International Conference on Model and Data Engineering

概要

MEDI 2026 is an established international forum bringing together researchers and practitioners in Model-Driven Engineering, Data Management, and Information Systems. Authors are invited to submit English-language research and application papers representing original, previously unpublished work. Duplicate submissions are not allowed. Paper Types: Full Papers (Up to 14 pages), Short Papers (Up to 8 pages). Submissions must conform to Springer's LNCS style. Papers must be submitted as a single PDF document via CMT System. Submitted papers will be carefully evaluated based on originality, significance, technical soundness, and clarity of exposition. All accepted papers, including short papers, will be published in the Springer LNCS series. Areas of interest include: Artificial Intelligence (AI), Modeling for Generative AI, Modeling for Large Language Models, Modeling for Explainable AI, Agent theories and models, Agent ontologies, reasoning, and decision-making, Agent and multi-agent learning, Q-learning, reinforcement learning, Traditional Databases for AI, AI for Data Management, Data Engineering, Data Science Workflow, Data Streams, Heterogeneous data, data Integration, Interoperability, Data warehouses, Data Lakes, Data Fabric, Database system Internals, performance analysis, self-tuning benchmarking and testing, Web databases, ontology-based databases, Service based data management, Service oriented applications, Modelling and Models Engineering, Modelling languages and related standards, Modelling in software and complex system engineering, Formal methods, analysis, verification & validation, Model-based testing and performance analyses, Ontology-based modelling, Heterogeneous modelling, model integration, interoperability, model transformation, Collaborative modelling and model repositories, Modelling for reuse, dependability and maintainability, Entity-Relationship modelling and extensions, Models for security, trust, risk, Models for Big Data & NoSQL databases, Graph-based modelling for complex relationships, Data modelling for machine learning pipelines. Best papers will be selected and invited for submission to the Journal of Computer Languages and other journals.

情報源ランク

地図