Open Research Data
In order to reproduce and replicate research findings, open and also FAIR research data are a prerequisite. However, publishing research data is still not a standard and studies show how difficult it is to gain access to research data upon request. The SwissRN working group aims to promote open research data, to improve and facilitate data management across different research disciplines, to provide a network to collaborate in Open Research Data projects (including project proposals for ORD calls) and to engage with different stakeholders to facilitate dissemination and uptake.
Contact: Leonhard Held
Preregistration and Registered Reports
Preregistration, or the practice of documenting research aspects such as hypothesis, sample size, design, data exclusion, and statistical analyses, before data collection or data analysis, can help reduce questionable research practices. When integrated into the publishing process in the form of Registered Reports, it can also reduce publication bias. The aim of the SwissRN working group on Preregistration and Registered Reports is to promote and support existing initiatives and services related to Preregistration and Registered Reports (e.g., through workshops and consulting services), as well as develop new initiatives with stakeholders.
Contact: Evie Vergauwe
Research Assessment and Incentives
Trustworthiness of research is unevitably linked to robustness, rigor and transparency. But the assessment of researchers for hiring and promotion rarely emphasizes behaviors that contribute to these factors. The SwissRN working group on Research Assessment and Incentives will be discussing possibilities to reward and recognise researchers for such behavior. In a dialogue with institutions and stakeholders the group will push for a change of culture. See the Hong Kong Principles for a starting point.
Replication studies are essential to confirm, expand or refute claims of new discoveries. Although replication has long been a central part of the scientific method, the so-called replication crisis has led to increased interest in replication in the last decade. The SwissRN working group on replication studies aims to discuss all aspects of the design, conduct and analysis of replication studies and to share best practices through trainings and workshops.
Contact: Leonhard Held
Reproducibility of research findings essentially depends on rigorous research methodology, including the selection of the study population to represent the target population, study design to control for potential confounders, study conduct to minimise risks of bias, adequate data analysis, and balanced interpretation of results. The aim of the SwissRN working group on research methodology is to promote rigorous research methods, considering commonalities and differences across different research disciplines, and to engage with different stakeholders to facilitate dissemination and uptake.
Contact: Hanno Würbel
The SwissRN working group on Training aims to provide pertinent training activities at different levels. All teaching materials will be made openly available.
See the Resources page for a list of training opportunities concerning reproducibility offered at Swiss institutions.
Computational reproducibility refers to the ability to reproduce scientific results using the same computational methods and data. This involves documenting all aspects of the analysis process, including data collection, preprocessing, analysis, and visualization, as well as the software and hardware environment used to perform the analysis. Our working group aims at learning from each other about tools, services and approaches to facilitate computational reproducibility. Based on this we aim to offer tutorials, workshop and best practices to onboard the research community to adopt rigorous, transparent and reproducible research practices. See the Working Group’s webpage.
Contact: Stekhoven Daniel
ReproducibiliTea is a grassroots journal club initiative that helps researchers create local Open Science journal clubs at their universities to discuss improving science, reproducibility and the Open Science movement, see https://reproducibilitea.org/.
ReproducibiliTeas at SwissRN local nodes:
- Basel: https://osf.io/kp98v/
- Bern: https://unibe-reptea.netlify.app/
- Geneva: https://reproducibilitea.org/journal-clubs/#Geneva
- Zurich: https://www.crs.uzh.ch/en/training/ReproducibiliTea.html