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*** Processing and Managing Complex Data for Decision Support ***

* Introduction

Nowadays, the data management community acknowledges the fact that data are not
only numerical or symbolic, but that they may be:
- represented in various formats (databases, texts, images, sounds, videos...);
- diversely structured (relational databases, XML documents repository...);
- originating from several different sources (distributed databases, the
Web...);
- described through several channels or points of view (radiographies and audio
diagnosis of a physician, data expressed in different scales or languages...);
- changing in terms of definition or value (temporal databases, periodical
surveys...).

Data that fall in several of the above categories may be termed as complex
data. Managing such data involves a lot of different issues regarding their
structure, storage and processing. However, in many decision support fields
(CRM, marketing, competition monitoring, medicine...), they are the real data
that need to be exploited. Now that most decision support technologies such as
data warehousing, on-line analysis (OLAP) or data mining have proven to be
valuable on "simple" data, the issue of complex data must be addressed.

* Overall objective of the book

The objective of this book is to provide an overall view of the field of
complex data processing by bringing together various research studies,
presumably in different subfields, and underlining the similarities between the
different data, issues and approaches. The idea is also to show that many
applications can benefit from the exploitation of other data that the ones they
usually deal with.

* Topics of interest (this list is non-exhaustive)

Complex data warehousing:
- Complex data description languages and formats
- Complex data integration
- Complex data warehouse foundations, design and architectures
- XML data warehousing
- Complex data warehouse consistency and quality
- Multidimensional modeling of complex data
- OLAP on complex data
- Maintenance and administration of complex data
- Performance, optimization and tuning
- Data warehouse benchmarks

Complex data mining:
- Mining different data formats
- Combining mining results from different sources
- Mining data streams
- Knowledge discovery in spatial, musical, biomedical data...
- Multi-agent environments for concurrent mining of complex data
- Human-machine interfaces for complex data mining
- Combining OLAP and data mining for complex data analysis
- Performance of complex data mining techniques

Metadata:
- Using the RDF and MPEG standards for metadata representation
- Metadata management
- Interoperability and heterogeneity

Semantic content analysis for complex data retrieval

* Important dates

October 15, 2004: Submission of proposals for chapters
November 1, 2004: Notification of proposal acceptance/rejection
January 15, 2005: Submission of full chapters
April 1, 2005: Notification of the chapter reviews
May 15, 2005: Submission of revised chapters
July 1, 2005: Notification of final acceptance/rejection
July 15, 2005: Final version of chapters

* Submission Guidelines

You are invited to submit a proposal of 2-5 pages describing the focus of your
chapter. The proposal should also give the tentative organization of the
chapter (section titles with section summaries).

Papers should be original and should not be submitted for publication or
published elsewhere. Electronic submissions are required. All submitted
chapters will be reviewed on a blind review basis.

The book is scheduled to be published in 2005 by Idea Group, Inc., publisher of
the Idea Group Publishing, Information Science Publishing, IRM Press, CyberTech
Publishing and Idea Group Reference imprints.

* Contact

Please e-mail your proposal or questions to:

Jerome Darmont and Omar Boussaid
ERIC, University of Lyon 2
5 avenue Pierre Mendes-France
69676 Bron Cedex
France

E-mail: cdbook-aqNk/Nfiapu/yem0rkCUM0Za+K1vlBrA@xxxxxxxxxxxxxxxx

Book web page: http://eric.univ-lyon2.fr/~jdarmont/cdbook/
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