Swiss Reproducibility Network

To promote rigorous research and robust results in Switzerland.

Eva Furrer

Go to: Sirro   SIRRO team

Strengthen the Interoperability and Reusability of Research Outputs (SIRRO)

Rigorous design, transparent reporting, and reproducible workflows are major factors strengthening the interoperability and reusability of research data and are hence crucial to increase the value of research data and, more broadly, the value of research outputs. The aims of the SIRRO project are to 1) fortify SwissRN as an existing community engaging with ORD practices that have the goal of strengthening interoperability and reusability, and 2) intensify the efforts of SwissRN towards a systematic assessment of the impact and obstacles in the implementation of ORD practices.

Fair principles

More specifically, the focus of this project is on the ORD practices of preregistration and data management planning as measures to avoid bias and to increase quality. The project contains four parts:

  1. Assessment of researchers’ understanding and perception of ORD practices across disciplines and their perceived impact on careers.
  2. Assessment of types of research outputs that are already produced and disciplinary differences herein.
  3. Assessment of hurdles and incentives for a community, here researchers in animal studies, to adopt preregistration and data management practices.
  4. Develop and dispense appropriate training activities on preregistration, data management practices and good research practices in general.

Funded by swissuniversities Swiss Open Research Data Grants program Track A, August 2022

Why preregistration? Ask the Texas sharpshooter

Texas sharpshooter

Work packages

Survey What is the understanding of ORD practices, and rigorous, transparent, and reproducible research practices more generally, across disciplines? What is the perceived impact of ORD related requirements on careers?
→ Large-scale, interdisciplinary survey together with FORS (Swiss Centre of Expertise in the Social Sciences)

Population: Researchers working at Swiss universities and universities of applied sciences


  1. Cover all types of research;
  2. Compare groups


  • Cluster Sampling (approx. 1500 institutes), multi-stage stratified sampling with over-sampling of some disciplines
  • Questions not normatively suggestive
  • Link to evaluation practices & barriers: feasibility of ORD implementation


Assessment What are research outputs? All digitally available information required to
  • reproduce research results
  • validate conclusions
  • reuse research data in further projects
  • raw and processed data
  • all software components of the research pipeline
  • preregistrations and/or protocols
  • standard operating procedures
What types of open research outputs are already produced and documented? Are there disciplinary differences in output type or quantity?
→ Exploratory data analysis with publicly available data from the SNSF


Feasibility What are the hurdles for a community to adopt preregistration as a measure more widely? Why are DMPs often not a part of preregistrations? What can be incentives to do both? How can researchers be supported for the adoption?
→ Feasibility study on the implementation of preregistration in the field of animal sciences


Training Design and teach Good Research Practice courses with a focus on preregistration and data management planning at several locations.
→ Four 1-day training events at
  • Uni Bern (31th May 2024),
  • Uni Geneva (7th June 2024),
  • Uni Zurich (6th May 2024) and
  • ETHz (6th May 2024)

Material available at osf.io/g45nt


Eva Furrer
Leonhard Held
Rachel Heyard
Michael Ochsner
Manuel Pfister
Christina Priboi
Evie Vergauwe
Hanno Würbel

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