🔴FAIR Workflow Roadmap

FAIR Workflow Roadmap

FAIR Workflow Roadmap

Stage	Goal	Recommended Tools / Resources	Notes / Examples
1. Plan	Define how data will be managed before collection begins	DMP Tools: DMPonline, DMPTool, Argos Policies: UCPH Research Data Policy, Horizon Europe DMP guidelines Identifiers: ORCID, ROR	Create a Data Management Plan (DMP) that describes data formats, metadata standards, storage, access control, and sharing strategy. Ensure alignment with FAIR Principles and funder mandates.
2. Collect	Acquire raw experimental data with proper structure & metadata	Acquisition tools: Microscope vendor software + Bio-Formats for conversion Metadata standards: OME (bioimaging), MIAME (microarrays), MIABIS (biobanking), REMBI (bioimaging metadata)	Capture primary metadata at the point of collection (instrument type, conditions, sample info). Use controlled vocabularies/ontologies (e.g., OBO Foundry, EDAM).
3. Store	Ensure secure storage, versioning, and metadata capture during the project	Institutional storage: OMERO (images), ERDA (UCPH), Dataverse, CKAN File formats: OME-TIFF, OME-Zarr, HDF5 ELNs: eLabFTW, Labguru	Store data in open formats with metadata. Use OME-Zarr for scalable N-D imaging. Document workflows in ELN systems. Maintain access control and backups.
4. Publish	Deposit datasets in repositories with persistent identifiers	Repositories: BioImage Archive, IDR, EMPIAR (bioimaging); GEO, PRIDE, ENA (omics); Zenodo, Figshare (general OA) Persistent IDs: DOIs via DataCite/CrossRef	Deposit data in trusted repositories to comply with FAIR and Open Access mandates. Datasets receive DOIs for citation and linking to publications.
5. Share	Make data discoverable and accessible for the community	Registries: FAIRsharing.org, re3data, OpenAIRE Policy frameworks: EOSC, GO FAIR, RDA, CODATA	Use metadata-rich records so data can be indexed in registries. Share under licenses (CC-BY, CC0) unless restricted. FAIR allows controlled access (e.g., dbGaP for genomic data).
6. Reuse	Enable reproducibility, secondary analysis, and integration	Tools: Fiji, napari, QuPath, ilastik, 3D Slicer, Galaxy Imaging Citation systems: ORCID (authors), ROR (institutions), RRID (resources) Impact tracking: Altmetric, OpenAlex	Reuse is enabled by machine-actionable metadata and open formats. Reused data should be cited properly (dataset DOI). Adoption tracked via citations, reanalysis, or policy uptake.

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Key Insights for Life Sciences & Bioimaging

• Planning & metadata are the foundations of FAIR. Without capturing metadata at collection, downstream FAIRification is much harder.

• Bioimaging-specific standards: OME-TIFF/OME-Zarr for formats, REMBI for metadata.

• Infrastructure integration: Use OMERO for lab-scale storage and management and BioImage Archive / IDR / EMPIAR for long-term FAIR publication.

• Reuse is maximized when datasets are linked across identifiers: dataset DOI ↔ publication DOI ↔ ORCID ↔ ROR ↔ RRID.

• FAIR ≠ Open: Controlled-access data can still be FAIR if metadata is discoverable.