ACM Eleventh International Workshop on Data Warehousing and OLAP
DOLAP 2008
(in conjunction with ACM CIKM 2008)
October 30, 2008, Napa Valley, CA, USA
Sponsored by ACM, SIGIR, SIGMIS
AIM OF THE WORKSHOP
Data Warehouse (DW) and Online Analytical Processing (OLAP) technologies are the core of current Decision Support Systems. Traditionally, a data warehouse has been a historical (and relatively static) repository of data collected from a wide variety of heterogeneous data sources by means of Extraction-Transformation-Loading (ETL) processes. The widespread deployment of both DWs and OLAP technologies is due to the intuitive representation of data provided to data analysts or managers in support of management decisions. Recently, the trend is that DWs become more and more dynamic, with near-realtime updates, and include more complex types of data.
Research in data warehousing and OLAP has produced important technologies for the design, management and use of information systems for decision support. Much of the interest and success in this area can be attributed to the need for software and tools to improve data management and analysis given the large amounts of information that are being accumulated in corporate as well as scientific databases. Nevertheless, the high maturity of these technologies as well as new data needs or applications not only demand more capacity or storing necessities, but also new methods, models, techniques or architectures to satisfy these new needs. Some of the hot topics in data warehouse research include distributed data warehouses, web warehouses, data streams, realtime DWs, GIS/location-based services, biomedical data, integration of semi-structured and unstructured data, security/privacy and quality management.
Like the previous successful DOLAP workshops, the DOLAP 2008 workshop aims to synergistically connect the research community and industry practitioners. It provides an international forum where both researchers and practitioners can share their findings in theoretical foundations, current methodologies, and practical experiences. DOLAP will focus on new research directions and emerging applications in DW & OLAP.
Topics of Interest
The workshop solicits two types of papers: regular and industry papers. Regular research papers and industry papers are separately reviewed and there will be separate sessions in a distinct industry track. In addition, there will be a session with invited industry papers presenting research challenges. A panel will discuss future research on data warehouses and OLAP technologies. Suggested regular research topics include, but are not limited to:
*Data warehousing foundations and architectures
*Data warehouse design
*Maintenance and evolution of data warehouses
*Source integration
*Data extraction, cleaning and loading
*Data warehouse consistency and quality
*Active/Real-Time data warehouses
*Lineage Tracing
*Multidimensional modeling and queries: languages, optimization, processing
*Visualization
*Metadata management
*View materialization
*Physical organization of data warehouses
*Performance optimization and tuning
*Web warehousing
*Data warehousing and the semantic web
*Data warehousing with unstructured data and semi-structured data (e.g., XML)
*Multimedia data warehouses
*Biomedical data warehouses
*Data warehousing & OLAP in mobile and wireless environments
*Frameworks for Business Process Management (BPM), Business Intelligence (BI),
and Business Process Intelligence (BPI)
*Tools for data warehousing and OLAP
*Integration of data warehouses/OLAP and data mining
*Integration of OLAP and Information Retrieval/search engines
*Warehousing Stream and Sensor data: integration, aggregation and approximation
*Security and privacy in data warehouses
*Personalization
*OLAP and what-if analysis
*Software Engineering techniques for DW&OLAP
*Knowledge-based approaches and AI techniques for DW&OLAP
Industry papers shall address:
*Experience and lessons in data warehousing projects and applications
*Administration tools
*Benchmarks
*Tools for data warehousing and OLAP
*Data warehousing and Enterprise Resource Planning (ERP)
*Data warehousing and Customer Relationship Management (CRM)
*Solutions for Business Process Management (BPM) and Business Intelligence (BI)