Overview - ISO/IEC 5392:2024 (Information technology - Artificial intelligence - Reference architecture of knowledge engineering)
ISO/IEC 5392:2024 defines a reference architecture for knowledge engineering (KE) in artificial intelligence. The standard standardizes KE roles, stakeholder activities, constructional layers, components and their relationships from both systemic user and functional views. It also provides a common KE vocabulary and organizes KE concerns such as safety, reliability, availability, bias reduction and responsibility. ISO/IEC 5392 is intended to guide the design, integration and governance of knowledge-driven AI systems.
Key topics and technical coverage
The standard addresses practical architectural and technical themes, including:
- KE stakeholder roles - data supplier, fundamental technology supplier, algorithm supplier, system coordinator, knowledge service provider, knowledge applier and ecosystem partners.
- User and functional views - clear separation of user concerns and functional architecture to support interoperability and integration.
- Constructional layers and components - KE infrastructure, construction, platform and application layers, plus multi-layer functions.
- KE distribution architecture - support for distributed systems and semantic web services-based deployment.
- Core KE technologies - knowledge representation, knowledge modelling, acquisition, storage, fusion, computing, visualization, maintenance and exchange.
- Enabling technologies & infrastructure - machine learning, natural language processing, speech processing, big data and cloud computing.
- Quality and governance concerns - safety, security, reliability, availability, construction quality, responsibility and bias mitigation.
- Informative annexes with examples: fundamental KE tools, specifications related to KE, typical KE application characteristics, KE life cycle and guidance on solution architectures (including integration with ISO/IEC/IEEE 42010).
The standard does not prescribe proprietary implementation details but provides a reference architecture and vocabulary to align implementations.
Practical applications and who should use it
ISO/IEC 5392 is useful for organizations building or integrating knowledge-driven AI systems across industries such as finance, healthcare, transportation, manufacturing, legal services and media. Typical applications include fraud detection, intelligent diagnostics, recommendation engines, case-based prediction, remote equipment maintenance and knowledge service platforms.
Primary users:
- KE system architects and solution architects
- AI/knowledge engineers and data scientists
- Platform and tool vendors (KE platforms, semantic web services)
- System integrators and DevOps/cloud teams
- Compliance, risk and governance professionals
- Procurement teams specifying KE requirements
Related standards and keywords
Related standards and technologies cited include semantic web standards (RDF, RDFS, OWL, SPARQL) and systems engineering guidance such as ISO/IEC/IEEE 42010. Keywords for SEO: ISO/IEC 5392:2024, knowledge engineering, reference architecture, AI, knowledge representation, semantic web, RDF, OWL, SPARQL, machine learning, NLP, cloud computing, big data.
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