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WORKSHOP ON MANAGING EVOLUTION OF DATA WAREHOUSES (MEDWa)
Riga, Latvia, September 7, 2009
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SUBJECT AREA DESCRIPTION AND MOTIVATION
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Nowadays, data warehouses are worldwide accepted and obligatory components of decision support systems. From a technological point of view, a data warehouse is a database that integrates multiple, usually heterogeneous, distributed, and autonomous data sources. An inherent feature of data sources is that they can evolve in time independently of a DW that integrates them. The evolution of EDSs can be characterized by content changes, i.e., insert/update/delete data, and schema changes, i.e., add/modify/drop a data structure or its property. The propagation of content changes into a DW is handled by means of materialized views. The evolution of DWs caused by the propagation of schema changes is much more difficult to handle and has not been fully solved yet.

The evolution of data sources has also impact on the Extraction-Translation-Loading (ETL) software used for feeding a data warehouse with data. For these reasons, it is inevitable to develop solutions for managing the evolution of data warehouses and ETL software.

The just emerging DW technologies applied to complex data like XML, spatio-temporal, and multimedia data will also suffer from structural and content changes in data sources and will face the same problems as traditional data warehouses. Moreover, currently, semantic Web, knowledge bases, and reasoning technologies are being incorporated into decision support systems. They will soon become technologies complementary to DW and OLAP, aiming at yet better decision support. These new technologies heavily use ontologies. Ontologies will evolve for similar reasons as information systems evolve. Thus, research in this field will face problems with managing the evolution of ontologies.

AIM
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The aim of this workshop is twofold. Firstly, to gather those researchers
and industry developers who focus on handling dynamics in data warehouses,
in order to discuss their achievements and open issues. Secondly, to inspire
a broader audience to further research and development in the area.

MAJOR TOPICS OF INTEREST:
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* Data warehouse architectures for evolution support
* Data warehouse modeling for evolution support
* Temporal and multiversion data warehouses
* Managing the evolution of ETL
* Query languages and OLAP tools for evolving data warehouses
* Integrity constraints for evolving data structures
* Indexing temporal and multiversion data
* Metadata management and querying
* Temporal and evolving ontologies
* Quality of evolving data
* Case studies, prototype systems, experience reports
* Surveys on research approaches, prototypes, and commercial systems

IMPORTANT DATES
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27.04.2009 - papers due
01.06.2009 - notification of acceptance
15.06.2009 - camera ready due

WORKSHOP PROCEEDINGS
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An extended post-worksop version of accepted and presented papers will be published in
a Springer Verlag LNCS volume. Accepted papers will also be published in a local
conference proceedings (available at the workshop).

PAPER SUBMISSION
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Papers of maximum 8 pages in the LNCS format should be submitted via the EasyChair system
http://www.easychair.org/conferences/?conf=inteledu2009

WORKSHOP CHAIR:
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Robert Wrembel, Poznan University of Technology, Poland
e-mail: Robert.Wrembel@cs.put.poznan.pl

PROGRAM COMMITTEE
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Ladjel Bellatreche, Ecole Nationale Sup?rieure de M?canique et d'A?rotechnique, France
Alfredo Cuzzocrea, University of Calabria, Italy
Matteo Golfarelli, University of Bologna, Italy
Marcin Gorawski, Silesian University of Technology, Poland
Carlos Hurtado, Universidad de Chile, Chile
Stanislaw Kozielski, Silesian University of Technology, Poland
Tadeusz Morzy, Poznan University of Technology, Poland
Stefano Rizzi, University of Bologna, Italy
Alkis Simitsis, IBM Almaden Research Center, USA
Alejandro Vaisman, Universidad de Buenos Aires, Argentina
Panos Vassiliadis, University of Ioannina, Grece