Reproducibility is vital for ensuring that research results are accurate and reliable, demonstrating that findings are not due to bias or chance. Reproducibility refers to the ability of other researchers to achieve the same results using the same dataset and analysis as the original study. Research is reproducible when other researchers can consistently replicate the results again with high reliability. 

In this blog, we look at the differences between reproducibility, repeatability and replicability, why reproducibility is important and how you can make your work reproducible.

Reproducibility, repeatability and replicability

Reproducibility, repeatability, and replicability are related terms that are often used interchangeably, though their meanings may differ across research communities and disciplines.

At Open Research Europe, we define reproducible research as research that can be executed by different researchers using the same data to achieve the same results. This definition aligns with the Claerbout and Karrenbach definition from 1992, which is widely used across disciplines. The definitions are as follows:

• Repeatable: Research is repeatable when the original researchers perform the same analysis on the same dataset and consistently produce the same findings.
• Reproducible: Research is reproducible when other researchers perform the same analysis on the same dataset and consistently produce the same findings. 
• Replicable: Research is replicable when other researchers perform new analyses on a new dataset and consistently produce the same findings. 

Why is reproducibility important to Open Research?

Science is dependent on the sharing of information. The growth of Open Research and open data has led to increased calls for researchers to improve the reproducibility of their work. Sharing data, code, and detailed research methods accelerate scientific discovery by making more elements of research available to all. Aside from faster progress, reproducibility offers numerous other benefits for the research community, including:

• Strengthening scientific evidence and reliability of results: When researchers can reproduce a study, it lends credibility to the original findings, making the original research more reliable, and conclusions supported by more evidence. This makes it more likely that research findings will be used to make a real-world impact by informing policy or practice.
• Increasing trust in science: Reproducible research helps maintain public trust in the scientific process, especially when public funding and policy decisions are involved.   
• Enabling research efficiency : reproducibility boosts efficiency in two main ways. First, reproducible research increases the likelihood that the research, or parts of it, can be reused by other researchers in the future. Second, by publishing negative results, researchers help their peers avoid redundant analyses that are unlikely to yield the desired outcomes.  
• Minimizing misinformation: Reviewers can spot mistakes more easily when researchers embrace transparency in the research process, provide detailed documentation of their methods and analyses, and share their research materials. This helps to avoid misinformation that can limit the replicability of research and, instead, leads to more accurate research papers. 

Benefits of reproducibility for authors

Making your work reproducible also offers additional benefits to you as an author. These include:

• Greater impact: Researchers who produce reproducible research share their underlying data and methods. Sharing detailed research data is associated with higher citation rates as other researchers use and credit the data in their projects. 
• Facilitating in-depth peer review: Reproducible research can result in higher-quality, faster peer review as reviewers have access to the data and analytical processes described in the manuscript. This increases the probability that errors are caught during the peer review process and reduces back-and-forth between authors and reviewers.  
• Enabling iterative science: Science is an iterative process, with many tasks repeated time and again. Reproducible research enables researchers to reuse previous research materials to execute similar research tasks more efficiently in new projects.  
• Fostering collaboration and reuse: Reproducible research opens the door to new partnerships to develop existing projects further. It also leads to greater reuse of research. Designing reproducible workflows and sharing all research outputs openly allows others to develop a deeper understanding of the work and build upon it. 

Learn more about how our Open Research guidelines help make your work reproducible.