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 a high-quality international journal.
Research topics include, but are not limited to:
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Data warehousing foundations and architectures
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Data warehouse Modelling and Design
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Maintenance and evolution of data warehouses
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Software Engineering techniques for DW and OLAP
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Security, personalization and privacy in data warehouses
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Data extraction, cleaning, and loading(ETL)
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Active/Real-Time data warehouses
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Multidimensional modeling and queries
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Metadata management
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Physical organization of data warehouses
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Performance optimization and tuning
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Data warehousing with unstructured data (e.g., text) and semi-structured data (e.g., XML)
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Multimedia data warehouses
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Data warehouses in Scientific Applications
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Spatial, temporal, and spatio-temporal data warehouses
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Integration of OLAP and information retrieval/search engines
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Integration of data warehouses/OLAP and data mining
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Warehousing stream and sensor data
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OLAP on Documents -Keyword search in Data Warehouses
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Workflows in Data warehouses
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Semantic Web & Deep Web in Data warehouses
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Using MapReduce in Data warehouses
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SQL Vs MapReduce for Analytical Processing
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DW Deployment (Parallel machine, Database Clusters, Cloud, etc.)
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Data warehousing and OLAP for Big Data
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Smart Grid & DW
