rohub

Deposit research objects and add semantic annotations to the RO-Hub portal using the rohub library.

7 stars

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

$curl -o ~/.claude/skills/rohub/SKILL.md --create-dirs "https://raw.githubusercontent.com/codata/croissant-toolkit/main/.gemini/skills/rohub/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/rohub/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How rohub Compares

Feature / AgentrohubStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/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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