Harvard Dataverse API

SkillDatabases & data

Deposit and discover research datasets via Harvard Dataverse API

Instructions available. Your AI can read the instructions. Execution depends on the setup they require.

Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.

Then ask your AI: use the Harvard Dataverse API skill

What this skill tells your AI

The instructions your AI receives, as published by brycewang-stanford/auto-empirical-research-skills in skills/43-wentorai-research-plugins/skills/literature/fulltext/dataverse-api/SKILL.md and read by ahel’s review.

Overview

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.

API Endpoints

Base URL

https://dataverse.harvard.edu/api

Search

# 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"

Get Dataset Metadata

# 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 Files

# 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"

Query Parameters (Search)

ParameterDescriptionExample
qSearch queryq=voter+turnout
typeItem typedataset, file, dataverse
per_pageResults per page (max 1000)per_page=50
startPagination offsetstart=50
sortSort fieldname, date
orderSort orderasc, desc
fqFilter query (Solr)fq=subject_ss:"Medicine"

Response Structure

{
  "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..."
      }
    ]
  }
}

Python Usage

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)")

Other Dataverse Installations

InstallationURLFocus
Harvard Dataversedataverse.harvard.eduMulti-discipline
UNC Dataversedataverse.unc.eduSocial science
AUSSDAdata.aussda.atAustrian social science
Borealis (Canada)borealisdata.caCanadian research
DataverseNLdataverse.nlDutch research

References

Signals

GitHub stars
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Forks
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Last commit
Sep 2026
Advanced
Item type
skill
Key
dataverse-api
Source
github.com/brycewang-stanford/auto-empirical-research-skills