Advancing Microbial Research Infrastructure: MibiNet's Data Management Strategies and the LichenMetaImage Collaboration

The CRC 1535 MibiNet consortium aims to enhance our understanding of microbial networks, providing insights into organelle evolution and microbiome functionality [1]. We implement effective data management strategies for consortium members by applying the FAIR principles (Findable, Accessible, Interoperable, Reusable) throughout data storage and processing workflows. A key component of our data management strategy is the Annotated Research Context (ARC) structure, developed by DataPLANT. This structure enables researchers to consolidate data, metadata, and computational workflow in a single location [2]. Enhanced by ontology-driven metadata templates and the DataHUB platform, this ARC framework ensures streamlined data sharing and interoperability within MibiNet. Integrating the eLabFTW electronic lab notebook and the eLab2ARC tool supports comprehensive experimental documentation [3,4].

The LichenMetaImage use case [5], a joint project between CRC 1535 MibiNet and the NFDIs NFDI4Microbiota, DataPLANT and NFDI4BIOIMAGE, focuses on developing standardized workflows and metadata annotations for bioimage data related to lichens and their associated microbiome. Addressing challenges of large file sizes and proprietary formats, we are creating tailored metadata templates based on REMBI [6] to meet the unique requirements of lichen bioimage. These templates, implemented in OMERO [7] and ARC structures, support comprehensive documentation of imaging data. Future plans include integrating complementary omics data, such as sequence information, to map microbial compositions and spatial distributions within lichen thalli. By enhancing metadata accessibility and usability, these initiatives improve reproducibility in microbial research, foster interdisciplinary collaboration, and advance our understanding of complex microbial ecosystems.

[1] https://www.sfb1535.hhu.de/
[2] Weil et al. (2023), The Plant Journal 116 (4), 974-988. DOI: 10.1111/tpj.16474
[3] CARPi et al. (2017), JOSS 2(12), 146, DOI:10.21105/joss.00146
[4] https://nfdi4plants.org/elab2arc/
[5] https://nfdi4microbiota.de/community/usecase.html
[6] Sarkans et al. (2021), Nat Methods 18, 1418–1422. DOI: 10.1038/s41592-021-01166-8
[7] Allan et al. (2012), Nat Methods 9, 245–253 DOI: 10.1038/nmeth.1896