Military-Grade · Open-Source · Modular · DDIL-Resilient Mission Application Ecosystem
OMEN (Open Mission Engine) is a government-owned, modular mission software platform that enables contested-environment aircrew operations through:
- Integrated situational awareness — blue-force, threat, airspace, and mission data fused into a single common operating picture
- Tactical moving map — aviation-optimized display with offline resilience
- Critical Abstraction Layer (CAL) — standards-based data normalization across diverse operational sources
- Deterministic evaluation — ARES-E–inspired test harnesses, DDIL simulation, and red-team pipelines
- Bounded AI/agentic support — route risk scoring, anomaly detection, and mission summarization under strict human-on-the-loop governance
- Energy-aware operation — compute budgeting, thermal management, and edge-device endurance
OMEN is not a single application. It is a mission software ecosystem.
OMEN/
├── spec.md # Full Solutions Package Specification
├── docs/ # Architecture, LOE guides, security, evaluation, deployment
├── examples/ # Plug-and-play sample adapter, plugin, and mission package
├── sdk/ # Typed interfaces, data contracts, UI components, guides
├── engine/ # Mission engine core, policy, telemetry, ARES-E & Energy hooks
├── map-app/ # Tactical moving map application
├── cal/ # Canonical data models, normalization pipelines, sync
├── adapters/ # CoT, KML, GeoJSON, NOTAM, UDL adapters
├── evaluation/ # Test harnesses, DDIL simulation, red-team scenarios
├── notebooks/ # Jupyter training manuals and field guides (all staff levels)
└── ops/ # Docker, Kubernetes, CI/CD, IaC, SBOM tooling
| LOE | Name | Directory |
|---|---|---|
| LOE 1 | Open Mission Engine and SDK | engine/ · sdk/ |
| LOE 2 | Tactical Moving Map Application | map-app/ |
| LOE 3 | Data Integration and Interoperability | cal/ · adapters/ |
| Ecosystem | Role in OMEN | Reference |
|---|---|---|
| DaScient ARES-E | Deterministic evaluation, red-teaming, HITL assurance, typed schemas | engine/ares_e/ · evaluation/ |
| DaScient Energy | Resource-constrained intelligence, energy-aware scheduling, world-sensing | engine/energy/ · ops/energy/ |
- Docker 24+ or Podman 4+
- Python 3.11+
- Node.js 20+ (for map-app and SDK)
- GNU Make
git clone https://github.com/DaScient/OMEN.git
cd OMENcat spec.md
# or open in your browser:
# https://dascient.github.io/OMENcd examples/sample-adapter
pip install -r requirements.txt
python run_adapter.pycd examples/sample-plugin
pip install -r requirements.txt
python run_plugin.pycd evaluation
pip install -r requirements.txt
pytest harnesses/ -v| Document | Description |
|---|---|
spec.md |
Full OMEN Solutions Package Specification |
docs/architecture.md |
High-level architecture and layer diagram |
docs/loe-1-engine.md |
Mission Engine and SDK detail |
docs/loe-2-moving-map.md |
Tactical Moving Map detail |
docs/loe-3-cal.md |
CAL and data integration detail |
docs/security.md |
Security controls and threat model |
docs/evaluation.md |
Evaluation framework and test philosophy |
docs/ddil-resilience.md |
DDIL design patterns and simulation guide |
docs/ai-governance.md |
AI/agentic governance policy |
docs/energy-awareness.md |
Energy-aware operation guide |
docs/ares-e-integration.md |
ARES-E integration reference |
docs/energy-integration.md |
DaScient Energy integration reference |
docs/contributing.md |
Contribution guide |
docs/deployment.md |
Deployment guide |
Plug-and-play Jupyter notebooks for all staff levels:
| Notebook | Audience | Description |
|---|---|---|
notebooks/training/01_omen_overview.ipynb |
All staff | OMEN architecture orientation |
notebooks/training/02_sdk_quickstart.ipynb |
Developers | SDK and plugin authoring quickstart |
notebooks/training/03_cal_adapters.ipynb |
Developers | CAL adapter development guide |
notebooks/training/04_evaluation_harness.ipynb |
Test engineers | Evaluation harness walkthrough |
notebooks/field-guides/fg_01_aircrew_map.ipynb |
Aircrew / operators | Tactical map field guide |
notebooks/field-guides/fg_02_ddil_ops.ipynb |
Operators | DDIL operations field guide |
notebooks/integration/ares_e_integration.ipynb |
Engineers | ARES-E integration walkthrough |
notebooks/integration/energy_integration.ipynb |
Engineers | DaScient Energy integration walkthrough |
- Mission Effectiveness First — every component improves decision quality, survivability, or mission continuity
- Open Architecture — open interfaces, open standards, government ownership
- DDIL Resilience — useful at low bandwidth, high latency, or fully disconnected
- Modular Replaceability — any component replaceable without full rewrites
- Deterministic Core, Adaptive Edge — safety-critical behavior is auditable; AI is optional and bounded
- Least-Privilege Trust — narrow, continuously enforced auth and data access
- Human-on-the-Loop — aircrew and operators retain final authority
- Energy-Aware Operation — compute efficiency, thermal, bandwidth, sustainability
- Observability by Default — telemetry, logs, traces, health as first-class features
- Community-Enabled Improvement — open feedback loops where policy permits
See docs/contributing.md for guidelines, CLA requirements, code review standards, and security disclosure procedures.
Apache 2.0 — see LICENSE
Copyright 2026. © DaScient, LLC — OMEN™ — All Rights Reserved.