LAMBDA-BER use cases

Six ways to make structural biology data actionable across facilities

These scenarios show how LAMBDA-BER metadata, RO-Crate packaging, local query stores, and agent-assisted workflows can turn facility outputs into reusable, federated research objects without forcing every site into one storage system.

The shared pattern

Move meaning first. Move bytes only when needed.

The use cases are not six unrelated demos. They trace one practical architecture: facilities expose typed metadata and stable file pointers; labs and compute environments ingest those records into local tables; agents use the shared schema to query, route processing, integrate results, package depositions, and decide what deserves reanalysis.

RO-Crate gives the portable graph and bundle. LAMBDA-BER gives the structural biology projection that is easy to validate, query, and join.

Facility run metadata RO-Crate portable graph Local catalog queryable tables Processing WorkflowRun trail Deposit archives + lakehouse reanalysis loop

Use-case catalogue

Start with the question you need answered

Each page is a concrete workflow sketch: who is doing the work, what metadata crosses the boundary, what the agent does, and what durable record is left behind.

End-to-end path

The architecture is visible in the workflow

1. Register

Pull a crate from a facility and record stable identifiers, sample metadata, and file locations.

2. Query

Project the graph into local tables so scientists and agents can ask operational questions.

3. Process

Route by technique and capture every computational step as explicit workflow provenance.

4. Integrate

Join outputs across techniques, facilities, archives, and local experiments.

5. Preserve

Deposit, index, and revisit results when upstream tools or references improve.

Who benefits

Same metadata, different jobs

Facility teams

Expose enough structured context for outside users to find, validate, and act on data without copying whole storage systems.

Computational biologists

Build local, queryable workspaces that preserve provenance while letting agents assemble the right files and workflows.

Data platforms

Land interoperable metadata in BRIDGE, a lakehouse, or a repository while keeping raw data federated by design.