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