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Authors

Eva Kormann

Tony Ross-Hellauer

Language
English

Keywords
Tools, practices, interventions, state of the evidence, open science, reproducibility

License
CC BY-SA 4.0 International

Target audience
Researchers, funders, publishers, research support staff, open science trainers

Prerequisites
None

Abstract

This module introduces key tools and best practices that enhance transparency and reproducibility across the research lifecycle. It provides an overview of the research process and highlights common sources of bias or error before presenting a suite of practical interventions—including preregistration, data management plans, open lab notebooks, open-source analysis tools (e.g., R, Python, Jupyter/Quarto, Docker), and data and code sharing practices.

The module also covers templates for documenting deviations from preregistration, reporting guidelines and checklists such as those offered by the EQUATOR Network, as well as preprints and good peer-review practices. A 20-minute video presentation and supporting materials illustrate how these tools apply across different epistemic contexts and summarise the current state of evidence on which interventions are most effective in strengthening research integrity and accountability.

Learning outcomes

By the end of this module, learners will be able to:

  1. Understand key concepts – Explain the importance of transparency and reproducibility in research and their role in supporting scientific integrity.

  2. Identify tools and practices – Recognise a range of practices that promote transparency, such as preregistration, data sharing, and reporting guidelines.

  3. Evaluate effectiveness – Assess current evidence on which reproducibility-enhancing interventions most effectively improve research quality.

  4. Apply best practices – Describe how to implement practical tools, including preregistration templates and transparent reporting checklists.

  5. Make informed decisions – Select and apply appropriate tools and workflows to improve rigor, accountability, and openness in their own research.

Skill Level: Beginner
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