Enhancements to the GigaScience Integrated Data & Research Object Publishing Pipeline

In the era of computation and data driven research, traditional methods of disseminating research are no longer fit-for-purpose. New approaches for disseminating data, methods and results are required to maximize knowledge discovery. As datasets get larger and more challenging to disseminate, one approach is to focus more on the compute and interactive research objects such as containers and virtual machines. Publishing more technically challenging and dynamic parts of the research cycle will require more transparent and interactive approaches to review, annotate, and credit the hard work of those assessing them, particularly to avoid the growing challenges of the replication crisis. GigaScience is an open-access, open-data journal tailored for the era of large-scale biological data. Using the data handling infrastructure of the genomics center BGI, GigaScience links standard manuscript publication with an integrated database (GigaDB) that hosts all associated data and provides additional analysis tools and computing resources. In addition, the supporting workflows and methods are also integrated. GigaDB has released many new and previously unpublished datasets and data types, and the latest version has a number of new and improved features. Along with a raft of major under-the-bonnet changes to the data structure, submission wizard, a new search function and results display, and the integration of the Hypothes.is web-annotation tools have all been implemented. Web forms integrate the manuscript and data peer review process with Publons, linking and crediting the peer reviews with DataCite DOIs. Protocols.io is also being merged with the data curation process to streamline the process for authors to enter their methodologies in the collaborative protocol-centered repository. Other “executable” research objects such as workflows, virtual machines, docker containers and software snapshots from several GigaScience articles have been archived and shared in the most open, reproducible, transparent and usable formats possible.