5. Parallel and Distributed Databases


Advances in data management (store, access, query, retrieval, analysis, mining) are inherent to current and future information systems. Today, accessing great volumes of information is a reality; in the future data intensive management systems will enable huge user communities to transparently access multiple pre-existing autonomous, distributed and heterogeneous resources (data, documents, images, 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 file systems, databases, data warehouses, and digital libraries 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.


  • 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 and grid-based knowledge discovery
  • Data management in P2P systems
  • Information retrieval and web search engines
  • Parallel and distributed algorithms for data mining
  • Storage area networks and parallel files systems
  • Data-intensive grids and data grids
  • XML processing
  • Data provenance
  • 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

Topic committee

Global chair
Alex Szalay The John Hopkins University USA
Vice chair
Alfons Kemper TU Munich Germany
Manuel Prieto-Matias UCM Spain
Local chair
Djoerd Hiemstra University of Twente Netherlands



August 25, 2009
0 days to go

Registration Logo

Registration is closed

Supported by

TU Delft Logo

PDS Logo

ACM Logo

Xtreem Logo