Table of Contents

Introduction

This handbook provides a comprehensive guide to integrating ontologies and semantic technologies into digital engineering practices. It explains how to use formal knowledge representation to enable interoperability, data integration, and computational reasoning across complex engineering systems.

This handbook is designed for PhD-level students studying digital system engineering, providing both theoretical foundations and practical implementation guidance.

Overview

The Handbook on Digital Engineering with Ontologies establishes the conceptual and technical foundation for using ontologies to enable interoperability and knowledge representation in digital engineering (DE) contexts. It introduces the Digital Engineering Framework for Integration and Interoperability (DEFII) and its implementation, the Armaments Interoperability and Integration Framework (IoIF), as the primary methodology for integrating ontologies with engineering models.

The handbook is structured into six parts, each addressing specific aspects of ontology-integrated digital engineering:

Part Primary Focus

Part I

Foundational concepts, terminology, and the DEFII framework

Part II

Mission and systems engineering methods using ontologies

Part III

Ontology development and alignment with engineering models

Part IV

Decision frameworks, digital thread impact analysis, and verification

Part V

Exercises and practical implementation guidance

Part VI

Case studies and advanced applications

The handbook emphasizes that ontologies are not just data dictionaries but formal knowledge representations that enable computational reasoning across engineering domains.

Position in Knowledge Hierarchy

Narrower concepts: - Part I (contains) - Part II (contains) - Part III (contains) - Part IV (contains) - Part V (contains)

Details

Digital Engineering Framework for Integration and Interoperability (DEFII)

The DEFII framework provides a structured approach for integrating ontologies with digital engineering models. It consists of three fundamental layers:

Layer Description

Ontology-aligned data

Foundation of the framework using ontologies like BFO and CCO to structure domain knowledge

Automated reasoning

Enables enrichment of data using axioms and rules defined in ontologies

Tool proxy interfaces

Three categories of interfaces for interacting with engineering tools: Direct, Mapping, and Specified Model Interfaces

The DEFII framework is implemented through IoIF, which uses ontology-aligned data to enable interoperability across engineering tools and models.

Ontology Alignment with Digital Engineering Models

The handbook emphasizes that ontology alignment is crucial for effective knowledge representation and interoperability in complex systems development. The process involves:

  1. Using clear and descriptive names for SysML blocks, properties, and OWL classes

  2. Applying ontology alignment principles to ensure consistency between models and ontologies

  3. Leveraging tool proxies to connect engineering models with ontology-aligned data

Avoid using vague or domain-specific terms that lack clear definitions. Every term added to an ontology should meaningfully differentiate it from other terms to ensure usability and interoperability.

Key Components of the Framework

The handbook introduces several key components that form the foundation of the ontology-integrated digital engineering approach:

Component Description

BFO (Basic Formal Ontology)

Top-level ontology providing foundational concepts for domain ontologies

CCO (Common Core Ontologies)

Mid-level ontologies serving as building blocks for domain-specific ontologies

IoIF (Armaments Interoperability and Integration Framework)

Implementation of DEFII for integrating ontologies with engineering models

AFD (Assessment Flow Diagram)

SysML-based model representing the flow of information between analysis models

SoA (System of Analysis)

The broader representation of analysis encompassing the AFD and related elements

The DEFII framework enables the "full stack" of models, from mission-level objectives to detailed engineering analysis, by providing a common semantic foundation for data exchange across the engineering lifecycle.

Ontology Modeling Principles

The handbook outlines several key principles for effective ontology development in engineering contexts:

  1. Use a top-level ontology (TLO): Align ontologies with a TLO like BFO to ensure consistency and interoperability.

  2. Create meaningful terms: Every term should have a clear definition that differentiates it from other terms.

  3. Reuse existing ontologies: Leverage established ontologies like CCO rather than creating new terms from scratch.

  4. Use standardized namespaces: Ensure coherence and compatibility with neighboring ontologies.

  5. Apply consistent naming conventions: Maintain predictability in term names to facilitate querying and usability.

Start with the existing Catapult example from the handbook to understand how to apply these principles in practice. The example demonstrates how to extend an existing model with new features using both SysML and OWL representations.

Practical applications and examples

Catapult Case Study

The Catapult example serves as a pedagogical foundation throughout the handbook, demonstrating how to:

  1. Extend a SysML model with new features (e.g., adding a "safety mechanism" to a catapult)

  2. Align the SysML model with an OWL ontology

  3. Use the Assessment Flow Diagram (AFD) to represent the flow of information between analysis models

The Catapult example demonstrates the entire workflow from mission-level objectives to detailed engineering analysis, showing how ontologies enable interoperability between different engineering domains.

IoIF Workflow Example

The IoIF workflow demonstrates how ontology-aligned data can be used to coordinate engineering analyses:

  1. Start with a SysML model containing an AFD

  2. Load ontologies into the IoIF framework

  3. Use tool proxies to exchange data between engineering tools and the ontology-aligned repository

  4. Run analyses and update the ontology-aligned data

  5. Visualize results through dashboards

graph LR A[SysML Model with AFD] --> B[IoIF Framework] B --> C[Ontology-Aligned Data] C --> D[SPARQL Queries] C --> E[Automated Reasoning] D --> F[Decision Dashboard] E --> G[Analysis Results] G --> H[Digital Thread Impact Analysis] H --> I[Updated SysML Model]

Related wiki pages

Part I
Part II
Part III
Part IV
Part V
Part VI
Ontology
Digital Engineering
MBSE
SysML
IoIF
DEFII

References

Protégé Ontology Editor
SysML v2 Specification
Basic Formal Ontology (BFO)
Common Core Ontologies (CCO)
OWL 2 Web Ontology Language
RDF Concepts and Abstract Syntax
SPARQL 1.1 Query Language
Driving Digital Engineering Integration and Interoperability Through Semantic Integration of Models with Ontologies
Systems Engineering for the Digital Age: Practitioner Perspectives

Knowledge Graph

Visualize the relationships between key concepts in the handbook

graph TD A[Handbook on Digital Engineering with Ontologies] --> B[DEFII Framework] A --> C[IoIF Implementation] B --> D[Ontology-Aligned Data] B --> E[Automated Reasoning] B --> F[Tool Proxy Interfaces] D --> G[BFO Top-Level Ontology] D --> H[CCO Mid-Level Ontologies] F --> I[Direct Interface] F --> J[Mapping Interface] F --> K[Specified Model Interface] C --> L[SysML Models] C --> M[AFD Assessment Flow Diagram] C --> N[SoA System of Analysis] L --> O[Block Definition Diagram] L --> P[Internal Block Diagram] L --> Q[Parametric Diagram] O --> R[Catapult Example] P --> S[Safety Mechanism Extension] Q --> T[Analysis Workflow]