The workshop solicits two types of papers: regular and industry papers. Regular research papers and industry papers are separately reviewed and there will be separate sessions in a distinct industry track. A panel will also be organized to discuss new and future research on data warehouses and OLAP technologies.

Suggested regular research topics include the following, but are not limited to:

• Data warehousing foundations and architectures
• Data warehouse design
• Source integration
• Data extraction, cleaning and loading
• Metadata management
• View materialization
• Physical organization of data warehouses
• Performance optimization and tuning
• Multidimensional modeling and queries: languages, optimization, processing
• Data warehouse consistency and quality
• Security in data warehouses
• Maintenance and evolution of data warehouses
• Data warehousing and the semantic web
• Data warehousing with unstructured data (e.g., text) and semi-structured data (e.g., XML)
• Data warehousing applications: corporate, scientific, government, healthcare, bioinformatics, etc.
• Data warehousing in mobile and wireless environments
• Tools for data warehousing and OLAP
• Frameworks for Business Process Management (BPM) and Business Intelligence (BI)
• Active data warehouses
• Integration of data warehouses and data mining
• Multimedia data warehouses

Suggested industry topics include the following, but are not limited to:

• Experience and lessons in data warehousing projects and applications
• Administration tools
• Benchmarks
• Tools for data warehousing and OLAP
• Data warehousing and Enterprise Resource Planning (ERP)
• Data warehousing and Customer Relationship Management (CRM)
• Solutions for Business Process Management (BPM) and Business Intelligence (BI)
• Surveys