In recent years, the credibility of scientific research has come under increasing scrutiny, exemplified by significant studies such as the Reproducibility Project: Cancer Biology conducted by the Center for Open Science (COS). This project aimed to replicate 50 high-impact cancer biology studies, revealing concerning replication rates. Computational reproducibility is a cornerstone of reproducible science, and every researcher, whether early career or senior, in computational sciences should understand its basic principles.

This workshop will explore strategies for enhancing reproducibility in data and life
sciences research through transparency, data sharing, and rigorous methodologies. Interactive sessions will focus on implementing Open Science practices in labs using lab management guides, such as Kirstie Whitaker’s manual. Lab manuals are crucial for detailing reproducible practices in data and computational pipeline management, lab inventory, protocols, and documentation.

Program

• Introduction – 10 min
• Reproducibility experiences – 10 min
• Sessions on working in groups 2×20 min
• Discussion + wrap-up

Organizers

• Ruben Dörfel, PhD Student, Rigshospitalet, Karolinska Institutet
• Veronika Cheplygina, Associate Professor, IT University of Copenhagen
• Ding He, Data Steward, DTU Biosustain
• Melanie Ganz-Benjaminsen, Associate Professor, University of Copenhagen, Rigshospitalet
• Marta Topor, PostDoc, Linköping University

Level

Introductory: Suitable for beginners with little to no prior knowledge of the
subject.