SAGE 2026: Semantic Architectures for Governance and Explainability is a workshop co-located with SEMANTiCS 2026. The workshop focuses on semantic architectures that make AI systems more governed, explainable, auditable, and evidence-driven.

The rapid development of machine learning and large language models has created powerful AI systems, but many remain difficult to audit, explain, and align with governance requirements. SAGE 2026 addresses this gap by bringing together researchers and practitioners working on knowledge graphs, ontologies, semantic reasoning, provenance, constraints, explainable AI, and hybrid symbolic–neural approaches.

The workshop aims to explore how semantic technologies can support trustworthy AI systems through explicit representation, validation, traceability, policy alignment, and explainable reasoning. It will provide a forum for discussing architectural patterns, evaluation methods, practical deployments, and future community artefacts such as shared tasks or benchmarks.

Submission Guidelines

All papers must be original and not simultaneously submitted to another journal or conference. The following paper categories are welcome.

• Full papers describing mature research contributions, technical approaches, architectures, frameworks, evaluations, or case studies related to semantic architectures for governance and explainability.
• Short papers / position papers describing emerging ideas, ongoing work, conceptual frameworks, challenges, or research directions.
• Posters describing practical tools, prototypes, datasets, applications, or early-stage implementations relevant to the workshop themes.

Submissions should follow the format and length requirements provided by SEMANTiCS 2026. All submissions will be peer-reviewed by the Program Committee based on relevance, originality, technical quality, clarity, and potential to stimulate discussion.

Accepted papers will be presented during the workshop and included in the workshop proceedings, subject to the conference proceedings requirements.

List of Topics

Topics of interest include, but are not limited to:

• Semantic architectures for governed AI systems
• Knowledge graphs for AI governance and compliance
• Ontologies for explainable and trustworthy AI
• Provenance-aware inference and reasoning
• Constraint validation using SHACL or related approaches
• Policy-based knowledge graphs
• Machine-actionable governance frameworks
• Semantic reasoning architectures
• Hybrid symbolic–neural reasoning
• LLM and knowledge graph integration for governed AI
• Explainability through knowledge graphs and semantic models
• Traceability, auditability, and evidence-based AI pipelines
• Causal reasoning and semantic representations
• Evaluation beyond predictive accuracy
• Metrics for evidence quality, provenance completeness, robustness, and policy compliance
• Semantic interoperability in data spaces and regulated domains
• Industrial deployments of governed semantic systems
• Semantic technologies for healthcare, finance, public administration, construction, sustainability, and other high-stakes domains
• Benchmarks and shared tasks for governance-aware semantic AI

Committees

Program Committee

• Anuoluwapo Adewuyi, Birmingham City University, UK
• Aliyuda Ali, Sheffield Hallam University, UK
• Sondess Missaoui, University of the West of England, UK
• Takwa Omrani, University of Sfax, Tunisia
• Aliyu Sani Sambo, University of Wales Trinity Saint David, UK
• Parnia Samimi, Birmingham City University, UK

Organizing Committee

• Amna Dridi, Birmingham City University, UK
• Edlira Vakaj, Birmingham City University, UK
• Cecilia Zanni-Merk, INSA Rouen Normandie, France
• Mohamed Ragab, Birmingham City University, UK

Contact

All questions about submissions should be emailed to amna.dridi@bcu.ac.uk