Data and Information Quality

Track Chairs

Bernd Heinrich (primary contact person):
Full Professor, Department of Information Systems, University of Innsbruck,
Universitaetsstrasse 15, A-6020 Innsbruck, Austria;
bernd.heinrich@uibk.ac.at; phone: +43 512/507-7680; fax: +43 512/507-9809

Yang W. Lee:
Associate Professor, College of Business Administration, Northeastern University,
214 Hayden Hall, Boston, MA 02115, USA;
y.lee@neu.edu; phone: +01 617/373-5052

Mathias Klier:
Assistant Professor, Department of Information Systems, University of Innsbruck,
Universitaetsstrasse 15, A-6020 Innsbruck, Austria;
mathias.klier@uibk.ac.at; phone: +43 512/507-7685; fax: +43 512/507-9809

Track Description:

The Data and Information Quality Track welcomes research papers and teaching cases that ask questions on strategic, economic, organizational, or technical aspects of data and information in organizations. Without a doubt, data and information are valuable resources and assets in today’s knowledge-based economy. Information impacts both the organizational as well as individual levels, as evidenced in the recent rise in social networks and increased use in customer relationship management. The value and benefit of data and information, however, will vary depending on the level of quality of data and information given. Indeed, organizations demand quality data and information to support decision-making and innovation in business.

Currently, data and information quality area is receiving increased attention from both academics and industry leaders because of the inherent value and risks involved in differentiating information practices.

The data and information quality track welcomes papers with diverse research methods, including theoretical, empirical, and 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

Journal Publication

Outstanding papers will be fast-tracked for publication at ACM Journal of Data and Information Quality (ACM JDIQ) (http://jdiq.acm.org/)