Contributions about methods, models, techniques, architectures and platforms for supporting the engineering and evolution of information systems and organizations could include (but are not limited to): 

▪ Models, Methods and Techniques in IS Engineering
        - Conceptual modeling, languages and design
        - Requirements engineering
        - Business process modeling, analysis, and engineering
        - Process mining
        - Models and methods for evolution and reuse
        - Domain and method engineering
        - Variability and configuration management
        - Compliance and alignment handling
        - Active and interactive models
        - Quality of IS models for analysis and design
▪ Domain Specific and multi-aspect IS Engineering
        - IT governance
        - eGovernment
        - Cyber security
        - Smart City management
        - Industrial ecology management
        - IS for healthcare
        - Educational IS
        - Value and supply chain management
        - Industry 4.0
        - Sustainability and social responsibility management
        - Predictive information systems
        - Big Data and privacy
        - Safety management
        - Dark data processing ▪ Novel approaches to IS Engineering
        - Context-aware and adaptive systems
        - Agile enterprise models and architecture
        - Distributed, mobile and open architecture
        - IS for collaboration
        - Social computing
        - Customer analytics
        - Secure and trusted systems
        - Big data application in IS
        - Application of AI in IS
        - Data and business analytics
        - Use of new visualization techniques in IS
        - Service science and innovation
▪ Architectures and Platforms for IS Engineering
        - Big Data architectures
        - Cloud-based IS engineering
        - Service oriented IS engineering
        - Multi-agent IS engineering
        - Robotic Process Automation
        - Multi-platform IS engineering
        - Cyber-physical systems
        - Big data and the Internet of Things
        - Blockchains
        - Digital twins
        - Workflow and PAIS systems
        - Handling of real time data streams
        - Content management and semantic Web