| Subject: | [WI] CFP Data and Information Quality Track at ECIS 2011 |
|---|---|
| Date: | Fri, 1 Oct 2010 10:41:51 +0200 |
| From: | Mathias KLIER <Mathias.Klier@uibk.ac.at> |
| To: | <wi@lists.uni-karlsruhe.de> |
************************************************
CALL
FOR PAPERS
19th
European Conference on Information Systems (ECIS 2011)
Track:
“Data
and Information Quality”
http://project.hkkk.fi/ecis2011/track_data_information_quality.htm
June 9-11,
2011, Helsinki,
Finland (http://www.ecis2011.fi)
************************************************
Deadline
for paper
submissions: December 1, 2010
==========================================
Track
Description:
===============
The
quality of
data and information plays a critical role in our
knowledge-based economy.
Moreover, novel fields of application such as online social
networks and customer
relationship management have given rise to a high relevance of
data and
information quality issues in theory and practice. This is due
to the fact that
the benefit of data and information depends heavily on their
quality.
Executives and employees need high-quality data and
information to perform
business, innovation, and decision-making processes properly.
Against this
background, it is not surprising that bad data and information
quality may lead
to wrong decisions and correspondingly high costs. According
to an
international survey up to 75% of executives have already made
wrong decisions
because of bad data and information quality. In addition, they
and their staff
spend up to 30% of their working time on checking the quality
of data and
information. Furthermore, 67% of marketing executives think
that the
satisfaction of their customers suffers from bad data and
information quality.
In this respect, the consequences of bad data and information
quality are
manifold: they range from insufficient decision support for
executives to
worsening customer relationships and customer satisfaction by
addressing
customers inadequately.
Against
this
background, the assessment and improvement as well as the
economic impacts of
data and information quality currently find a great deal of
attention in
science and practice. In this context, the Data and
Information Quality Track
focuses on novel managerial as well as technological data and
information
quality challenges and solutions. The track welcomes
theoretical and empirical
contributions as well as design science-oriented research.
Suggested
Topics:
==============
*
Impact of data
and information quality
*
Assessment of
data and information quality
*
Cost/benefit
analyses of data and information quality improvement
*
Data and
information quality in sustainable decision making
*
Management of
data and information quality
*
Data and
information quality tools, methods, and concepts
*
Data and
information quality in the enterprise context
*
Data and
information quality of unstructured data
*
Quality of
ontologies
*
Value of
information (quality)
*
Data and
information quality cases and applications
-
Web 2.0
-
E-business
-
Healthcare
-
Financial services industry
-
E-government
-
Customer relationship management
-
Supply chain management
-
Data Warehousing and data mining
-
Master data management
-
Data integration
-
Quality of metadata
*
Research
Methodologies in data and information quality
Fast-Track
Publication:
===================
Outstanding
papers
will be fast-tracked for ACM Journal of Data and Information
Quality (ACM JDIQ)
(http://jdiq.acm.org/)
Track
Chairs:
===========
Bernd
Heinrich,
University of Innsbruck, Austria
Yang
W. Lee,
Northeastern University, USA
Mathias
Klier,
University of Innsbruck, Austria
Best
regards
Mathias
Klier
--------------------------------------------------------------
Dr. Mathias Klier
Leopold-Franzens-University of Innsbruck
School of Management
Information Systems
-------------------------------------
Universitaetsstrasse 15
A-6020 Innsbruck
Austria
Phone: +43 (0) 512 507 7685
Fax: +43 (0) 512 507 9809
Email: mathias.klier@uibk.ac.at
WWW: http://www.uibk.ac.at/wipl
----------------------------------------------------------------