Method / tool

Micro-Meta App

An interactive, open-source tool for collecting microscopy metadata against the 4DN-BINA-OME tiered specifications — guiding instrument operators through required fields at acquisition time so metadata is captured before it can drift.

The problem — Microscopy metadata is most accurate at the moment of acquisition and most commonly recorded days later, from memory, in a free-text methods section. By then, the objective numerical aperture, the exact laser power, the filter set, and the pixel-size calibration have either been forgotten or reconstructed imprecisely. Retrospective metadata is not provenance — it is an approximation of provenance, and the difference is measurable in downstream reproducibility.

What it is / how it works — Micro-Meta App is an open-source, browser-deployable tool developed by Rigano and colleagues (Nature Methods, 2021) that operationalises the 4DN-BINA-OME tiered system of Microscopy Metadata specifications. It presents instrument operators with an interactive interface that walks through the exact fields required by the community spec: hardware components (objective, laser, detector, filter sets), acquisition settings (pixel size, z-step, exposure time, channel assignments), and sample context. Each field maps to the OME data model, so the output JSON can be embedded directly in an OME-NGFF store or handed to a deposition tool like the BioImage Archive. The tool was validated across 16 core facilities to produce more uniform metadata records than lab-notebook practices. It addresses both tiers of the metadata framework that Metadata & Provenance: The Run Manifest draws on: provenance metadata (MPM — how the image was made) and quality metadata (MQM — how good it is).

Where it breaks — Micro-Meta App captures what an operator tells it; it cannot infer fields from a vendor file it has not been given. If the microscope session ends before the app is run, the value is lost to memory. The practical discipline is to treat Micro-Meta App as a concurrent step at acquisition — run alongside the vendor software — not as a post-hoc documentation tool. A half-filled record is better than none, but the acquisition-level fields (pixel size, objective NA, channel identities) are the ones that feed downstream validation; incomplete there means uncomputable downstream.

Metadata captured after the session ends is reconstructed from memory, not recorded from the instrument. Run Micro-Meta App during acquisition — not at deposition — or the fields that matter most will already be uncertain.

References

Appears in these notes

  • Verification — A Pipeline You Can Re-RunVerification is the engineering discipline of making a microscopy pipeline deterministic, version-pinned, and re-executable from a provenance record. Without it, every result is a one-off, and "we changed nothing" is unprovable.
  • Every Output Should Know Where It Came FromProvenance is a property of the artifact, not the pipeline — every mask, profile, and count matrix should carry the lineage that produced it. Where verification asks whether a run reproduces, provenance asks whether a single output, found alone, can still explain itself.

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