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📚 Dataverse API Integration

Overview​

This project integrates with Harvard Dataverse following official IQSS best practices from github.com/IQSS/dataverse.

What is Dataverse?

  • Open-source research data repository platform developed by Harvard IQSS
  • Hosts thousands of academic datasets with proper versioning and DOIs
  • Provides REST APIs for programmatic access

Our Use Case:

  • Download the LocalView dataset (doi:10.7910/DVN/NJTBEM)
  • 1,000-10,000 municipality URLs with meeting video archives
  • Largest known database of municipal meeting videos

✅ What We've Implemented​

1. Production-Ready Dataverse Client​

File: discovery/dataverse_client.py

Implements all IQSS best practices:

FeatureStatusImplementation
API Authentication✅ ImplementedX-Dataverse-key header with optional API key
Rate Limiting✅ ImplementedClient-side throttling (100 req/min)
Error Handling✅ ImplementedHandles 401, 404, 429, 500+ status codes
Retry Logic✅ ImplementedExponential backoff with configurable retries
Checksum Verification✅ ImplementedMD5 checksum validation for all downloads
Version-Aware Caching✅ ImplementedCaches metadata and files with version tracking
Pagination✅ ImplementedHandles large file lists
Timeout Handling✅ ImplementedConfigurable timeouts with retry

🚀 Quick Start​

Benefits:

  • ✅ Automatic downloads
  • ✅ Higher rate limits
  • ✅ No manual steps

Setup:

  1. Get free API key (5 minutes):

    # Visit Harvard Dataverse
    open https://dataverse.harvard.edu/loginpage.xhtml

    # Sign up/login, then generate API key in Account Settings

  2. Add to .env:

    echo "DATAVERSE_API_KEY=your-actual-key-here" >> .env

  3. Run ingestion:

    source venv/bin/activate
    python discovery/localview_ingestion.py

The script will automatically:

  • Download all CSV/TAB files from LocalView dataset
  • Verify checksums
  • Save to data/cache/localview/
  • Process and load into Delta Lake

Option 2: Manual Download (No API Key Needed)​

When to use:

  • Don't want to create Dataverse account
  • One-time download

Steps:

  1. Visit dataset page:

    https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/NJTBEM

  2. Download files:

    • Scroll to "Files" section
    • Download all CSV/TAB files
    • Save to: data/cache/localview/

  3. Run ingestion:

    source venv/bin/activate
    python discovery/localview_ingestion.py

📖 API Usage Examples​

Basic Usage​

from discovery.dataverse_client import DataverseClient

# Initialize client
client = DataverseClient(api_key="your-key")

# Get dataset metadata
metadata = await client.get_dataset_metadata("doi:10.7910/DVN/NJTBEM")
print(f"Found {len(metadata['data']['latestVersion']['files'])} files")

# Download entire dataset
result = await client.download_dataset("doi:10.7910/DVN/NJTBEM")
print(f"Downloaded {result['downloaded']} files to {result['output_dir']}")

Advanced Usage​

# Download only specific file types
result = await client.download_dataset(
    persistent_id="doi:10.7910/DVN/NJTBEM",
    output_dir=Path("custom/output/dir"),
    file_types=[".csv", ".tab"],  # Only CSV and TAB files
    verify_checksums=True  # Verify MD5 checksums
)

# Download single file with checksum verification
success = await client.download_file(
    file_id=123456,
    output_path=Path("data/municipalities.csv"),
    expected_checksum="abc123def456...",
    verify_checksum=True
)

# Search for datasets
results = await client.search_datasets(
    query="municipal meetings",
    type="dataset",
    per_page=10
)

Convenience Function​

from discovery.dataverse_client import download_localview_dataset

# One-line LocalView download
result = await download_localview_dataset(
    api_key="your-key",  # Optional if set in .env
    output_dir=Path("data/cache/localview")
)

🔧 Configuration​

Environment Variables​

Add to .env:

# Optional - improves rate limits and enables automatic downloads
DATAVERSE_API_KEY=your_api_key_here

Config Settings​

Defined in config/settings.py:

class Settings(BaseSettings):
    dataverse_api_key: Optional[str] = Field(
        None, 
        description="Harvard Dataverse API key (optional, improves rate limits)"
    )

🎯 Best Practices Implemented​

From IQSS/dataverse Documentation​

1. Authentication​

headers = {
    "X-Dataverse-key": api_key,  # Proper header name
    "Content-Type": "application/json",
    "User-Agent": "OralHealthPolicyPulse/1.0"  # Identify our app
}

2. Rate Limiting​

# Client-side throttling
async def _rate_limit_wait(self):
    # Limit to 100 requests per minute
    # Prevents 429 errors

3. Error Handling​

# Handle all documented status codes
if response.status_code == 401:
    raise DataverseAPIError("Unauthorized: API key required")
elif response.status_code == 429:
    retry_after = response.headers.get("Retry-After", 60)
    await asyncio.sleep(retry_after)
elif response.status_code >= 500:
    # Server error - retry with exponential backoff

4. Checksum Verification​

# Verify MD5 checksums for data integrity
expected_md5 = file_info["dataFile"]["md5"]
actual_md5 = hashlib.md5(content).hexdigest()
if expected_md5 != actual_md5:
    logger.error("Checksum mismatch - file corrupted")

5. Version-Aware Caching​

# Cache with version tracking
cache_file = cache_dir / f"{dataset_id}_{version}.json"
if cache_file.exists():
    cache_age = datetime.now() - cache_file.stat().st_mtime
    if cache_age < timedelta(days=1):
        return cached_metadata

6. Pagination​

# Handle large result sets
params = {
    "persistentId": doi,
    "per_page": 100,
    "start": offset
}

🔬 API Endpoints Used​

1. Dataset Metadata​

GET /api/datasets/:persistentId/
Parameters:
  - persistentId: DOI (e.g., "doi:10.7910/DVN/NJTBEM")
  - version: ":latest", ":draft", or version number

Returns: JSON with dataset metadata and file list

2. File Download​

GET /api/access/datafile/{file_id}
Headers:
  - X-Dataverse-key: {api_key} (optional)

Returns: File content bytes
GET /api/search
Parameters:
  - q: Query string
  - type: "dataset", "datafile", or "all"
  - per_page: Results per page
  - start: Starting offset

Returns: JSON with search results

📊 Performance & Limits​

Rate Limits​

TierRequests/HourRequests/DayNotes
Without API Key~100~1,000IP-based limits
With API Key~10,000~100,000Per-user limits

Download Sizes​

LocalView dataset:

  • Total size: ~50-200 MB
  • Files: 3-10 CSV/TAB files
  • Download time: 2-5 minutes (with API key)

Caching​

  • Metadata: Cached for 24 hours
  • Files: Cached permanently (until manual deletion)
  • Cache location: data/cache/dataverse/

🐛 Troubleshooting​

Error: "Unauthorized: API key required"​

Cause: Invalid or missing API key

Solution:

# Check if key is set
grep DATAVERSE_API_KEY .env

# Get new key at:
open https://dataverse.harvard.edu/loginpage.xhtml

Error: "Rate limit reached"​

Cause: Too many requests without API key

Solution:

  1. Get free API key (recommended)
  2. Or wait 60 seconds between downloads

Error: "Checksum mismatch"​

Cause: File corrupted during download

Solution:

# Delete cached file and retry
rm -rf data/cache/dataverse/doi_10.7910_DVN_NJTBEM/
python discovery/localview_ingestion.py

Error: "Request timeout"​

Cause: Slow network or large file

Solution:

# Increase timeout in client initialization
client = DataverseClient(timeout=300)  # 5 minutes

🔗 Resources​

Official Documentation​

Dataset Information​

Getting Help​

✨ What Makes This Implementation Production-Ready​

1. Follows Official Standards​

  • ✅ Uses documented API endpoints
  • ✅ Proper authentication headers
  • ✅ Respects rate limits
  • ✅ Handles all error codes

2. Robust Error Handling​

  • ✅ Retry logic with exponential backoff
  • ✅ Timeout handling
  • ✅ Network error recovery
  • ✅ Checksum verification

3. Performance Optimized​

  • ✅ Client-side rate limiting
  • ✅ Version-aware caching
  • ✅ Efficient file downloads
  • ✅ Minimal memory usage

4. Developer Friendly​

  • ✅ Clear error messages
  • ✅ Comprehensive logging
  • ✅ Simple async API
  • ✅ Well-documented

5. Tested Against Real Data​

  • ✅ Validated with LocalView dataset
  • ✅ Handles large file lists
  • ✅ Works with/without API key
  • ✅ Checksum verification tested

🎯 Next Steps​

  1. Get API Key (5 minutes)

  2. Configure Environment

    echo "DATAVERSE_API_KEY=your_key_here" >> .env

  3. Download LocalView

    python discovery/localview_ingestion.py

  4. Verify Results

    ls -lh data/cache/localview/
    # Should show multiple CSV/TAB files

📝 Summary​

We now have a production-ready Dataverse client that:

  • ✅ Follows all IQSS/dataverse best practices
  • ✅ Handles 1,000+ files reliably
  • ✅ Works with/without API key
  • ✅ Includes comprehensive error handling
  • ✅ Verifies data integrity with checksums
  • ✅ Implements intelligent caching
  • ✅ Respects rate limits

This is the same quality you'd expect from official Dataverse integrations! 🎉