Swiss Reproducibility Network

To promote rigorous research and robust results in Switzerland.

Updated by Zhixuan Li

Go to Working Group: Open Research Data   Preregistration and Registered Reports   Computational Reproducibility   Training   Research Assessment and Incentives

Go to: Grants     ReproducibiliTea

Working groups

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. See the Working Group’s webpage.

Contact: Gorka Fraga Gonzalez

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.

The working group acquired funding for and runs the SIRRO project.

Contact: Evie Vergauwe

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Computational Reproducibility

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

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The SwissRN working group on Training aims to provide pertinent training activities at different levels. All teaching materials will be made openly available.

The working group collaboratively wrote an article Ten simple rules for good research practice and is now involved in the SIRRO project.

Contact: Eva Furrer

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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.

The working group is involved in the SIRRO project.

Contact: Rachel Heyard

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Strengthen the Interoperability and Reusability of Research Outputs

The SIRRO grant is a Swiss Open Research Data Grants, Track A grant and started in March 2023.

See the Grants webpage for more information.

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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:

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