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Journal of Data and Information Quality (JDIQ), Volume 2 Issue 1, July 2010

Editors’ Comments: ACM Journal of Data and Information Quality (JDIQ) is alive and well!
Stuart E. Madnick, Yang W. Lee
Article No.: 1
DOI: 10.1145/1805286.1805287

Using Data Mining Techniques to Discover Bias Patterns in Missing Data
Monica Chiarini Tremblay, Kaushik Dutta, Debra Vandermeer
Article No.: 2
DOI: 10.1145/1805286.1805288

In today’s data-rich environment, decision makers draw conclusions from data repositories that may contain data quality problems. In this context, missing data is an important and known problem, since it can seriously affect the accuracy of...

Judging the Credibility of Information Gathered from Face-to-Face Interactions
Matthew L. Jensen, Judee K. Burgoon, Jay F. Nunamaker, Jr
Article No.: 3
DOI: 10.1145/1805286.1805289

One of the most pernicious threats to information quality comes through perpetration of deception by information suppliers. Deception undermines many critical dimensions of information quality, such as accuracy, completeness, and believability....

On Detecting Data Flow Errors in Workflows
Hema S. Meda, Anup Kumar Sen, Amitava Bagchi
Article No.: 4
DOI: 10.1145/1805286.1805290

When designing a business workflow, it is customary practice to create the control flow structure first and to ensure its correctness. Information about the flow of data is introduced subsequently into the workflow and its correctness is...

A Survey on Uncertainty Management in Data Integration
Matteo Magnani, Danilo Montesi
Article No.: 5
DOI: 10.1145/1805286.1805291

In the last few years, uncertainty management has come to be recognized as a fundamental aspect of data integration. It is now accepted that it may not be possible to remove uncertainty generated during data integration processes and that...

Call for Papers Special Issue on Entity Resolution
John R. Talburt, Stuart E. Madnick, Yang W. Lee
Article No.: 6
DOI: 10.1145/1805286.1805292