Claudia Neuendorf (Universität Tübingen) & Aleksander Kocaj (Institut zur Qualitätsentwicklung im Bildungswesen)
In recent years, an increasing number of studies have been published questioning the robustness of the results from empirical studies. Reproducibility and replicability of research results are becoming increasingly important in empirical research. In this regard, Open Science practices are essential building blocks to increase the trust in research findings (Krammer & Svecnik, 2021). In this workshop, we address selected topics from the four core areas of Open Science that help ensure that the entire research process is transparent and accessible (van der Zee & Reich, 2018): (1) study design & preregistration, (2) Open Data, (3) transparency in analysis, and (4) study publication & Open Acess. We address aspects such as preregistration templates and preregistration requirements. In addition, we can discuss which platforms are available for publishing datasets, how to prepare and document research data according to FAIR criteria, and how to make analysis plans transparent and reproducible. We can also discuss data protection aspects of data sharing and how to deal with sensitive variables. The workshop concludes with outlooks on how studies can be published in open access and how data protection regulations can be complied with through synthetic data generation.
The workshop is scheduled for early 2023.