on a variety of topics. For example, available data and script files can be used to fully replicate an analysis of an insightful study on motivation to learn in adulthood7, which revealed strong correlations with a need for cognition and self-concept of ability, as well as moderate correlations with the personality traits openness and conscientiousness. The collection also includes data and script files for replicating an insightful study on gendered hiring discrimination and beauty-based treatment.8 The study shows that attractive applicants receive higher competence ratings and are more likely to be invited to job interviews than less attractive candidates. However, only men consistently benefit from their looks, while women only benefit from a beauty premium in female-typed jobs, not male-typed ones. Lastly, the collection provides replication files for a revealing study on place inequality9, which showed that the place in which young refugees reside is linked to their chances of completing vocational education and training, which offers them a promising opportunity for professional and social integration. These are only a few examples of published syntax files and datasets that can be used to replicate these results in professional and educational contexts.
References
- Parsons, S., Azevedo, F., Elsherif, M.M. et al. A community-sourced glossary of open scholarship terms. Nat Hum Behav 6, 312–318 (2022). https://doi.org/10.1038/s41562-021-01269-4
- Nosek BA, Hardwicke TE, Moshontz H, et al. Replicability, Robustness, and Reproducibility in Psychological Science. Annu Rev Psychol. 2022;73:719-748. https://doi.org/10.1146/annurev-psych-020821-114157
- Freese, J., & Peterson, D. (2017). Replication in Social Science. Annual Review of Sociology, 43(1), 147-165. https://doi.org/10.1146/annurev-soc-060116-053450
- Brodeur, A., Esterling, K., Ankel-Peters, J., et al. (2024). Promoting Reproducibility and Replicability in Political Science. Research & Politics, 11(1). https://doi.org/10.1177/20531680241233439
- Korbmacher, M., Azevedo, F., Pennington, C.R. et al. The replication crisis has led to positive structural, procedural, and community changes. Commun Psychol 1, 3 (2023). https://doi.org/10.1038/s44271-023-00003-2
- Jedinger, Alexander, Oliver Watteler, and André Förster. 2018. “Improving the quality of survey data documentation: A total survey error perspective.” Data 3 (4): 45. doi: https://doi.org/10.3390/data3040045.
- Gorges, J. (2025). Global motivation to learn and adult learning: A nomological network analysis and a four-year longitudinal study. Learning an Individual Differences, 123, Article 102763. https://doi.org/10.1016/j.lindif.2025.102763
- Kühn, J., & Wolbring, T. (2024). Beauty pays, but not under all circumstances: Evidence on gendered hiring discrimination from a novel experimental treatment using deepfakes. Research in Social Stratification and Mobility, 94, Article 100992. https://doi.org/10.1016/j.rssm.2024.100992
- Meyer, F., & Winkler, O. (2023). Place of residence does matter for educational integration: The relevance of spatial contexts for refugees’ transition to VET in Germany. Social Sciences, 12(3), 120. https://doi.org/10.3390/socsci12030120