Evaluation Matrix for and Collection of Training Materials for becoming a Data Steward in Bioimaging

- This is a evaluation matrix of a systematic review for training materials in the field of data stewardship in bioimaging - The table is structured in key topics (Implementation of FAIR principles in image data management, Microscopy techniques and imaging modalities, Metadata and annotations, File formats, Folder structures and naming conventions, Electronic Lab Notebooks (ELN), RDM platforms, Creation of DMPs in biological imaging, Scripting for data processing, Image data annotation workflows, Image data analysis and reproducible analysis pipelines, Virtual desktop, Public data deposition and archival, Licensing and data protection, Data standards in interdisciplinary teams, Training for PhDs, junior researchers, and young scientists) and contains identified training materials for each key topic - This table was created in the course of creating a curriculum for becoming a data steward in bioimaging.

This work outlines the knowledge and tools DaSts need to support researchers throughout the bioimaging data lifecycle toward FAIR data. It serves as a guide to becoming a DaSt in the bioimaging domain, linking to detailed training material on core competencies, essential tools and infrastructures in this field. - This table is part of an academic publication (Müller et. al. 2026, Curriculum for Bioimaging Data Stewardship: A Systematic Review of Existing Training Resources), which is linked in the metadata field "Related Identifier" of this data package.