The scope of the workshop includes several aspects of conceptual modeling in data-driven paradigm, but is not limited to:

• Agile modeling for big data
• Advanced applications with Hadoop or MapReduce paradigm
• Application design and architecture of big data environment
• Big Data Analytics
• Business Process Modeling
• Business Intelligence applications and modeling
• Conceptual modeling approaches for Big Data
• Ontologies for Big Data
• Conceptualization for data-drive paradigm
• Data-driven businesses
• Using data science approaches for novel analysis and applications
• Enterprise modeling and architectures for big data projects
• Data Integration and management for Hadoop ecosystems
• Data virtualization, ELT, or ETL for data integration
• Information packaging
• Knowledge management for big data
• Metamodeling
• Modeling and management for social network data
• Novel applications in Big Data
• Interface design and visualization for big data
• Model-driven development methodologies and approaches
• Provenance modeling
• Requirements modeling for Web-based applications
• Security and privacy in social networks
• Software as a Service (SaaS) modeling solutions
• Use of Hive and Hadoop in social networks
• Analytics for complex data
• Data analytics as a service
• Data mining, analytics, and warehousing over the cloud
• ETL over the cloud
• Smart Cities
• Smart health
• Education for big data and data science