Complete Technical Specification with 4-Phase Implementation Architecture
The WIA-MEDICAL-RESEARCH-DATA standard provides a comprehensive framework for managing, sharing, and preserving medical research data throughout its lifecycle. Built on FAIR principles and the WIA 4-phase architecture (Data, API, Protocol, Integration), this standard enables interoperable, ethical, and sustainable research data management.
Guided by the principle of 弘益人間 (Hongik Ingan) - "Benefit All Humanity" - this standard aims to maximize the value of research investments by making data findable, accessible, interoperable, and reusable while protecting participant privacy and respecting researcher contributions.
The WIA-MEDICAL-RESEARCH-DATA standard implements the WIA 4-phase architecture pattern:
The 4-phase architecture separates concerns into distinct layers: Phase 1 (Data) defines dataset and metadata models aligned with DataCite and domain standards; Phase 2 (API) provides RESTful endpoints for data discovery, access, and management; Phase 3 (Protocol) enables communication between repositories, registries, and analysis platforms; Phase 4 (Integration) connects with institutional systems, federated networks, and preservation infrastructure.
| Phase | Name | Purpose | Components |
|---|---|---|---|
| Phase 1 | Data Layer | Information modeling | Dataset, Metadata, Provenance models |
| Phase 2 | API Layer | Programmatic access | Discovery, Access, Management APIs |
| Phase 3 | Protocol Layer | System communication | OAI-PMH, SWORD, Signposting |
| Phase 4 | Integration Layer | External connectivity | ORCID, DOI, Federated networks |
The Data Layer defines core information models for research data management:
{
"id": "doi:10.5281/zenodo.123456",
"identifier": [{
"identifierType": "DOI",
"identifier": "10.5281/zenodo.123456"
}],
"title": "Diabetes Biomarker Study Dataset",
"creator": [{
"name": "Smith, John",
"nameIdentifier": "0000-0001-2345-6789",
"affiliation": "University Medical Center"
}],
"subject": [{
"subject": "Diabetes Mellitus",
"subjectScheme": "MeSH",
"schemeURI": "http://id.nlm.nih.gov/mesh"
}],
"description": "Clinical and biomarker data from...",
"publisher": "Zenodo",
"publicationYear": "2024",
"resourceType": "Dataset",
"version": "2.0",
"rights": [{
"rights": "Creative Commons Zero v1.0",
"rightsURI": "https://creativecommons.org/publicdomain/zero/1.0/"
}],
"relatedIdentifier": [{
"relatedIdentifierType": "DOI",
"relatedIdentifier": "10.1234/journal.12345",
"relationType": "IsSupplementTo"
}]
}
{
"schemaVersion": "4.4",
"descriptive": {
"title": "string",
"creators": ["CreatorObject"],
"subjects": ["SubjectObject"],
"description": "string",
"keywords": ["string"]
},
"administrative": {
"publisher": "string",
"publicationYear": "YYYY",
"rights": "LicenseObject",
"accessLevel": "open | registered | controlled | closed"
},
"technical": {
"format": ["string"],
"size": "bytes",
"checksum": "MD5/SHA-256"
},
"provenance": {
"created": "datetime",
"modified": "datetime",
"methodology": "string",
"processing": ["ProcessingStep"]
}
}
{
"requestId": "UUID",
"datasetId": "DOI",
"requestor": {
"name": "string",
"orcid": "0000-0001-2345-6789",
"institution": "string",
"email": "string"
},
"purpose": "string",
"researchPlan": "string",
"ethicsApproval": {
"hasApproval": "boolean",
"approvalNumber": "string",
"approvalDocument": "URL"
},
"dataUseAgreement": {
"accepted": "boolean",
"version": "string",
"acceptedDate": "datetime"
},
"status": "submitted | under_review | approved | denied",
"requestDate": "datetime"
}
The API Layer provides programmatic access to research data infrastructure:
| Category | Endpoint | Method | Description |
|---|---|---|---|
| Discovery | /api/v1/datasets | GET | Search datasets |
| /api/v1/datasets/{id} | GET | Get dataset metadata | |
| /api/v1/datasets/{id}/files | GET | List dataset files | |
| Access | /api/v1/access/request | POST | Submit access request |
| /api/v1/access/{id}/status | GET | Check request status | |
| /api/v1/datasets/{id}/download | GET | Download dataset | |
| Deposit | /api/v1/deposits | POST | Create new deposit |
| /api/v1/deposits/{id}/files | POST | Upload files | |
| /api/v1/deposits/{id}/publish | POST | Publish deposit | |
| Metrics | /api/v1/datasets/{id}/metrics | GET | Usage statistics |
| /api/v1/datasets/{id}/citations | GET | Citation tracking |
APIs use OAuth 2.0 with ORCID integration for researcher authentication. Scopes include: deposit:create, deposit:update, access:request, access:download, admin:review. Machine-to-machine access uses API keys with rate limiting.
The Protocol Layer enables interoperability between repositories and systems:
| Protocol | Purpose | Standard |
|---|---|---|
| OAI-PMH | Metadata harvesting | Open Archives Initiative Protocol |
| SWORD | Repository deposit | Simple Web-service Offering Repository Deposit |
| Signposting | Resource discovery | FAIR Signposting Profile |
| ResourceSync | Content synchronization | ANSI/NISO Z39.99 |
| DataCite | DOI registration | DataCite Metadata Schema 4.4 |
The Integration Layer connects research data infrastructure with the broader ecosystem:
| System | Integration | Data Exchanged |
|---|---|---|
| ORCID | OAuth, API | Researcher identity, works |
| DOI/DataCite | API, metadata | Identifiers, citations |
| Federated Networks | Distributed queries | Discovery, aggregate stats |
| Institutional Systems | SSO, storage | Authentication, files |
| Preservation | Archival protocols | AIPs, checksums |
The standard ensures FAIR compliance through specific mechanisms:
| Principle | Implementation |
|---|---|
| F1-F4 | DOIs, DataCite metadata, OAI-PMH harvesting, Google Dataset Search |
| A1-A2 | HTTPS, OAuth, persistent metadata, access statements |
| I1-I3 | Standard schemas, ontologies, qualified references |
| R1-R1.3 | Rich metadata, machine-readable licenses, provenance, community standards |
The WIA-MEDICAL-RESEARCH-DATA standard embodies the principle of benefiting all humanity by maximizing the value of research investments. Every dataset represents countless hours of work and participant contributions. By making this data FAIR—Findable, Accessible, Interoperable, and Reusable—we multiply its impact, enable validation, and ensure that research benefits everyone. Open science accelerates discovery and translates findings to improve human health worldwide.
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