dataverse-sync

Synchronize local research files with Harvard Dataverse datasets via API.

37|1|Updated Feb 20, 2026

Search Tags:#API #sync #research data #dataset #dataset management #dataverse

Ready to run

npx skills add https://github.com/letitbk/claude-academic-setup --skill dataverse-sync

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: dataverse-sync
Source: https://github.com/letitbk/claude-academic-setup/tree/main/skills/dataverse-sync
Command: npx skills add https://github.com/letitbk/claude-academic-setup --skill dataverse-sync

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires requests, json, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill facilitates the synchronization of local research datasets with Harvard Dataverse, enabling effortless uploading, replacing, or deleting files within a dataset.

Core Features & Use Cases

Dataset File Management: Retrieve current files, add new files, replace existing ones, or delete outdated files via Dataverse API.
Version Control: Manage dataset versions by creating drafts for updates and publishing them to the public repository.
Use Case: Researchers can automate updating their datasets with new data files without manual uploads, ensuring consistency and saving time.

Quick Start

Use the dataverse-sync skill to upload new data files to your Harvard Dataverse project and keep your dataset updated automatically.

Frequently Asked Questions about dataverse-sync

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I sync local research data with Harvard Dataverse?▼

Syncing local research data with Harvard Dataverse involves using API interactions to upload, replace, or delete dataset files automatically. This keeps your local storage and the online repository consistent without manual uploads.

Can I automate dataset file uploads to Dataverse?▼

Automating dataset file uploads to Dataverse is possible through API interactions. The system retrieves current files and adds new data files, allowing researchers to update datasets automatically and save time.

How do I manage dataset versions when updating files in Dataverse?▼

Managing dataset versions in Dataverse requires creating drafts for updates and publishing them to the public repository. This workflow ensures structured version control when you upload, replace, or delete files.

What do I need to automate Harvard Dataverse synchronization?▼

Automating Harvard Dataverse synchronization requires a Python environment with the requests and json dependencies installed. This setup enables the API interactions required for automated dataset management and version control.

What is the best way to replace or delete outdated files in a Dataverse dataset?▼

Replacing or deleting outdated files in a Dataverse dataset is best handled through automated API synchronization. This approach directly manages file replacements and deletions while maintaining data consistency across local and online repositories.