NExTLi is a proposed national research infrastructure, currently under review within the NWO RI programme

NExTLi

Data & FAIR

NExTLi focuses on interpretable lipid biology. That requires data that stays usable: with QC evidence, annotation confidence, and metadata that survives beyond a single paper.

FAIR is not a checkbox at the end. The NExTLi Data & Analysis Portal — built on iSODA architectural principles and supported by institutional compute and storage infrastructure (ACDC, SURF) — embeds FAIR compliance into every step of the workflow, from experimental design to data delivery and long-term preservation. The diagram below shows how data flows through the NExTLi infrastructure from generation to published, reusable outputs.

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Concept

What “FAIR” means here

  • QC evidence and method context, not just files
  • Annotation confidence metadata alongside results
  • Structured metadata using ISA framework and community standards (Lipidomics Standards Initiative)
  • Packaging designed for portal ingestion and repository deposition (e.g. MetaboLights)
NExTLi FAIR data workflow: experimental design and data generation at AUMC and MU-M4i feeds into FAIR data management via AUMC ACDC, then data models and provenance via LUMC, metadata and research objects via SURF, leading to published FAIR data and integrated analyses in Health-RI and MetaboLights
NExTLi FAIR data workflow. Experimental design, data generation, and annotation (AUMC/MU-M4i) are integrated with FAIR data management and HPC workflows via AUMC/ACDC. Data models, analysis, and provenance are handled by LUMC, with metadata and research objects stored via SURF. The endpoint is published, FAIR lipidomics data integrated with Health-RI and MetaboLights.

Core deliverables

Deliverables are workflow-dependent, but the default is: results + QC + context + provenance. Users receive structured, reproducible research objects that can be explored interactively through the NExTLi Data & Analysis Portal or accessed locally.

  • Analysis-ready tables with identifiers and annotation confidence metadata
  • QC summaries (batch structure, controls, and key checks)
  • Method and processing documentation with full provenance tracking
  • Statistical results, visualization outputs, and structured research objects

What we capture early

Most “FAIR problems” are created before measurement. Mandatory metadata completion during project intake ensures experiments are FAIR-by-design from the start.

  • Study design context (comparisons, covariates, constraints, intended outputs)
  • Sample description and handling constraints (including low-input considerations)
  • Workflow choice and QC plan (what success looks like)
  • Reporting and reuse intent (integration targets, repository deposition, embargo needs)

What you can expect

Interpretability

Results come with context: QC evidence, annotation confidence, processing documentation, and expert-supported guidance on biological interpretation.

Reusability

Datasets are structured for reanalysis, cross-study comparison, and multi-omics integration. Formats conform to community standards suitable for deposition in established repositories.

Infrastructure & preservation

Data is stored on institutional infrastructure supported by ACDC and SURF services for long-term preservation. Metadata is registered in national catalogues (FAIRDOM-SEEK, Health-RI) to support findability across Dutch and European data ecosystems.

NExTLi facilitates and encourages data sharing in accordance with FAIR principles: as open as possible, as closed as necessary. Decisions on data release, embargo periods, and access conditions remain with the data owners.

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