Governance-Ready, AI-Aware Healthcare Research Infrastructure (Quarto-Based)
This repository implements a structured, governance-ready research object for healthcare research projects using Quarto.
It provides a reproducible, navigable framework that integrates:
- A clear research lifecycle (question → protocol → data → methods → results → interpretation → reuse)
- Governance artefacts (dataset card, model card, risk register, decision log, reproducibility checklist)
- Optional AI capability reflection scaffolds
- Static, portable publication via Quarto
This is not simply a writing template.
It encodes research transparency and governance directly into project
structure.
👉 http://cloudpedagogy-research-object-demo.s3-website.eu-west-2.amazonaws.com/
This screenshot shows the fully rendered research object generated from the /example/ project in this repository.
The demo allows users to explore the complete structure of a governance-ready research object, including:
• research lifecycle documentation
• governance artefacts (dataset card, model card, risk register, decision log)
• optional AI capability reflection checkpoints
• reproducible research structure built with Quarto
The demonstration uses entirely synthetic data and represents a fictional healthcare service utilisation study.
git clone [repository-url]
cd [repository-folder]npm installnpm run devOnce running, your terminal will display a local URL (often http://localhost:5173). Open this in your browser to use the application.
npm run buildThe production build will be generated in the dist/ directory and can be deployed to any static hosting service.
- Fully local: All data remains in the user's browser
- No backend: No external API calls or database storage
- Privacy-preserving: No tracking or data exfiltration
- Suitable for use in sensitive organisational and governance contexts
Healthcare research projects are often fragmented:
- Manuscript in one place
- Code in another
- Governance documentation elsewhere
- AI usage inconsistently disclosed
This template addresses:
- Structural fragmentation
- Reactive governance
- Opaque AI use
- Reproducibility gaps
- Inconsistent documentation practices
It transforms a research project into a coherent, version-controlled research object.
- Not a data platform\
- Not a journal replacement\
- Not an AI automation system\
- Not regulatory compliance software\
- Not a learning management system
It is a lightweight infrastructure pattern for structuring and documenting research projects responsibly.
The root project contains the blank, reusable template:
- Structured content pages\
- Governance artefacts\
- AI Capability Checkpoints (optional)\
- Data documentation scaffolds\
- Deployment guidance
This is the version intended for forking and reuse.
Explore the synthetic demonstration project here:
- Browse source:
/example/
The /example/ folder contains a synthetic, fully populated healthcare
research project:
"Understanding Factors Associated with Missed Outpatient Appointments: A Synthetic Service Utilisation Study"
This example:
- Uses entirely synthetic data\
- Does not represent any real institution\
- Demonstrates governance completion\
- Demonstrates proportionate AI reflection\
- Shows how the template can be implemented end-to-end
It serves as a working demonstration of good practice.
http://cloudpedagogy-research-object-demo.s3-website.eu-west-2.amazonaws.com/
This site shows the fully rendered research object generated from the /example/ project in this repository.
The demo allows users to explore the complete structure of a governance-ready research object, including:
• research lifecycle documentation
• governance artefacts (dataset card, model card, risk register, decision log)
• optional AI capability reflection checkpoints
• reproducible research structure built with Quarto
The demonstration uses entirely synthetic data and represents a fictional healthcare service utilisation study.
This template includes optional AI Capability Checkpoints aligned to a six-domain reflection model:
- Awareness & Orientation\
- Human--AI Co-Agency\
- Applied Practice & Innovation\
- Ethics, Equity & Impact\
- Decision-Making & Governance\
- Reflection, Learning & Renewal
AI use is not required.
These sections are designed to support transparent, proportionate
documentation where AI tools are used.
Human responsibility remains central.
For a step-by-step working guide, see:
This document covers:
- Getting started\
- Completing governance artefacts\
- Using AI Capability Checkpoints (optional)\
- Rendering and exporting
- Healthcare researchers\
- Service evaluation teams\
- Applied analytics groups\
- AI-in-health projects\
- Governance-conscious research teams\
- Institutions seeking lightweight transparency structures
This project extends the CloudPedagogy ecosystem from curriculum infrastructure into research infrastructure.
It demonstrates how governance and AI capability principles can be operationalised in research practice.
This repository contains exploratory, framework-aligned tools developed for reflection, learning, and discussion.
These tools are provided as-is and are not production systems, audits, or compliance instruments. Outputs are indicative only and should be interpreted in context using professional judgement.
All applications are designed to run locally in the browser. No user data is collected, stored, or transmitted.
This repository contains open-source software released under the MIT License.
CloudPedagogy frameworks and related materials are licensed separately and are not embedded or enforced within this software.
CloudPedagogy develops open, governance-credible resources for building confident, responsible AI capability across education, research, and public service.