- PhD Symposium.- Optimisation of Reasoning over Ontologies on Embedded Hardware for Avionics-Context Semantic-Aware to Generate Minimisation of Computation Time and Memory Footprint.- Computational Approaches for Addressing Problematic Terminology in Museum Catalogues: A Knowledge Graph of Museum Critical Cataloguing Guidelines.- PErsoNal Genome QUery IN healthcare and clinical practice (PENGQUIN).- Enhancing Hypoglycemia Prediction in Type 1 Diabetes through Semantic Knowledge Integration and Machine Learning Optimization.- Knowledge Graph Repair.- Towards an ontology of data sovereignty and ownership in cyberspace.- Personalized Query Engine Optimization for Link Traversal-based Query Processing over Structured Decentralized Environments.

- GraphWiseLearn: Personalized Learning through Semantified TEL, Leveraging QA-Enhanced LLM-generated Content .- AIREG: Enhanced Educational Recommender System with Large Language Models and Knowledge Graphs.- Explaining misleading claims using graphs of entities.- Enabling Efficient and Semantic-Aware Constraint Validation in Knowledge Graphs.- Knowledge Graph-enhanced Vision-to-Language Multimodal Models for Radiology Report Generation.- AI supported Knowledge Graph Design & Generation.- Hybridization of Description Logics and Logic Programming.- Extended best papers from the Workshops.

- Analysis of Automated Tools for FAIRness Evaluation: A Literature Perspective.- An Extended Evaluation of Single-Label Multi-Modal Field of Research Classification Using a Taxonomy-Based Metric.- Challenges and Opportunities of LLM-augmented Semantic Model Creation for Dataspaces.- Versioning Virtual Reconstruction Hypotheses: Revealing Counterfactual Trajectories of the Fallen Voussoirs of Notre-Dame de Paris using Reasoning and 2D/3D Visualization.- Designing an Ontology Network for Digital Product Passports.- Explainable Moral Values: a neuro-symbolic approach to value classification.- Static and Adaptive Planning with WoT TD by Generating Python Objects as Intermediary Representations using Large Language Models.