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11. Data and Information Quality

  

Track Chairs:

 

Markus Helfert, Dublin City University, Ireland ( This e-mail address is being protected from spam bots, you need JavaScript enabled to view it )
Cinzia Cappiello, Politecnico di Milano, Italy ( This e-mail address is being protected from spam bots, you need JavaScript enabled to view it )

  

Track Description:

 

The problem of poor data and information quality is widespread and plays a critical role for all organisations whose activity is based on communication and information. Insufficient quality of information and data often leads to numerous negative effects; it can disrupt business processes and interfere with decisions or can compromise communication and understanding among people. High data and information quality have become the crucial factor for innovative organisations in the information economy. Currently, there are two main research streams addressing the problem of ensuring high data and information quality: first a technical, database oriented approach and second a management, business oriented approach. So far, both streams are fairly isolated, although they address similar problems. Problems regarding the interdependences between technological choices and business concepts are rarely considered.

In this context, the Data and Information Quality Track aims to bring together both streams and addresses problems related to information system design and modelling. The track focuses on crucial and interrelated issues such as information systems architectures and process modelling as well as business implications correlated with data and information quality.

  

Suggested topics:

 

- Data & Information Quality-specific research problems:

- Defining and planning
- Assessment
- Management and improvement - processes and technologies
- DIQ oriented IS-Engineering methods and techniques
- Costs and benefits analyses
- Data & Information Quality in specific contexts:
- Financial service industry
- Logistics
- Healthcare
- Government
- Multimedia applications and Web environments
- Data mining & Data warehousing
- Knowledge Management
- Data & Information Quality and security/privacy/trust

 

Associate Editors:

 

- Monica Scannapieco, University of Roma “La Sapienza”, Italy
- Walter Brenner, University of St. Gallen, Switzerland
- Helinä Melkas, Helsinki University of Technology, Finland
- Bernd Heinrich, University of Augsburg, Germany