Open-Ontological-Peer-Review-OOPR
Abstract
OOPR Tool v1.0-alpha Open Ontological Peer Review — Reproducible AI-Based Peer Review for Ontological Framework What is OOPR? OOPR enables rigorous, reproducible peer review of ontological and foundational frameworks using AI reviewers. It formalizes review as an open, transparent, and repeatable procedure. The Problem: Traditional peer review fails systematically with pre-physical models, cross-disciplinary frameworks, and paradigm-questioning work. The Solution: OOPR separates review methodology from disciplinary authority through explicit criteria, transparent prompts, and full reproducibility. Quick Start Use in Claude Artifacts (Recommended) Go to claude.ai Ask Claude: "Create the OOPR Tool v1.0-alpha as an artifact" Paste the React code from src/oopr-tool.jsx Start reviewing immediately Local Development bash git clone https://github.com/Christianfwb/oopr-tool.git cd oopr-tool npm install npm start 7 Review Axes OOPR evaluates frameworks along seven rigorous dimensions: A. Axiomatic Clarity - Are foundational assumptions explicit and non-circular? B. Internal Consistency - Are there contradictions or undefined behaviors? C. Logical Derivation - Do conclusions follow necessarily from premises? D. Conceptual Precision - Are key terms unambiguous and operationalizable? E. Model Scope & Boundaries - What does it explain? Where does it stop? F. Falsifiability & Kill-Test - What experiment would prove it wrong? G. Terminological Economy - Are new terms necessary or just renamings? Key Features ✅ Queue-Based Reviews - Run all 7 axes automatically in sequence ✅ Stop Control - Abort reviews mid-process if needed ✅ Dual Export - JSON snapshots (scientific) + Markdown reports (human-readable) ✅ Full Reproducibility - Every review includes prompts, versions, and metadata How to Use Enter Your Framework - Paste your ontological model with axioms, principles, and definitions Choose Review Mode - "Run Missing" (skip completed) or "Re-run All" (fresh start) Start Review - AI analyzes each axis with brutal honesty Export Results - Download JSON for reproducibility or copy Markdown for documentation Philosophy "Do not ask whether a model is correct. Ask whether it is coherent, explicit, and inspectable." OOPR is not about declaring truth—it's about making review transparent, reproducible, and honest. ∞ − 1 = you: AI reviewers are finite agents, not omniscient judges. They serve understanding and dialogue, not verdicts. Current Limitations (Alpha) ⚠️ Use in trusted environments only: API calls made directly from frontend (no backend proxy) No rate limit handling or automatic retry No persistence between sessions Best for: Claude artifacts, local testing, research use Roadmap v1.0-alpha (Current) ✅ 7 review axes, queue system, exports v2.0 (Next) 🔨 Serverless backend with secure API handling 🔨 Rate limit detection and retry logic 🔨 Public deployment ready v3.0 (Future) 💭 Meta-review synthesis across all axes 💭 Multi-AI comparison (Claude vs GPT vs Gemini) 💭 Review evolution tracking Citation bibtex @software{berrang2025oopr, author = {Berrang, Christian}, title = {OOPR: Open Ontological Peer Review Protocol}, year = {2025}, version = {1.0-alpha}, url = {https://github.com/Christianfwb/oopr-tool} } Contributing OOPR is an open protocol. Contributions welcome: Code: Backend implementation, UI/UX improvements, new review axes Testing: Bug reports, diverse framework testing Documentation: Examples, tutorials, translations Research: Compare with human review, develop meta-review algorithms See ROADMAP.md for detailed plans. Contact 📧 Email: christianfwb@gmail.com 🔗 GitHub: github.com/Christianfwb License MIT License - See LICENSE file for details.
Fields of Study & Subjects
Publishing and Scholarly Communication
Academic Writing and Publishing
Academic Publishing and Open Access
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 17 January 2026