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This work aims to demonstrate how to manage and structure complex datasets in plant sciences using the ARC framework.

Integrating cross-omics research through FAIR Digital Objects with DataPLANT

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This work aims to demonstrate how to manage and structure complex datasets in plant sciences using the ARC framework.
Developed an annotated research context (ARC) to manage barley single-cell RNA sequencing and spatial transcriptomics data.
Captured experimental metadata in ISA tables with ontology annotations for machine readability.
Wrapped computational analyses as common workflow language (CWL) scripts for reproducibility and reusability.
Utilizing ARC enhances the FAIRness of complex datasets, improving data interoperability.
Standardized CWL workflows allow easy parameter variations and results tracing without manual editing.
The integration of spatial and single-cell data improves comparative analyses across heterogeneous datasets.

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Randomized trial integrates spatial transcriptomics with single-cell RNA sequencing, highlighting improved FAIR data management and reusability.

Dörpholz et al. (2026) studied this question.

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Randomized trial integrates spatial transcriptomics with single-cell RNA sequencing, highlighting improved FAIR data management and reusability.