At GigaScience we see more and more of our published papers use computational workflows, as they provides researchers easy access to high-quality analysis methods without the requirement of computational expertise. However, systems are needed to enable the sharing of these workflows in a reusable form.

Frictionless Data improves not just machine readability of scientific articles, but also enables humans to directly interact with the data within the article itself.

GigaScience has always had a focus on reproducibility rather than subjective impact, and it can be challenging for our reviewers to judge this, especially now that more and more tools are being created – bringing data science to the masses.  This also means more efficiency and ease is required especially when multiple collaborators and contributors on a specific project are involved.

The National Academies of Sciences, Engineering, and Medicine (NASEM) hosted the two-day virtual workshop “Changing the Culture of Data Management and Sharing” on 28th-29th April 2021 to discuss the challenges and opportunities for establishing effective data management and sharing practices and exploring the question of universal availability of scientific data.

GigaScience Press and River Valley Technologies, with the help of Stencila, launch their first interactive “ Executable Research Article ” from their new scientific journal, GigaByte.

Out today in GigaScience is ShinyLearner, a new tool to make it easier to perform benchmark comparisons of classification algorithms. This tool stands out by making this process super systematic and reproducible, and despite needing to interface with many different libraries and languages it uses software containers (and a CodeOcean demo) so end users don’t need to worry about this complexity.