RO-Crate Analysis and Visualisation Tools

The University of Melbourne Perpetual Calendar RO-Crate rendered as a network graph with crategraph.

ARDC Community Data Lab Phase 2: Work Package 2

Tools for analysing and visualising research data collections stored in RO-Crates.

About

RO-Crates offer a powerful format for preserving HASS and GLAM collections with curated metadata and linkage information. While existing tools focus on creating RO-Crates as archival objects, this project unlocks them for active research use.

This project develops accessible tools for researchers to:

• Analyse network relationships and metadata within and across RO-Crates
• Visualise collections interactively, both online and offline
• Understand and work with RO-Crate workflows through documentation and training

A set of RO-Crates converted from OHRM databases are available on FigShare: https://figshare.unimelb.edu.au/projects/OHRM_Upload_Project/230466

Project Goals

The project focuses on use-case driven development, prioritising specific research contexts for HASS and GLAM collections. Initial work will target:

• Visualisation of linkages between RO-Crates
• Visualisation of contents within RO-Crates

Background

This work builds on existing University of Melbourne projects and external collaborations that have developed specialised RO-Crate tools and workflows, including work derived from former Online Heritage Resource Manager projects.

Survey

We are excited to collaborate with researchers from various backgrounds. By taking this short survey, you're helping us co-design something that reflects and supports the way researchers work. We encourage you to share this survey with colleagues and research networks beyond your institution.

Feedback on WP2: working with RO Crate

Quick Start

Install crategraph from PyPI:

python -m pip install crategraph

Interactive Python shell:

python

>>> from crategraph import Crate
>>> crate = Crate("path/to/my-collection/")
>>> crate.entities
>>> crate.relationships

Jupyter notebook:

python -m pip install jupyter
jupyter notebook

Documentation

Full documentation, guides, and API reference are published at unimelbmdap.github.io/cdl2-rocrates.

• Getting Started — install, load a crate, and take a first look.
• Tutorials — task-focused guides, including Visualising a Collection, From Graph to DataFrame, and Searching a Collection. A one-page cheat sheet covers the common commands.
• Case Studies — real collections explored end to end, such as Navigating the Encyclopedia of Australian Science and the Australian Radio Talkback corpus.
• API Reference and Architecture — for extending crategraph or understanding its internals.

Development Setup

Prerequisites

• Python 3.12 or later
• uv package manager

Installation

# Clone the repository
git clone https://github.com/unimelbmdap/cdl2-rocrates.git
cd cdl2-rocrates

# Install dependencies
uv sync

# Install pre-commit hooks
uv run pre-commit install

Running Tests

uv run pytest

Code Quality

This project uses Ruff for linting and formatting, enforced via pre-commit hooks.

# Run pre-commit checks manually
uv run pre-commit run --all-files

# Run linter
uv run ruff check .

# Run formatter
uv run ruff format .

Licence

Licensed under the Apache License, Version 2.0. See the LICENSE file for the full terms.

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