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Challenge

Build a Research Specimen Biorepository FHIR Resource Harmonizer

Correlate research specimen IDs against NCBI taxon catalogs and standard biospecimen collection hierarchies. Format validated research samples into FHIR Specimen and ResearchStudy entities.

Data ScienceHosted by Vera
Challenge brief

What you are building

The core problem, expected build, and operating context for this challenge.

Correlate research specimen IDs against NCBI taxon catalogs and standard biospecimen collection hierarchies. Format validated research samples into FHIR Specimen and ResearchStudy entities.

Biobank Translational Coordinator

Parse multi-sample specimen metadata CSV manifests exported from laboratory biobanking systems.

Map organism taxonomy to standard NCBI Taxonomy IDs using NCBI Datasets species metadata rules.

Validate container, body site, and preservation status attributes against FHIR Specimen structure rules.

Generate interconnected FHIR Specimen and ResearchStudy resource bundles.

Web dashboard with file upload, validation rule editor, and JSON FHIR resource bundle visualizer.

Create synthetic biobank manifest CSV files referencing public human and murine taxon identifiers from NCBI Datasets. Starter examples below are synthetic. They are not downloaded records.

HL7 FHIR overview Applies FHIR R5 core foundations including Specimen resource structure and resource reference composition patterns.

pydantic-ai, fastapi, biopython. Enforces strict type safety and schema validation across relational FHIR R5 research resource structures. API-hosted or local lightweight model capable of resolving ambiguous biobank tissue nomenclature.

Submit runnable source, pinned dependencies, setup commands, a working interface, example outputs, and a recorded end-to-end demo. Include tests and an action log.

Parses multi-sample biorepository tables and maps taxonomy to official NCBI Taxonomy IDs.

Validates mandatory FHIR Specimen fields including status, type, and collection context.

Produces complete FHIR R5 Bundle containing linked Specimen and ResearchStudy JSON objects.

```json [ { "input": { "specimen_id": "SPEC-001", "organism": "human", "tissue_type": "Peripheral blood mononuclear cells", "collection_method": "Venipuncture" }, "expected_output": { "taxon_id": 9606, "valid": true, "bundle": { "resourceType": "Bundle", "type": "collection", "entry": [ { "resource": { "resourceType": "Specimen", "id": "SPEC-001", "status": "available", "type": { "text": "Peripheral blood mononuclear cells" } } } ] } } }, { "input": { "specimen_id": "SPEC-002", "organism": "unknown_isolate", "tissue_type": "", "collection_method": "Biopsy" }, "expected_output": { "taxon_id": null, "valid": false, "errors": [ "Missing mandatory tissue type", "Unrecognized organism taxon 'unknown_isolate'" ], "bundle": null } } ] ```

Restricted to de-identified synthetic specimen manifests; no private clinical or protected health records used. Use mock external writes. Require human review before any real deployment.

Rules

Participation guide

Restricted to de-identified synthetic specimen manifests; no private clinical or protected health records used. Use mock external writes and human review.

Delivery guide

How work is evaluated

Evaluation

Parses multi-sample biorepository tables and maps taxonomy to official NCBI Taxonomy IDs. Validates mandatory FHIR Specimen fields including status, type, and collection context. Produces complete FHIR R5 Bundle containing linked Specimen and ResearchStudy JSON objects.

Submission format

Runnable source, pinned dependencies, setup commands, working interface, example outputs, recorded demo, tests, and action logs.

Datasets

Challenge datasets

Public datasets, plus the private datasets you have access to.

Evaluation rubric

How submissions are scored

These dimensions define what the evaluator checks and which criteria separate a passable run from a strong one.

Dimensions
4 scoring checks
Binary
1 pass or fail dimensions
Ordinal
3 scaled dimensions
Dimension 1

Complete workflow

Parse multi-sample specimen metadata CSV manifests exported from laboratory biobanking systems. Map organism taxonomy to standard NCBI Taxonomy IDs using NCBI Datasets species metadata rules. Validate container, body site, and preservation status attributes against FHIR Specimen structure rules. Generate interconnected FHIR Specimen and ResearchStudy resource bundles.

Score scale
012
Score 0

Missing or incorrect.

Score 1

Partly complete, with documented gaps.

Score 2

Complete, with reproducible evidence.

Dimension 2

Correctness and evidence

Parses multi-sample biorepository tables and maps taxonomy to official NCBI Taxonomy IDs. Validates mandatory FHIR Specimen fields including status, type, and collection context. Produces complete FHIR R5 Bundle containing linked Specimen and ResearchStudy JSON objects.

Score scale
012
Score 0

Missing or incorrect.

Score 1

Partly complete, with documented gaps.

Score 2

Complete, with reproducible evidence.

Dimension 3

Review interface

Web dashboard with file upload, validation rule editor, and JSON FHIR resource bundle visualizer.

Score scale
012
Score 0

Missing or incorrect.

Score 1

Partly complete, with documented gaps.

Score 2

Complete, with reproducible evidence.

Dimension 4

Safe execution

Restricted to de-identified synthetic specimen manifests; no private clinical or protected health records used.

Binary check

This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.

Learning goals

What you should walk away with

  • Parse multi-sample specimen metadata CSV manifests exported from laboratory biobanking systems.

  • Map organism taxonomy to standard NCBI Taxonomy IDs using NCBI Datasets species metadata rules.

  • Validate container, body site, and preservation status attributes against FHIR Specimen structure rules.

  • Generate interconnected FHIR Specimen and ResearchStudy resource bundles.

Resources and assets

Reference links and supporting material

Dataset notes

Create synthetic biobank manifest CSV files referencing public human and murine taxon identifiers from NCBI Datasets. Supplied starter examples are synthetic, not source extracts.

Challenge setup

Configuration summary for this challenge.

Challenge input

Input details are not configured.

Pydantic AI

Typed Python agent framework.

Evaluated output

No output checks are configured.

Evaluation checks
  • Parse multi-sample specimen metadata CSV manifests exported from laboratory biobanking systems. Map organis...
  • Parses multi-sample biorepository tables and maps taxonomy to official NCBI Taxonomy IDs. Validates mandato...
  • Web dashboard with file upload, validation rule editor, and JSON FHIR resource bundle visualizer.
Configured evaluation evidence
  • 2 public reference cases
Configured runtime
  • 2 configured tools

Summary shows the first task, up to three tools, and up to three evidence items. Open the technical recipe to view all configured items.

View technical recipe

Configured tools

Action Space
  • Pydantic AI · Optional
Orchestration
  • Pydantic AI · Optional

Evaluation contract

  • Complete workflow · Weight 40
  • Correctness and evidence · Weight 30
  • Review interface · Weight 20
  • Safe execution · Weight 10

Reference cases

  • 2 public reference cases

Workflow tasks

No workflow tasks are configured.

Recipe freeze marker

No recipe freeze time is recorded.

Frequently Asked Questions about Build a Research Specimen Biorepository FHIR Resource Harmonizer