rohub
Deposit research objects and add semantic annotations to the RO-Hub portal using the rohub library.
Best use case
rohub is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Deposit research objects and add semantic annotations to the RO-Hub portal using the rohub library.
Teams using rohub should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/rohub/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How rohub Compares
| Feature / Agent | rohub | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Deposit research objects and add semantic annotations to the RO-Hub portal using the rohub library.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# ROHub Skill The **ROHub** skill enables the Croissant Toolkit to deposit research data and metadata into the **RO-Hub** portal (https://rohub.org). It handles the creation of Research Objects (ROs) and the addition of semantic triples for rich provenance and discoverability. ## 🌟 Key Features 1. **RO Creation**: Programmatically create new Research Objects with titles, descriptions, and research areas. 2. **RO Loading**: Access and update existing Research Objects using their persistent identifiers (DOIs/UUIDs). 3. **Semantic Annotations**: Add structured triples (Subject-Predicate-Object) to research objects to describe variables, spatial coverage, and temporal coverage. 4. **Integration**: Harmonizes with the `RO-Crate Expert` and `Croissant Expert` to translate machine-readable metadata into RO-Hub semantic structures. 5. **Authentication**: Securely logs in to the RO-Hub API using environment variables. ## 🛠️ Configuration The following environment variables are required for authentication: - `ROHUB_USER`: Your RO-Hub username (e.g., your email). - `ROHUB_PASSWORD`: Your RO-Hub password. ## 🚀 Usage ### Deposit a new Research Object ```bash python3 .gemini/skills/rohub/scripts/deposit.py --title "Arctic Radioisotopes" --description "Sea surface observations" --areas "Radiobiology" ``` ### Add annotations from a JSON-LD file (e.g., Croissant) ```bash python3 .gemini/skills/rohub/scripts/deposit.py --id "ea792c69-9037-4d06-84a8-6fded7356e12" --metadata path/to/croissant.jsonld ``` ### Add annotations from a local metadata file ```bash python3 .gemini/skills/rohub/scripts/deposit.py --id "85d38a45-d0cc-4269-9ca6-44d71b0c6ef7" --metadata path/to/metadata.jsonld ``` ## ⚙️ Service Details - **API Endpoint**: https://api.rohub.org/ - **Library**: `rohub` (python package)
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