\"From DataPLANT’s DataHUB to DataPUB(lication)\" officially published

Fri Jan 03 2025

A core document describing one of the central objectives of the DataPLANT consortium has been published by our partner, the University Library of Tübingen. One of the major development tasks in our project was to provide a science gateway as a technical foundation that applies software engineering-inspired approaches to data management and makes them accessible to plant researchers. The document outlines the PLANT DataHUB (HDL), which delivers various RDM workflows to support research data scientists throughout the data life cycle—from the annotation and structuring of collected data to the publication of the resulting insights.

To foster cultural change, we aim to support formal data publication with DOIs or comparable persistent resolvers, aligning with the evolving scientific landscape and advancing developments in plant research toward Open Science and Open Data. The technical platform adheres to the ARC principle of being “Immutable yet evolving.” Data publications, via domain-specific repositories or the DataPLANT ARChive, provide opportunities to publish “frozen in time” versions that are stable and citable, not limited to the end of the research process. This paper was presented at the IWSG in Tübingen in 2023.

This initiative aligns with DataPLANT’s strategy to empower users by enabling participation and establishing a clear strategy for quality assurance through automation and tooling. In the proposed second funding phase, this strategy includes expanding and automating validation processes with unit testing, ensuring no user is prevented from sharing their data while enabling collaborative improvements over time. Automation enhances data quality by ensuring metadata completeness and measurement quality, with quality control workflows tailored to specific measurements and implemented by data experts or method developers. Moreover, automatic reproduction triggers can verify long-term reproducibility.