Conference Information

KEOD 2026: International Conference on Knowledge Engineering and Ontology Development

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KEOD
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Submission Date:
2026-07-03 Extended
Notification Date:
2026-07-17
Conference Date:
2026-10-28
Location:
Angers, France
Years:
18
ICORE: C   Viewed: 18735   Tracked: 0   Attend: 0

Conference Partner Index (CP-I)

52.6 / 100
Ranked #1,059 of 5,651 conferences · Top 19%

#53 of 253 in Information Systems & Web #94 of 735 in Artificial Intelligence & Machine Learning

Academic recognition (35%)
58
Submission selectivity (20%) No data - scored at the neutral baseline of 50 —
Editions held (20%)
79
Community attention (10%)
12
Public record completeness (15%)
35

Inputs used: Listed as ICORE C · Editions on record: 18 · Researchers who opened this page in the past 24 months: 4

Missing from the public record: Historical acceptance rates (+4.5) · Past editions (+3.0) · Best-paper records (+2.3)
Organizers can add these from this page after claiming the conference; scores are recomputed nightly. How to raise this score

Confidence 80% - the share of the score backed by observed data rather than the neutral baseline. How this score is calculated · Browse the ranking · Algorithm version 1.1 · Computed 2026-09-05

Call For Papers

KEOD 2026 (International Conference on Knowledge Engineering and Ontology Development) is a ICORE C conference held in Angers, France on 2026-10-28. The paper submission deadline is 2026-07-03 (extended). Acceptance notifications are sent on 2026-07-17.

SCOPE Knowledge Engineering (KE) refers to the technical, scientific, and social aspects involved in building, maintaining, and utilizing knowledge-based systems. As a multidisciplinary field, KE draws upon methodologies from artificial intelligence (AI), databases, expert systems, decision support systems, and information systems, with strong ties to software engineering principles. KE also intersects with disciplines like logic, cognitive science, and socio-cognitive engineering. In recent years, the integration of Large Language Models (LLMs) has opened new pathways in ontology development, enabling automated extraction, refinement, and evolution of ontologies. Additionally, the rise of Low-code and No-code Platforms empowers non-experts to participate in ontology engineering, broadening accessibility and fostering innovation. Ontology Development (OD) focuses on building reusable semantic structures such as vocabularies, glossaries, and formal ontologies that specify types of entities and relationships within a domain. These semantic structures are increasingly central to applications like knowledge graphs, digital twins, explainable AI (XAI), and cybersecurity frameworks, where ontologies enhance data integration, decision-making, and system transparency. Current applications of KE and OD include sustainable AI solutions, semantic interoperability in IoT, natural language processing (NLP), and enterprise engineering. Ontologies now play a crucial role in ensuring ethical AI development by mitigating bias and enhancing transparency. The KEOD conference aims to be a major meeting point for researchers and practitioners interested in methodologies and technologies related to Knowledge Engineering and Ontology Development. It encourages the exploration of cutting-edge topics such as LLM-based Ontology Development, Ontology-driven Digital Twins, and Ontology-enhanced Low-code Platforms, fostering dialogue and innovation across academic and industrial spheres. CONFERENCE TOPICS Knowledge Engineering Ontology Engineering Knowledge Acquisition Knowledge Representation Ontologies and Knowledge Graphs Domain Ontologies Ontology Tools Ontology Quality Assurance Ontology Sharing and Reuse Ontology Matching and Alignment Integration and Interoperability LLM-based Ontology Development Semantic Web Ontologies in Low-code and No-code Platforms Natural Language Processing Automated Ontology Learning and Evolution Explainable Artificial Intelligence (XAI) in Ontology Development Applications and Case-Studies Ontologies in Industry Domain Analysis and Modeling Enterprise Engineering Enterprise Ontology Knowledge Graphs and Graph Neural Networks (GNNs) Ontology-driven Digital Twins Reference Models Semantic Interoperability in IoT and Cyber-Physical Systems
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