Make your article more transparent, useful, and trustworthy by embracing research reproducibility—the documentation of research in sufficient detail so that an independent researcher could follow your outlined steps, complete the same work, and obtain the same results. Publishing reproducible research enables others to understand, learn from, and build upon your work more efficiently.
Key areas for improving the reproducibility of your article include: providing a detailed description of your research methodology; sharing your data in an online data repository; and uploading your code to an online code repository.
Consistent with its broad mission to advance technology for the benefit of humanity, IEEE is committed to the principles of open science. IEEE strongly supports the sharing of research processes, methods, data, code, and findings as openly as possible to promote collaboration, accelerate innovation, and advance scientific knowledge. IEEE likewise supports the transparent disclosure of peer review activities to ensure the quality, validity, and reliability of its scientific publications.
All IEEE authors are encouraged to share their data, code, and other research outputs to facilitate verification and reproducibility of experiments and their conclusions.
IEEE is committed to continuously improving the research infrastructure in its fields of interest to enable, facilitate, and foster adoption of these open science principles.
Improve the discoverability of your data by hosting it in an easily accessible repository such as IEEE DataPort™, an online data repository of datasets and data analysis tools. IEEE DataPort accepts all types of datasets up to 2TB and provides a Digital Object Identifier (DOI) for easy citation. Standard (i.e., non-Open Access) datasets can be uploaded for free at IEEE DataPort. Articles in the IEEE Xplore® Digital Library with linked data in IEEE DataPort will have a Code & Datasets tab where readers can link to the dataset from the article.
IEEE also recommends figshare, Zenodo, and Dryad as alternative data repositories.
Help other researchers view and run your code with Code Ocean, a cloud-based computational reproducibility platform that allows code to be stored, shared, and run in the cloud. Anyone can run code posted to Code Ocean, modify it, and test the modifications, without changing the original code.
When uploading to Code Ocean, you will be asked to create a “compute capsule.” The compute capsule creates a home for the code to live in and is the key to having your code work for everyone who runs it from Code Ocean.
Authors who have published with IEEE in the past five years can upload their code to Code Ocean and link it to the article published in IEEE Xplore. Articles with linked code have a Code & Datasets tab where readers can run the code without installing or downloading anything.
Follow these steps to upload your code and link it to your IEEE Xplore article.
In November 2016, IEEE held its first workshop on the future of research curation and research reproducibility. This meeting brought together stakeholders including researchers, funders, and leading science, technology, engineering, and mathematics (STEM) publishers. Since then, IEEE has been committed to providing resources for authors to be aware of and follow best practices of reproducible research.
The two short video tutorials below provide more in-depth information about research reproducibility.
