The purpose of the workshop is to bring to the fore current issues of data quality as it affects users and researchers dealing with large data sets in potentially complex settings. There are (at least) three overlapping constituencies that must have a stake in these matters: computer scientists, statisticians, and users (especially in business and government). One aim is to create interactions across the constituent groups leading to collaborative efforts to resolve open questions; another goal is to disseminate more widely an awareness of the problems, methodologies, and practices.
Data Quality and Reconciliation, Munir Cochinwala, Telcordia Technologies
Information Quality Processes and Technologies: Information Quality in Practice, Larry P. English, Information Impact International, Inc.
The Statistical Administrative Record System and Administrative Records 2000 Experiment: System Design, Successes, Challenges, Dean H. Judson, U.S. Census Bureau
Challenges in Improving Information Quality, Ann Thornton, Deloitte and Touche LLP
Developing Data Warehouses with Quality in Mind, Yannis Vassiliou, National Technical University of Athens
A Decision Model for Cost Optimal Record Matching, Vassilis Verykios, Drexel University
Raising the Bar for Data Quality in the New Millenium, Richard Wang, Boston University
Data Quality for Large Transaction Streams, Allan R. Wilks, AT&T Labs Research
Records Linkage Methods, William E. Winkler, U.S. Census Bureau
Papers by the Presenters
Seven Deadly Misconceptions About Information Quality, Larry P. English
Machine Learning, Information Retrieval, and Record Linkage, William E. Winkler