Structured Resource Names
Every record has a stable, versioned address that still resolves in ten years.
urn:osa:antibodies.example.org:ab:AB-04412@3Private beta · onboarding archives nowDeploy a scientific data bank
Deploy a scientific data bank
in minutes
Define the shape and semantics of your data. You get a database that validates every deposit, gives every record a permanent address, and answers queries from people and agents.
antibodies.example.org
$ amacrin deploy --archive antibodies --domain antibodies.example.org→ validating data model antibody-discovery-v2 … ok→ building 3 hooks, 1 ingester … 4/4 succeeded→ publishing bld_8f3a91c2✓ archive live · 3 features per record https://antibodies.example.org
The problemEvery field wants a PDB.
Every field wants a PDB.
Almost none get one.
The PDB works because deposition is structured, validation is mandatory, and every record is addressable. Building that takes a decade and a consortium.
- 01
Nobody can find it
A DOI on a ZIP is not a queryable dataset. Reuse depends on guessing what the columns mean.
- 02
Quality is assumed, not checked
Without validation at deposition, missing metadata and broken ontology terms surface years later, in someone else's analysis.
- 03
Unfit for training
Training on public data means months of scraping and normalising, with no record of what was processed by which version of which script.
- 04
The infrastructure outlives the grant
Someone has to keep the server up after the postdoc leaves. Most portals are gone within three years.
Open source
We built OSA. We host it too.
Open Science Archive is an open source scientific data platform: deposition, validation, records, search and export. Amacrin hosts OSA archives, so you can run a data bank for your field without operating one.
Nothing about your archive is proprietary. Export everything at any time, or take the node in-house and run it yourself.
The platform
One data model, the whole pipeline
You write the data model: record schemas, validation checks, and hooks that compute derived features. Amacrin runs everything downstream of it: deposition, builds, hosting, search and APIs.
- 01DepositA wizard generated from your schema. Depositors sign in with ORCID.
- 02ValidateYour checks run on every submission. Failures stay private to the depositor.
- 03Compute featuresHooks derive embeddings, QC metrics, predictions, versioned per build.
- 04Publish recordsA record page per SRN, plus semantic search across every schema.
- 05Serve and federateREST, bulk export, MCP. Other nodes can mirror or fork with provenance intact.
Your domain, your rules
Public reads by default; you decide who can deposit and who curates. ORCID all the way down, so no new accounts.
antibodies.example.orgNothing to operate
Compute, database, registry and TLS are ours to keep up. Push a data model and export everything whenever you want.
tls · backups · upgradesAgent-native
Readable by people and AI
Every archive publishes a skill file describing what it holds and an MCP server exposing search, tables and export. Both regenerate on every build, so an agent that queried you last week picks up today's schemas and records without a client update.
- Semantic search, not keyword guessing
- Structured filters over typed fields and features
- Bulk exports pinned to a build digest
antibodies.example.org/SKILL.mdpublished
--- name: osa-data-antibodies-example-org description: Antibody sequences with binding affinity, expression yield and target metadata. Use when answering questions like: Which antibodies against PD-1 have sub-nanomolar Kd? What VH gene families target HER2? --- ## Datasets | Schema | Records | |---------------------------|---------| | antibody-sequence@2.1.0 | 7,204 | | binding-assay@1.3.0 | 3,118 |
mcp.json6 tools live
{
"mcpServers": {
"antibodies": {
"type": "http",
"url": "https://antibodies.example.org/mcp"
}
}
}Take the slice you need. Give it a permanent name.
Most work on an archive starts by narrowing it: the records that pass QC, the assays from one platform, everything since the last release. A cut is that subset, exported with its features computed and given a name that resolves to exactly these rows.
amacrin cut antibodies \ --schema antibody-sequence@2.1.0 \ --where 'target = "PD-1" and qc.status = "pass"' \ --features affinity_kd_nM, expression_yield, embedding \ --format parquet
idaffinity_kd_nMexpression_yieldembedding
AB-00417@20.42118
AB-01186@11.3796
AB-02940@30.09142
AB-04412@32.8571
AB-07356@10.61205
⋯
Filter on real fields
Query typed metadata instead of parsing filenames. If a field is in the schema you can filter on it, and everything that matched passed the same checks.
Features already computed
Embeddings, QC metrics and predictions come out as columns, versioned with the build that produced them. No preprocessing pipeline to rebuild.
A freeze everyone shares
Publish a cut as the official release and every member works from the same rows. Re-cut later and diff the two to see what changed.
Provenance
Track provenance on every row
Rows in a cut aren't anonymous. Open one and you get the record behind it: the specimen, the lab, the instrument, the licence, and what changed since.
cut 2f9a80urn:osa:antibodies.example.org:ab:AB-04412@3 opened
idaffinity_kd_nMexpression_yieldembedding
AB-01186@11.3796
AB-02940@30.09142
AB-04412@32.8571
AB-07356@10.61205
AB-09103@11.02133
NOTEThe same lookup works from the API and from an agent, so a model can check what it's looking at.
- Records are versioned, never replacedA correction publishes a new version and keeps the old one addressable. An analysis that used @1 still resolves to exactly what it saw.
- Corrections find your cutsWhen a depositor revises a record, every cut that contained it is flagged. You find out which models were trained on the old value.
- Licence terms stay attachedWhat you are allowed to do with a record travels with it through export, mirroring and forking.
Who runs archives
Collaborate with confidence
Your data model is the contract between member sites. Validation makes it concrete, and every site's contribution stays attributed.
A quality home for your public data
A hosted archive is the product you were going to build in-house anyway. Validation your funders can point to, and no infrastructure staff on headcount.
Get the deliverable you paid for
Agree the data model before the work starts and every CRO batch arrives validated against it. The deliverable lands queryable instead of as spreadsheets you reconcile after the contract closes.
Publish the data your field never got
Write the data model once and every future deposit inherits validation, search and a permanent address.
Start with one dataset, or bring the whole field
We're onboarding archives one field at a time. Leave your email and what you'd deposit, and we'll get you a slot.
Running a consortium or a large release? Talk to us directly.