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Swiss Reproducibility Network

To promote rigorous research and robust results in Switzerland.

Eva Furrer and Valentin Amrhein

The SwissRN is a grassroots movement – everybody can participate, no matter the field they work in, no matter if they are from a big or a small university or from another institution within academia, no matter if they are senior or junior. The common ground of these diverse researchers is the desire to increase reproducibility of research. The goal of the network is to benefit from diversity, to push for trustworthiness from the bottom up, and, quite simply, to promote a culture change towards a focus on quality rather than novelty.

The original reproducibility network was created in the UK, the UKRN, other national networks will follow soon in Germany, Australia and Slovakia.

Diversity is a strength of the SwissRN. There will be a chorus of different voices, for example:

Hanno Würbel “Rigorous and reproducible research depends on a healthy research culture. As the research ecosystem is dynamic and researchers adapt to new incentives, research performance needs to be assessed and refined continuously. With the SwissRN we aim to contribute to a healthy research culture and facilitate performance standards that promote rigorous and reproducible research."   Hanno Würbel, Animal Welfare, University of Bern

 

Evie Vergauwe “I want to contribute to a better science and science culture. I hope that, by working together with researchers across disciplines, career stages, and institutions, we can increase the reproducibility and credibility of Swiss-based research, and create an incentive structure that reflects the efforts towards better research."   Evie Vergauwe, Psychology, University of Geneva

 

Daniel Stekhoven “The level of reproducibility is very different across the many fields of research and development. I would like to take the best of all worlds and push into an era where most published research findings are correct – and ultimately, reproducible!"   Daniel Stekhoven, Bioinformatics, ETH Zurich

 

 

Nicolas Rothen “I share the vision that the quality and value of science is based on transparency and reproducibility. SwissRN is an exciting major step in this direction."   Nicolas Rothen, Psychology, FernUni Schweiz

 

 

Meike Ramon “As a local node leader at UniFR, together with my team, I will focus on identifying best practices and advocating for them among researchers. This involves for instance identifying and implementing standards for data sharing - and extends to working with journal editors who can ensure that reproducibility is a requirement for publication. With reproducibility networks just emerging internationally, this is an exciting time to get involved in the movement."   Meike Ramon, Psychology, University of Fribourg

 

Patricia Palagi “Reproducibility in bioinformatics and life sciences research is a primary concern at SIB. We contribute to promoting reproducible research by training scientists in best practices for robust and high-quality research, among other things. The Swiss Reproducibility Network brings together scientists from several different fields who face very similar issues. The network’s multidisciplinary environment will promote new opportunities for learning from peers. I’m sure it will positively impact Swiss research and will enrich SIB’ training offer as well."   Patricia Palagi, Team Leader, SIB Training, SIB Swiss Institute of Bioinformatics

 

Laurenz Meier “The University of Neuchâtel is a comparatively small university, so exchanges between students and researchers, as well as between faculties, are easier and a strength that we would like to capitalize on. We aim to provide an overview of the existing courses (e.g. lectures, doctoral programs) and to promote interdisciplinary and interfaculty exchange by means of short workshops and meetings."   Laurenz Meier, Psychology, University of Neuchâtel

 

Leonhard Held“The reproducibility of research findings is crucial for the credibility of science. Many factors contribute to irreproducible research, including poor methodology, poor reporting and incentives that focus on quantity rather than quality, novelty rather than replication. The Swiss Reproducibility Network offers unique possibilities to improve research quality and to change the research landscape in Switzerland for the better. I am proud to be part of this exciting initiative."   Leonhard Held, Biostatistics, University of Zurich

 

Michael Dayan “In my field, neuroimaging, the variety of approaches and tools is such that building on other researcher’s work can often be a major challenge. The issue of low reproducibility that hampers generalization of research findings is faced by many fields. It is my hope that together within the Swiss Reproducibility Network we will learn from each other to promote best practices to enhance reproducibility, build awareness on the subject, and help improve research generalizability in whichever way we can.”   Michael Dayan, Neuroimaging, EPFL/Unige Campus Biotech

 

Florian Cova “In my field of research, philosophy, numerous heated debates about human nature and behavior have turned and are still turning on famous experiments that ultimately failed to replicate. As such, my goal is not only to encourage researchers to scrutinize and replicate influential studies, but also to sensibilize them to the need for replication, and the way unreliable but famous results can lead us astray in theorizing."   Florian Cova, Philosophy, University of Geneva

 

Valentin Amrhein “The most important aspect of reproducibility, among all the other most important aspects, is communication. Currently, researchers are paid for drawing conclusions from isolated bits of research that we call “studies”, and for communicating the conclusions in aphoristic PR texts that we call “papers”. It should be no surprise that such conclusions are often not reproducible. I’m looking forward to the debates in the Swiss Reproducibility Network, and I hope the debates will transfer to the universities and funding bodies."   Valentin Amrhein, Zoology, University of Basel

 


Background Reading

Monya Baker, 1,500 scientists lift the lid on reproducibility. Nature 533, 452–454 (2016). https://doi.org/10.1038/533452a

Marcus R. Munafò, Brian A. Nosek, Dorothy V. M. Bishop, Katherine S. Button, Christopher D. Chambers, Nathalie Percie du Sert, Uri Simonsohn, Eric-Jan Wagenmakers, Jennifer J. Ware & John P. A. Ioannidis, A manifesto for reproducible science. Nature Human Behaviour 1, 0021 (2017). https://doi.org/10.1038/s41562-016-0021

Improving Reproducibility in the Empirical Sciences, Royal Netherlands Academy of Arts and Sciences, Amasterdam, 2018. https://www.knaw.nl/en/news/publications/replication-studies

Reproducibility and Replicability in Science, National Academies of Sciences, Engineering, and Medicine, Washington, DC, 2019. https://doi.org/10.17226/25303.

Chris Chambers, What’s next for Registered Reports? Nature 573, 187-189 (2019). https://doi.org/10.1038/d41586-019-02674-6

David Moher, Lex Bouter, Sabine Kleinert, Paul Glasziou, Mai Har Sham, Virginia Barbour, Nicole Foeger, Ulrich Dirnagl, The Hong Kong Principles for assessing researchers: Fostering research integrity. PLoS Biol 18(7): e3000737. https://doi.org/10.1371/journal.pbio.3000737