Which projects fit?
Suitable for teams aligning equipment, business and operational semantics or connecting system models to graphs and AI tools. Start with one object family and a defined set of business questions.
Ontology Modeling
Give system models and operational data a shared business vocabulary
Connect MBSE, dynamic knowledge graphs and engineering AI applications.
What we provide
New Horizon models objects, properties, relationships and events in an ontology, mapping requirements, equipment, interfaces, telemetry and fault knowledge into inspectable semantics. Scoped deliverables include an ontology project, source mappings, constraint checks and graph integration examples for retrieval, analysis and agent tools.
Last updated: 2026-10-13 · New Horizon Digital Outsourcing Team
View delivery and acceptance detailsCapability Highlights
- Traceable identifiers and semantic definitions
- Separate ontology definitions from live state
- Inspectable rules and inference results
Typical deliverables
- OWL/RDF ontology project
- Source model and data field mappings
- Constraint rules and validation records
- Graph initialization and update examples
Delivery workflow
- 01 Define questions and vocabulary
- 02 Model the ontology and mappings
- 03 Integrate samples and check rules
- 04 Review and hand over the version
Frequently asked questions
How do ontologies, knowledge graphs and SysML models work together?
SysML represents system requirements, structure and behavior. An ontology defines shared domain semantics, while a knowledge graph organizes instances and relationships. Mappings must specify which properties, relationships and constraints survive conversion; export alone does not prove semantic preservation.
Can an ontology eliminate language model hallucinations?
Ontologies and rules provide a basis for retrieval, tool calls and output checks, but do not guarantee error-free answers. Validate provenance, rule coverage, reasoning paths and human review. Physical equipment control requires separate authorization and safety conditions.
Other Capabilities in This Domain
Implementation References for This Domain
Explore implementation guides and case studies to understand input requirements, technical approaches, delivered assets, and methods for evaluating outcomes.
Knowledge Guides
- How Should Multiple Product Configurations Be Delivered? Align Models, Requirements, and Verification Materials
- What Should Be Checked before Running a Behavior Model? From Initial Context to Event Records
- How Should a SysML Profile Be Customized? Define Meaning before Extending Elements
- How Should Cross-Tool Requirements Exchange Be Accepted? Track Data Loss Explicitly
Case Studies
Engineering delivery brief
What should ontology modeling deliver, and how is it accepted?
What inputs are needed?
Prepare models, vocabulary, identifiers, fields and units, relationships, data samples and business rules. Define data ownership, tool licenses, versions and the permitted scope of automated updates.
Applicability and Limits
Document search alone may not require a full ontology. Unconfirmed semantics should not be merged automatically. Exportable OWL/RDF files do not prove correct reasoning, and dynamic graphs do not replace physical validation.
What drives time and cost?
Effort depends on concept and relationship types, source systems, identifier and unit quality, mappings, update frequency and acceptance-query complexity. Validate a small slice before estimating conversion and maintenance costs.
Deliverables and acceptance
OWL/RDF ontology project
Acceptance Evidence
Import into the agreed tool, inspect types, properties, relationships and versions, and retain source-to-ontology mappings.
Constraint rules and validation records
Acceptance Evidence
Test known valid and invalid samples for missing fields, type conflicts, units and invalid references, and retain reproducible validation reports.
Graph initialization and update examples
Acceptance Evidence
Replay agreed data and verify event times, state changes, evidence paths and queries. Measure update throughput and latency separately.
Related case study
Satellite Ontology and Dynamic Knowledge Graph Design
Feasibility case study: use MBSE to align satellite, subsystem, equipment and telemetry semantics, connecting an OWL ontology to graph initialization and state updates.
Read the full case studyFurther Reading and Technical References
Related standards and technical documentation for solution selection and implementation.
Discuss Ontology Modeling Services
Describe your stage objectives and constraints (without classified details), and we will provide scope recommendations and a deliverables list.