Topic 5

Parallel and distributed databases


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.


  • 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.


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