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March 28, 2026Open Access

Computational Reproducibility: A Primer from UKRN

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Authors

ASAnna SchultzeLondon School of Hygiene & Tropical MedicineLSLouise SaulUniversity of SouthamptonEREtienne B. RoeschUniversity of Reading

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Implication

This primer introduces computational reproducibility challenges in research, suggesting practical guidance for improvement.

Key Points

  • The aim is to explain the key concepts and challenges of computational reproducibility in research.
  • Introduced key concepts related to computational reproducibility.
  • Outlined challenges like ambiguous methods and resource availability.
  • Provided practical guidance on improving reproducibility and transparency.
  • Highlighted the importance of reproducibility for understanding and evaluating research.
  • Emphasized that reproducibility does not guarantee correctness but supports knowledge building.
  • Introduced the FAIR principles as a framework for assessing computational tools.

Cite This Study

Schultze et al. (2026) studied this question.

synapsesocial.com/papers/69c7725e8bbfbc51511e2d07https://doi.org/10.5281/zenodo.19232890
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  4. 4Advancing Reproducibility in Computer \& Computational Science: Experiences, Challenges, and Recommendations2026
  5. 5Reproducibility Levels in Practice: a pragmatic framework for computational research2026