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Open and reproducible research in musculoskeletal imaging: why it matters and how to implement it with the guidelines of the Open and Reproducible Musculoskeletal Imaging Research (ORMIR) community

  • Serena Bonaretti*
  • , Mojtaba Barzegari
  • , Melissa Bevers
  • , Steven Boyd
  • , Andrew J. Burghardt
  • , Donnie Cameron
  • , Francesco Chiumento
  • , Gianluigi Crimi
  • , Gerald Degenhart
  • , Pholpat Durongbhan
  • , Michelle Alejandra Espinosa Hernandez
  • , Giulia Fraterrigo
  • , Ali Ghasem-Zadeh
  • , Lorenzo Grassi
  • , Jukka Hirvasniemi
  • , Seyedmahdi Hosseinitabatabaei
  • , Gianluca Iori
  • , Joeri Kok
  • , Michael Kuczynski
  • , Youngjun Lee
  • Cecilia Liberati, Sarah Manske, Matt Mccormick, Maria Monzon, Martino Pani, Simone Poncioni, Jilmen Quintiens, Sabine Rauber, Paul Ritsche, Alfonso Dario Santamaria, Francesco Santini, Fabio Sarto, Enrico Schileo, Vincent Stadelmann, Kathryn S. Stok, Rachel Surowiec, Fulvia Taddei, Jared Vicory, Matthias Walle, Mariska Wesseling, Danielle Whittier, Bettina Willie, Andy Kin On Wong, Dzenan Zukic
*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

The Open and Reproducible Musculoskeletal Imaging Research community is a scientific community dedicated to promoting openness and reproducibility in musculoskeletal imaging, image processing, and computational modeling. In this perspective paper, we outline the motivations for conducting transparent research and provide practical guidelines for implementing it. We start by defining open and reproducible research and describing the benefits and challenges of working transparently. Next, we redefine the outputs of a computational research study as-ideally-a combination of data, code, and a publication, recommend a folder and file structure that reflects these three study outcomes, and describe how to maintain and update such a structure during the study and at study publication. Finally, we emphasize that working in an open and reproducible manner is a learning process, and the best way to acquire the necessary competencies is simply to start.The Open and Reproducible Musculoskeletal Imaging Research community promotes openness and reproducibility in musculoskeletal imaging research. In this perspective paper, we explain why transparency matters and recommend how to conduct a computational study in an open and reproducible manner, focusing on its three outputs: data, code, and the publication. Finally, we highlight that the best way to learn these practices is simply to start.
Original languageEnglish
Article numberziag025
Number of pages10
JournalJBMR plus
Volume10
Issue number4
DOIs
Publication statusPublished - 1 Apr 2026

Keywords

  • Open research
  • reproducible research
  • data sharing
  • open-source code
  • computational narratives
  • guidelines
  • license
  • ORMIR

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