Topic 5

Parallel and distributed databases

Description

Advances in data exploitation (access, query, retrieval, analysis, mining) are inherent to current and future information systems. Today, accessing great volumes of information is reality; tomorrow data intensive management systems will enable huge user communities to transparently access multiple pre-existing autonomous, distributed and heterogeneous resources (data, documents, services). Existing data management solutions do not provide efficient techniques for exploiting and mining Tera-datasets available in clusters, peer to peer and Grid architectures. Parallel and distributed databases are a key element for achieving scalable, efficient systems that will both cost-effectively manage and extract knowledge from huge amounts of highly distributed and heterogeneous digital data repositories.

Focus

• Parallel, replicated, and distributed databases,
• Data mining, knowledge discovery,
• Web applications and web services,
• Data streaming,
• Discovering structures in web data, web data mining,
• Middleware systems,
• Distributed knowledge discovery,
• Data management in P2P systems,
• Information retrieval and web search engines,
• Parallel algorithms for data mining,
• Storage area networks and parallel files systems,
• Data-intensive grids and data grids,
• XML processing,
• Sensor network data management,
• Data warehousing and decision support,
• Communication requirements for parallel data mining,
• Distributed and parallel transaction and query processing,
• Mobile computing and databases.

Organization

Global Chair	Local Chair
Marta Patiņo-Martinez Universidad Politecnica de Madrid Madrid, Spain	Genoveva Vargas-Solar French Council on Scientific Research (CNRS) Grenoble, France
Vice Chair	Vice Chair
Elena Baralis Politecnico di Torino Torino, Italy	Bettina Kemme McGill University Montreal, Canada