DIKE 2017 - Data, Information and Knowledge Engineering

The track is devoted to all aspects of eliciting, acquiring, modeling, storing, and managing data, information, and knowledge. Contributions concerning all steps in the development of data and knowledge-intensive systems ? theoretical foundations, design, implementation and maintenance techniques ? are welcome.
Topics include, but are not limited to:
Big Data storage, processing and analytics,
business process modeling, automation, and management
data and information modeling,
data and information semantics,
data integration, data cleaning,
data intensive applications,
data warehousing,
data mining, knowledge discovery and machine learning,
data privacy and security,
information retrieval,
intelligent agents, multi-agent systems,
knowledge modeling and processing,
knowledge acquisition and engineering,
linked data and open data,
mobile data and information,
multimedia, spatial, and temporal data and knowledge,
parallel and distributed data platforms
probabilistic databases, uncertainty and approximate querying,
query and natural language processing,
provenance and trust in data management and knowledge engineering,
stream data management,
web and semantic web data and knowledge engineering.