2nd CfP: Track on Business Intelligence at 10-th ISPE CE

CALL FOR PAPERS
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ISPE/CE2003 Conference and Exhibition
10th ISPE INTERNATIONAL CONFERENCE ON 
CONCURRENT ENGINEERING: RESEARCH AND APPLICATIONS

Carlton Madeira Hotel - Madeira Island, Portugal

26 - 30 JULY, 2003

new deadline: March 15, 2003 
(due to a request by the general conference chair)

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Invited Track on 

Business Intelligence and CE
===========================

Session 1: Data Warehousing
Session 2: Knowledge Discovery in Databases
Session 3: Application of Business Intelligence Solutions (Experience Papers)

http://www-is.informatik.uni-oldenburg.de/~ce2003/


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Concurrent Engineering (CE) is widely known as an effective product 
development approach. Its major objective is to reduce the system/product 
development time and effort through a better integration of activities and 
processes. As defined by the US Institute for Defense Analyses (IDA), CE 
is the systematic approach to the integrated, concurrent design of products 
and related processes, including manufacturing and support throughout the 
whole product life cycle from conception to disposal. CE methodology becomes 
even more attractive today and in the future when the procedures and the 
technologies of design and manufacturing become more globalized, standardized, 
dynamic and flexible. The challenge for the future generation of CE 
methodologies and infrastructures is the provision of the solutions for 
automated rational interoperation among independent human and artificial 
team-players in open organizations. The appearance of virtual enterprises, 
consortia as temporary coalitions in design and manufacturing make CE 
activities and processes globally dispersed organizationally and 
geographically. Another big task for CE methodology is to properly and 
effectively guide the assembly of a design or a production process from 
matching distributed service components. The services are evidently 
provided by independent parties and possess varying availability and 
price over time. 

CE leads to a rapid growth of on-line data and the widespread use of 
databases necessitates the development of techniques for efficiently 
integrating and storing huge amounts of data, extracting useful knowledge 
and for facilitating database access. Data Warehousing and Knowledge 
Discovery in Databases which are often characterized as Business intelligence 
solutions are emerging as key technologies for enterprises that wish to 
improve their data analysis, decision support activities, and the automatic 
extraction of knowledge from data. The objective of the track "Business 
Intelligence and CE" is to bring together researchers and 
practitioners to discuss research issues and experience in developing and 
deploying data warehousing and knowledge discovery systems, applications 
and solutions in order to assist CE. 

Data Warehousing embraces technology and industrial practice to systematically 
integrate data from multiple distributed data sources which are common to CE 
and to use that data in annotated and aggregated form to support business 
decision-making, enterprise management but also product placement and 
manufacturing. Although many database techniques have been revisited or 
newly developed in the context of data warehouses (such as view maintenance 
and OLAP) little attention has been paid to the design and management of 
data warehouses in order to serve CE. 

Advances in data gathering, storage, and distribution technologies have 
far outpaced computational advances in techniques for analyzing and 
understanding data. This created an urgent need for a new generation 
of tools and techniques for Data Mining and Knowledge Discovery in 
Databases (KDD). KDD is a broad area that integrates methods from several 
fields including statistics, databases, AI, machine learning, pattern 
recognition, uncertainty modeling, data visualization, high performance 
computing, optimization, management information systems, and knowledge-based 
systems ... KDD refers to a multi-step process that can be highly interactive 
and iterative. It includes selection, preprocessing, transformation, data 
mining, interpretation/evaluation and deployment. Data mining algorithms 
are used to discover patterns, clusters and models from data. These patterns 
and hypotheses are then rendered in operational forms that are easy for 
people to visualize and understand. 


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SCOPE
======

The scope of the track is formed of, but not limited to, the following topics:

Session 1: Data Warehousing
===========================

+ DW architecture and functionality 
+ Data warehouses vs. federated database systems vs. federated data warehouses 
+ Management of data quality and uncertainty, vagueness, imprecision in CE 
+ Organization of meta-data management 
+ Query processing and optimization 
+ Data Warehouse Operational Processes in concurrent environments 
+ Temporal Aspects in CE 
+ Extract-Transform-Load (ETL) and Data Cleaning tools and techniques 
+ Query Optimizing and Planning 
+ DW Design in order to support CE 
+ Materialized view selection for data warehousing 
+ DW Usage & OLAP in CE 
+ Multidimensional query languages for CE 
+ Data warehouse evolution 
+ Data warehouse security and reliability 
+ Data warehouses and the web 
+ Spatiotemporal aspects of data warehousing 
+ Active data warehousing 
+ Analytical front-end tools for CE 
+ Data cleansing 
+ Design and maintenance of metadata repository 
+ Distributed data warehousing 
+ Concurrent Transaction processing in data warehouses 
+ Virtual data warehousing

Session 2: Knowledge Discovery in Databases
===========================================

+ Preprocessing in concurrent environments 
+ Discovering (temporal) knowledge on temporal target data 
+ Distributed and parallel data mining/Knowledge Discovery 
+ Association rules and temporal association rules 
+ Clustering 
+ Data and knowledge representation in concurrent envronments 
+ Data mining agents 
+ Evaluating, consolidating, and explaining discovered knowledge 
+ Incremental knowledge discovery 
+ Integration of data warehousing and OLAP and data mining 
+ Interactive data exploration and discovery 
+ Languages and interfaces for data mining in the CE-context 
+ Mining unstructured and structured texts

Session 3: Application of Business Intelligence Solutions (Experience Papers)
=============================================================================

+ Experience with data warehouse software and tools 
+ Motivation for installing business intelligence solutions 
+ Integration of a data warehouse into an organization's business processes 
+ Supporting federations of data warehouses in CE 
+ Detection of useful/necessary functionalities lacking from commercial 
  products in CE 
+ Problems and challenges in data warehouse usage (e.g. data loading, data 
  cleaning, data 
  inconsistency, data maintenance, data quality, performance issues) 
+ User acceptance of data warehouses 
+ Impact of OLAP and data mining on business decisions 
+ Success stories / Failures of implementing Business Intelligence Solutions 
+ Surveys of industrial applications, particularities and problems

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SUBMISSIONS AND PUBLICATION
===========================

Only full paper submissions will be accepted to CE2003, subject to the 
international scientific rules for review. Only electronic submissions will 
be accepted to the track. Please submit the PDF version of your manuscript to 

ce2003-P5zCR3hpn1/PGafi4Lr74IE/qvNn98+dl1ZRrequuSGELgA04lAiVw@xxxxxxxxxxxxxxxx

indicating the session you want to submit the paper to. 

For questions regarding the individual sessions please contact the session 
chairs (see website).

Proceedings will be published as an ISBN numbered book with accompanying CD by 
A.A. 
Balkema Publishers and will be printed before the conference to be distributed 
to the 
attendants. 

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REVIEW
======

Submitted papers will be reviewed by at least three members of the conference 
program committee or the Track committee and selected on the basis of their 
relevance, originality and scientific quality. 

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AUTHOR GUIDELINE
================

Papers should include: Title, name(s) and affiliations(s) of authors, an 
abstract of no more than 200 words, a set of relevant keywords, resulting 
in a manuscript of six to eight A4-size pages together with figures and 
references. Please also include an additional cover sheet containing name, 
address, telephone, FAX numbers, and e-mail address of the person to 
whom correspondence regarding the paper should be addressed.

Formatting guidelines may be downloaded from 
http://isg.uninova.pt/ce2003/instrution_to_authors.htm


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IMPORTANT DATES
===============

Friday,  March 15, 2003 (NEW) Paper submission deadline 
Monday,  March 24, 2003       Notification of acceptance 
Monday,  April 14, 2003       Camera ready due 
Monday,  April 21, 2003       Preliminary program due 
Friday,  April 25, 2003       Early bird registration deadline



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TRACK REVIEW COMMITTEE
======================


Hans-Jürgen Appelrath, University of Oldenburg, Germany
Peter Chamoni, University of Duisburg, Germany
Eibe Frank, University of Waikato, New Zealand
Norbert Gronau, University of Oldenburg, Germany
Wolfgang Hümmer, University of Erlangen-Nuremberg, Germany
Manfred Jeusfeld, Tilburg University, Netherlands
Frank Köster, University of Oldenburg, Germany
Ulrich Küsters, Katholische Universität Eichstätt, Germany
Wolfgang Lehner, University of Dresden, Germany
Matthias Meyer, Ludwig-Maximilians-University Munich, Germany
Bamshad Mobasher, DePaul University, Chicago, USA
Manfred Schwaiger, Ludwig-Maximilians-University Munich, Germany
Heiko Tapken, University of Oldenburg, Germany
Stefan Wrobel, Fraunhofer Institute for Autonomous Intelligent Systems (AIS), 
Germany

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