Bio-DID-Sequencer

Bio-DID-Seq is a GDPR compliant Decentralized Identifier (DID) system designed for research data, integrating with Dataverse and powered by AI agents.

System Overview

Bio-DID-Seq provides a robust, decentralized approach to managing identifiers for research data. By implementing the W3C DID specification and integrating with existing persistent identifier infrastructures (like DOI and Handle), it offers a sustainable and user centric solution for the research community.

Core Components

1. Layered Architecture

Bio-DID-Seq implements a 5 layer architecture:

Storage Layer

• IPFS Cluster: Provides redundant, decentralized storage for research data
• Content Addressing: All data is referenced by its cryptographic hash
• Private IPFS Network: Ensures data security while maintaining decentralization

Identity Layer

• W3C DID Implementation: Creates and manages decentralized identifiers
• Dilithium5 Signatures: Post quantum cryptographic security for DIDs
• DID Resolution: Resolves DID documents from the decentralized network

Authorization Layer

• UCAN Integration: User Controlled Authorization Network for capability based security
• Delegated Permissions: Allows controlled sharing of data access
• GDPR Compliance: Built in privacy controls and user data ownership

Application Layer

• Actix Web API: High performance web service endpoints
• Async Processing: Efficient handling of compute intensive operations
• Rate Limiting: Protection against abuse and DoS attacks

Integration Layer

• BioAgents Connector: Integration with AI powered data processing
• Dataverse Adapter: Seamless connection with Harvard Dataverse
• DOI & Handle Bridge: Interoperability with existing identifier systems

2. Key System Entities

DID Document

The core data structure representing a decentralized identifier for research data. Each DID document includes:

{
  "@context": [
    "https://www.w3.org/ns/did/v1",
    "https://w3id.org/security/suites/ed25519-2020/v1",
    "https://w3id.org/biodata/v1"
  ],
  "id": "did:bio:123456789abcdefghi",
  "controller": ["did:key:z6MkhaXgBZDvotDkL5257faiztiGiC2QtKLGpbnnEGta2doK"],
  "verificationMethod": [
    {
      "id": "did:bio:123456789abcdefghi#keys-1",
      "type": "Ed25519VerificationKey2020",
      "controller": "did:bio:123456789abcdefghi",
      "publicKeyMultibase": "z6MkhaXgBZDvotDkL5257faiztiGiC2QtKLGpbnnEGta2doK"
    }
  ],
  "authentication": ["did:bio:123456789abcdefghi#keys-1"],
  "service": [
    {
      "id": "did:bio:123456789abcdefghi#storage",
      "type": "IPFSStorage",
      "serviceEndpoint": "https://ipfs.bio-did-seq.example/api"
    }
  ],
  "metadata": {
    "title": "CRISPR-Cas9 Gene Editing Dataset",
    "researchers": [
      {
        "name": "Jane Smith",
        "orcid": "0000-0001-2345-6789",
        "role": "Principal Investigator"
      }
    ],
    "keywords": ["CRISPR", "gene editing", "genomics"],
    "dataverse_link": "https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/EXAMPLE"
  }
}

BioAgents

AI agents that provide enhanced functionality for biological data:

• Metadata Extraction: Automatically extracts metadata from research papers
• Entity Recognition: Identifies biological entities (genes, proteins, diseases)
• Knowledge Graph Generation: Creates semantic networks of biological relationships
• Semantic Search: Enables discovery across biological datasets

UCAN Token

Capability-based security tokens that provide decentralized authorization:

{
  "header": {
    "alg": "EdDSA",
    "typ": "JWT"
  },
  "payload": {
    "iss": "did:key:z6MkhaXgBZDvotDkL5257faiztiGiC2QtKLGpbnnEGta2doK",
    "aud": "did:key:z6MkgYGF3tLg4MzGCLjkpkzYZqhrMkWGBMPXATFksYp1PxJh",
    "nbf": 1617228000,
    "exp": 1617314400,
    "att": [
      {
        "with": {"scheme": "did", "hierPart": "bio:123456789abcdefghi", "parameters": {}},
        "can": "biodata/read"
      }
    ]
  },
  "signature": "..."
}

System Workflows

1. DID Creation and Registration

2. BioAgents Processing

3. UCAN Authorization Flow

Technical Specifications

API Endpoints

Endpoint	Method	Description
/api/did	POST	Create a new DID
/api/did/{id}	GET	Retrieve a DID document
/api/did/{id}	PUT	Update a DID document
/api/did/resolve/{id}	GET	Resolve and validate a DID
/api/did/dataverse/link	POST	Link DID to Dataverse DOI
/api/bioagents/process	POST	Process paper via BioAgents
/api/bioagents/status/{task_id}	GET	Check processing status
/api/bioagents/metadata/{task_id}	GET	Get extracted metadata
/api/bioagents/search	GET	Search biological entities
/api/bioagents/knowledge-graph/{cid}	POST	Generate knowledge graph
/api/dataverse/dataset	POST	Create dataset in Dataverse
/api/dataverse/dataset/file	POST	Upload file to Dataverse
/api/dataverse/dataset/publish	POST	Publish dataset in Dataverse

Database Schema

-- DID Documents table
CREATE TABLE did_documents (
    id BIGINT PRIMARY KEY AUTO_INCREMENT,
    did VARCHAR(100) NOT NULL UNIQUE,
    cid VARCHAR(100) NOT NULL,
    user_id BIGINT NOT NULL,
    created_at TIMESTAMP NOT NULL,
    updated_at TIMESTAMP NOT NULL,
    dataverse_doi VARCHAR(255),
    FOREIGN KEY (user_id) REFERENCES users(id)
);

-- UCAN Tokens table
CREATE TABLE ucan_tokens (
    id BIGINT PRIMARY KEY AUTO_INCREMENT,
    user_id BIGINT NOT NULL,
    token TEXT NOT NULL,
    audience_did VARCHAR(255) NOT NULL,
    issued_at TIMESTAMP NOT NULL,
    expires_at TIMESTAMP NOT NULL,
    revoked BOOLEAN DEFAULT FALSE,
    revoked_at TIMESTAMP NULL,
    delegated_from VARCHAR(255) NULL,
    FOREIGN KEY (user_id) REFERENCES users(id)
);

-- BioAgents Processing Tasks
CREATE TABLE bioagent_tasks (
    id BIGINT PRIMARY KEY AUTO_INCREMENT,
    task_id VARCHAR(100) NOT NULL UNIQUE,
    user_id BIGINT NOT NULL,
    cid VARCHAR(100) NOT NULL,
    status VARCHAR(20) NOT NULL,
    progress FLOAT DEFAULT 0.0,
    result_cid VARCHAR(100),
    created_at TIMESTAMP NOT NULL,
    completed_at TIMESTAMP NULL,
    FOREIGN KEY (user_id) REFERENCES users(id)
);

Security Considerations

GDPR Compliance

The system is designed with privacy as a core principle:

• Data Minimization: Only essential data is collected
• User Control: Researchers maintain control over their data
• Right to be Forgotten: DIDs can be deactivated/deleted
• Transparency: Clear audit trails for data access
• Consent Management: Explicit permission required for data sharing

Decentralized Security

Unlike traditional centralized systems:

• No Single Point of Failure: Distributed architecture
• Capability Based Security: Fine grained access control with UCAN
• Tamper Evident Storage: Content addressing ensures data integrity
• Decentralized Identity: No central authority for identity management

Future Enhancements

1. Enhanced AI Capabilities: Expand BioAgents functionality with specialized models for different biological domains
2. Federated UCAN Network: Establish cross institutional trust networks for research collaboration
3. Blockchain Anchoring: Timestamp DID operations for non repudiation and audit trails
4. Verifiable Credentials: Implement W3C VCs for attesting research data properties
5. Smart Contract Integration: Programmatic data access control and licensing