Research Reproducibility
Research reproducibility has become a major concern for the science community. Unless the published research provides insight into the process, we cannot rule out that the result may be statistically insignificant or incorrect.
Research is reproducible when others or your future self can replicate the process and obtain similar results for the same or different data. In a survey conducted among 1,500 scientists, it was found that over 70 percent had tried and failed to reproduce another scientist’s research, and more than 50 percent had failed to reproduce their own.
Open Science
Open science enables researchers to communicate the tools and best practices for reproducible, reliable, and trusted research. It makes all the factors from ideation to post publication, like methods, protocols, materials, data, code, and revisions, that went into producing the results accessible to all. OA enables scientists to publish relevant data and research in the preprint format. Study protocols, software, data sets, tools, and methodology used to underpin the results need to be open. Registered reports encourage the publishing of null results. Open data archiving can also increase the impact of the published article and the chances of it being reproduced.
Challenges and Benefits of Reproducible Research
The reproducibility crisis undermines the credibility of research papers and hinders any progress in the field. Incomplete reporting, small sample sizes, publishing only significant findings, and differences in methodology can make the reproduction of research challenging.
When an article proves a hypothesis, the underlying understanding is that the hypothesis stands true for all such samples/data. Open, reproducible research data will not allow p-hacking—that is, forming a hypothesis after arriving at the results.
High-profile journals overrepresent confirmatory work while neglecting null results that also provide significant information. When research is reliable, it is easier to do further studies and experiments instead of replicating until a known result is achieved. It saves time and funds that can then be diverted to other projects.
Tips to Produce Reproducible Research
- Using open source tools makes your work available to those who do not have the privilege to purchase licenses.
- Make your data adhere to FAIR principles: findable, accessible, interoperable, and reusable.
- Keep raw data separate with version control so that the original data remains unaffected.
- Organize and name your files and directories correctly so that others can use them with ease.
- Documenting through notes, comments, and audio recordings is greatly appreciated.
- Finally, publish with open access to make your work available to everyone.
The reproducibility issue has gained attention in recent years. Incentivizing research works with a focus on reproducibility, funding replication works, and publishing null results and improved data management can help decentralize science. Researchers must consider making the work reproducible as a part of their research and not something they think of later. Open access provides a platform that supports reproducible research.
The faster processes and real-time collaboration of Nvcleus’s simplified workflows enable seamless open access publishing. Experience the power of advanced open source technology on Nvcleus, and enhance your publishing efforts.
Sources
- https://doi.org/10.1038/533452a.
- https://www.linkedin.com/pulse/what-open-science-public-library-of-science-1c/.
- https://mindthegraph.com/blog/reproducibility/.
- https://litmaps.substack.com/p/the-reproducibility-crisis-isnt-new.
- https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4898932/.
- https://www.timeshighereducation.com/blog/reproducibility-research-critical-open-science-and-open-britain.
- https://www.earthdatascience.org/courses/intro-to-earth-data-science/open-reproducible-science/get-started-open-reproducible-science/.
- www.Nvcleus.com.
