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ACM Thirteenth International Workshop On
Data Warehousing and OLAP
(DOLAP 2010)

Colocated with

Toronto, Canada

October 30, 2010

Main Page
Call for Papers
Submission Instructions
Contact Info

Important Dates

Submission deadline:
 July 2, 2010
 July 30, 2010
 October 30, 2010
Invitation to Journal:
 November 09, 2010
Submission to IS journal:
 December 10, 2010

Topics of Interest

DOLAP accepts submissions on data warehousing in a broad sense from both universities and industry. We are expanding topics to include work that bridges data warehousing and other large scale data processing platforms. This year, we encourage submissions from industry data warehouse technology developers describing technical details about their products as well as companies exploiting data warehousing technology describing case studies, experiences and technology limitations. A selection of best papers will be recommended for inclusion in a special issue of the Information Systems Journal.

Research topics include, but are not limited to:

  • Data warehousing foundations and architectures
  • Data warehouse Modelling and Design
  • Maintenance and evolution of data warehouses
  • Software Engineering techniques for DW and OLAP
  • Security, personalization and privacy in data warehouses
  • Data extraction, cleaning, and loading(ETL)
  • Active/Real-Time data warehouses
  • Multidimensional modeling and queries
  • Metadata management
  • Physical organization of data warehouses
  • Performance optimization and tuning
  • Data warehousing with unstructured data (e.g., text) and semi-structured data (e.g., XML)
  • Multimedia data warehouses
  • Data warehouses in Scientific Applications
  • Spatial, temporal, and spatio-temporal data warehouses
  • Integration of OLAP and information retrieval/search engines
  • Integration of data warehouses/OLAP and data mining
  • Warehousing stream and sensor data
  • Software approaches for DW & OLAP
  • OLAP on Documents
  • Keyword search in Data Warehouses
  • Workflows in Datawarehouses
  • Semantic Web & Deep Web in Datawarehouses
  • Using MapReduce in Datawarehouses
  • SQL Vs MapReduce for Analytical Processing

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