CAiSE 27

Theme: Hybrid Intelligent Information Systems Engineering

Hybrid Intelligent Information Systems Engineering is considered a multidisciplinary field that combines data-driven (e.g., machine learning, deep learning) and knowledge-driven (e.g., symbolic reasoning, ontologies, rules) approaches to support intelligent, adaptive, and explainable decision-making in complex cyber-physical environments. It is concerned with the design, development, integration, and management of information systems that ensure data and information management, interoperability, scalability, and alignment with organisational and domain-specific requirements.

Within this field, Information Systems Engineering (IS Engineering) provides the foundational principles, methods, and frameworks that enable the integration of hybrid intelligence into organisational environments, ensuring that these systems are semantically grounded through data and information models; architecturally coherent and interoperable across heterogeneous components; governed and aligned with organisational processes, policies, and decision-making needs; and, sustainable and evolvable across the full lifecycle of data, models, and knowledge.