The workshop solicits contributions on data management issues related to data processing/analytics within the energy domain ranging from conceptual modeling over theoretical foundations, system architecture and implementation to real world case studies. Relevant topics include, but are not limited to, the following:

Energy-specific data modeling
Meta-data management, provenance management, life cycle management of energy data
Large-scale data integration considering energy-specific formats and protocols
Novel data processing architectures for coping with very large energy data sets
Novel partitioning, caching, and replication schemes within energy IT infrastructures
Query language design, query processing, and query optimization techniques
Robustness aspects with regard to performance, scalability, reliability, and dependability
Data security and data privacy when managing energy data
Novel and domain specific data mining algorithms
Domain-specific forecasting and prediction methods
Systems support to manage and query forecasted data
Support for advanced energy analytics within database systems
Case studies outlining real world applications and application scenarios with a strong focus on production, distribution, and consumption of energy
Challenges and vision of mid-/long-term solutions for an efficient and robust energy data management system

We welcome submissions of high-quality, original research and are particularly interested in submissions that demonstrate industrial-strength solutions from systems as well as application perspectives. We also explicitly ask for contributions describing work-in-progress with a clear vision of the overall work.