Ten simple rules for implementing open and reproducible research practices after attending a training course

Verena Heise, Constance Holman, Hung Lo, Ekaterini Maria Lyras, Mark Christopher Adkins, Maria Raisa Jessica Aquino, Konstantinos I Bougioukas, Katherine O Bray, Martyna Gajos, Xuanzong Guo, Corinna Hartling, Rodrigo Huerta-Gutierrez, Miroslava Jindrová, Joanne P M Kenney, Adrianna P Kępińska, Laura Kneller, Elena Lopez-Rodriguez, Felix Mühlensiepen, Angela Richards, Gareth Richards, Maximilian Siebert, James A Smith, Natalie Smith, Nicolai Stransky, Sirpa Tarvainen, Daniela Sofia Valdes, Kayleigh L Warrington, Nina-Maria Wilpert, Disa Witkowska, Mirela Zaneva, Jeanette Zanker and Tracey L Weissgerber

PLOS Computational Biology, 2023, vol. 19, issue 1, 1-11

Abstract: Open, reproducible, and replicable research practices are a fundamental part of science. Training is often organized on a grassroots level, offered by early career researchers, for early career researchers. Buffet style courses that cover many topics can inspire participants to try new things; however, they can also be overwhelming. Participants who want to implement new practices may not know where to start once they return to their research team. We describe ten simple rules to guide participants of relevant training courses in implementing robust research practices in their own projects, once they return to their research group. This includes (1) prioritizing and planning which practices to implement, which involves obtaining support and convincing others involved in the research project of the added value of implementing new practices; (2) managing problems that arise during implementation; and (3) making reproducible research and open science practices an integral part of a future research career. We also outline strategies that course organizers can use to prepare participants for implementation and support them during this process.

Date: 2023
References: Add references at CitEc
Citations:

Downloads: (external link)
https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1010750 (text/html)
https://journals.plos.org/ploscompbiol/article/fil ... 10750&type=printable (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:plo:pcbi00:1010750

DOI: 10.1371/journal.pcbi.1010750

Access Statistics for this article

More articles in PLOS Computational Biology from Public Library of Science
Bibliographic data for series maintained by ploscompbiol ().