skills/literature/fulltext/dataverse-api/SKILL.md
Deposit and discover research datasets via Harvard Dataverse API
npx skillsauth add wentorai/research-plugins dataverse-apiInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Dataverse is an open-source research data repository platform developed by Harvard IQSS, hosting 150K+ datasets across 80+ installations worldwide. The Harvard Dataverse alone has 130K+ datasets covering social science, natural science, and humanities. The API supports search, metadata retrieval, file download, and dataset deposit. Free, no authentication for read access.
https://dataverse.harvard.edu/api
# Search datasets
curl "https://dataverse.harvard.edu/api/search?q=climate+change&type=dataset&per_page=20"
# Search files within datasets
curl "https://dataverse.harvard.edu/api/search?q=temperature+data&type=file&per_page=20"
# Filter by subject
curl "https://dataverse.harvard.edu/api/search?q=survey+data&type=dataset&\
fq=subject_ss:\"Social Sciences\""
# Filter by publication date
curl "https://dataverse.harvard.edu/api/search?q=genomics&type=dataset&\
fq=dateSort:[2024-01-01T00:00:00Z TO *]"
# Sort by relevance or date
curl "https://dataverse.harvard.edu/api/search?q=machine+learning&type=dataset&\
sort=date&order=desc"
# By persistent ID (DOI)
curl "https://dataverse.harvard.edu/api/datasets/:persistentId/?persistentId=doi:10.7910/DVN/EXAMPLE"
# By dataset ID
curl "https://dataverse.harvard.edu/api/datasets/12345"
# Get dataset versions
curl "https://dataverse.harvard.edu/api/datasets/:persistentId/versions?persistentId=doi:10.7910/DVN/EXAMPLE"
# Download a specific file by ID
curl -O "https://dataverse.harvard.edu/api/access/datafile/67890"
# Download with original format
curl -O "https://dataverse.harvard.edu/api/access/datafile/67890?format=original"
# Download all files in a dataset (as zip)
curl -O "https://dataverse.harvard.edu/api/access/dataset/:persistentId/?persistentId=doi:10.7910/DVN/EXAMPLE"
| Parameter | Description | Example |
|-----------|-------------|---------|
| q | Search query | q=voter+turnout |
| type | Item type | dataset, file, dataverse |
| per_page | Results per page (max 1000) | per_page=50 |
| start | Pagination offset | start=50 |
| sort | Sort field | name, date |
| order | Sort order | asc, desc |
| fq | Filter query (Solr) | fq=subject_ss:"Medicine" |
{
"status": "OK",
"data": {
"q": "climate change",
"total_count": 2450,
"items": [
{
"name": "Global Temperature Dataset 2024",
"type": "dataset",
"url": "https://doi.org/10.7910/DVN/EXAMPLE",
"global_id": "doi:10.7910/DVN/EXAMPLE",
"description": "Monthly global temperature anomalies...",
"published_at": "2024-03-15",
"publisher": "Harvard Dataverse",
"subjects": ["Earth and Environmental Sciences"],
"fileCount": 12,
"citation": "Smith, J. (2024). Global Temperature Dataset..."
}
]
}
}
import requests
BASE_URL = "https://dataverse.harvard.edu/api"
def search_datasets(query: str, per_page: int = 20,
subject: str = None) -> list:
"""Search Harvard Dataverse for datasets."""
params = {
"q": query,
"type": "dataset",
"per_page": per_page,
"sort": "date",
"order": "desc",
}
if subject:
params["fq"] = f'subject_ss:"{subject}"'
resp = requests.get(f"{BASE_URL}/search", params=params)
resp.raise_for_status()
data = resp.json()
results = []
for item in data.get("data", {}).get("items", []):
results.append({
"name": item.get("name"),
"doi": item.get("global_id"),
"description": item.get("description", "")[:300],
"published": item.get("published_at"),
"subjects": item.get("subjects", []),
"files": item.get("fileCount", 0),
"url": item.get("url"),
})
return results
def get_dataset_files(doi: str) -> list:
"""List files in a dataset."""
resp = requests.get(
f"{BASE_URL}/datasets/:persistentId/",
params={"persistentId": doi},
)
resp.raise_for_status()
data = resp.json().get("data", {})
files = []
version = data.get("latestVersion", {})
for f in version.get("files", []):
df = f.get("dataFile", {})
files.append({
"id": df.get("id"),
"filename": df.get("filename"),
"size": df.get("filesize"),
"content_type": df.get("contentType"),
"md5": df.get("md5"),
})
return files
def download_file(file_id: int, output_path: str):
"""Download a file from Dataverse."""
resp = requests.get(
f"{BASE_URL}/access/datafile/{file_id}",
stream=True,
)
resp.raise_for_status()
with open(output_path, "wb") as f:
for chunk in resp.iter_content(chunk_size=8192):
f.write(chunk)
# Example: find social science datasets
datasets = search_datasets("income inequality",
subject="Social Sciences")
for ds in datasets:
print(f"[{ds['published']}] {ds['name']} ({ds['files']} files)")
print(f" DOI: {ds['doi']}")
# Example: list files in a dataset
# files = get_dataset_files("doi:10.7910/DVN/EXAMPLE")
# for f in files:
# print(f" {f['filename']} ({f['size']} bytes)")
| Installation | URL | Focus | |-------------|-----|-------| | Harvard Dataverse | dataverse.harvard.edu | Multi-discipline | | UNC Dataverse | dataverse.unc.edu | Social science | | AUSSDA | data.aussda.at | Austrian social science | | Borealis (Canada) | borealisdata.ca | Canadian research | | DataverseNL | dataverse.nl | Dutch research |
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