Templates for best practice metadata annotation in plant sciences - Enhancing FAIRness of data through DataPLANT's metadata tools

Comprehensive annotation of data with metadata is crucial to ensure findability and reusability of data in line with the FAIR principles. Multiple research communities and data repositories have defined checklists of metadata that should be provided for a specific research domain or data type. Keeping an overview of current standards can be an overwhelming task for researchers. As the German national research data infrastructure (NFDI) for plants, one major aim of DataPLANT [1] is to facilitate the provision of detailed, precise and reusable metadata with a focus on plant sciences. To address this, the annotation tool Swate (Swate Workflow Annotation Tool for Excel) was developed [2], which is available as an Excel-add-in, a standalone web-tool and is integrated into other DataPLANT software. Swate facilitates creating ISA (Investigation Study Assay, [3])-based annotation tables with ontology terms that are accessible within the tool. Within Swate about 50 pre-defined, curated templates are available that harmonize the metadata annotation for diverse use cases [4]. These include minimum information standards focused on different plant sciences domains like MIAPPE (Minimum Information about a Plant Phenotyping Experiment, [5]) or MIMS (Minimum Information about a Metagenome Sequence [6]), checklists of data repositories like ENA (European Nucleotide Archive) or MetaboLights and commonly used protocols like omics-related assays, plant growth, phenotyping or imaging. Templates are designed to represent ISA-processes and annotate them with ontology terms. Prefilled example values and use of ontology terms facilitate the interpretation of templates [7] and allow the automated suggestion of suitable ontology terms as entries. Templates for repository checklists are regularly updated to match the current requirements. Using these templates will ensure that the mandatory metadata for submission is covered. Filled out annotation tables can be validated against repository requirements through automated processes that are currently being established to receive feedback on missing metadata. In addition to using templates as provided, they can be extended, combined, shortened or otherwise modified according to user needs. Based on community requirements, additional templates continue to be added. While the DataPLANT-provided templates are focused on applicability in plant sciences, different communities can add their own templates for other research domains or institute-specific standard operating procedures through well-documented GitHub workflows. To assist searching the template database, templates are associated with relevant tags. Additionally, a metadata quiz is provided in the DataPLANT knowledge base as a starting point for getting an overview about available standards, repositories and Swate templates depending on the selected organism and data type. Researchers are thus supported with metadata annotation throughout their whole project. By facilitating and harmonizing metadata annotation for researchers, DataPLANT therefore contributes to the availability of more completely and uniformly annotated data.