About MEDI
International Conference on Model and Data Engineering (MEDI)
The 15th International Conference on Model and Data Engineering (MEDI 2026) will take place at Neapolis University Pafos in Pafos, Cyprus. Cyprus is a place where centuries-old history blends seamlessly with contemporary advancements. MEDI 2026 provides a special chance to engage with state-of-the-art research in model and data engineering while experiencing the island's rich cultural and historical backdrop. The conference seeks to unite researchers, professionals, and industry experts from across the globe to present new discoveries, examine emerging developments, and encourage collaboration in the areas of model and data engineering. We welcome submissions of high-quality research papers, industry case studies, and forward-looking contributions that advance both the theoretical and practical aspects of these domains.
Areas of interest for MEDI 2026 include, but are not limited to:
Artificial Intelligence (AI)
• Modelling approaches for Generative AI
• Modelling techniques for Large Language Models
• Models supporting Explainable AI
Modelling and Model Engineering
• Modelling languages and relevant standards
• Modelling in software engineering and complex systems
• Formal methods, including analysis, verification, and validation
• Model-based testing and performance evaluation
• Ontology-driven modelling
• Heterogeneous modelling, model integration, interoperability, and model transformation
• Collaborative modelling and management of model repositories
• Models offered as services and approaches to model monitoring
• Modelling for reuse, reliability, and maintainability
• Models addressing security, trust, and risk
Models for Data and Databases
• Modelling approaches for Big Data and NoSQL systems
Data Engineering
• Novel data models and database architectures
• Heterogeneous data, data integration, and interoperability
• Data warehouses, data lakes, OLAP, data mining, and analytics
• Internal aspects of database systems, including performance, self-tuning, benchmarking, and testing
• Database security, personalization, and recommendation systems
• Web-based databases and ontology-driven database approaches
• Data management in service-based systems
• Service-oriented applications
• Modernization and restructuring of database applications
• Data models for AI and machine learning methods
Applications and Tools
• Industrial applications and technology transfer
• Use of modelling in data management
• Modelling applications for biomedical data and systems
• Tools supporting modelling and experimental evaluation
• Insights, case reports, and practical lessons in model and data engineering
The conference proceedings will be published as a dedicated volume in the Springer Lecture Notes in Computer Science (LNCS) series.
