ICIQ 2010 - The International Conference on Information Quality (ICIQ-2010)

The International Conference on Information Quality (ICIQ) attracts researchers and practitioners from the academic, public and private sectors. The 2010 conference is jointly sponsored by the MIT Information Quality Program and the UALR Information Quality Graduate Program and will be hosted by the Donaghey College of Engineering and Information Technology at the University of Arkansas at Little Rock (UALR), the first university to offer graduate degree programs in information quality.

The conference program will include tracks of research papers, practice-oriented papers, and panel sessions. Accepted papers will compete for the Stuart E. Madnick IQ Best Paper Award (US$1,000). Further, the best paper and other high-quality papers will be considered for fast-track to the ACM Journal of Data and Information Quality. The 15th International Conference on Information Quality will be held at UALR from November 12th (Friday, Reception: 5-6:30 p.m.) to November 14th (Sunday noon), 2010.

TOPICS OF INTEREST

Corporate and organizational IQ
■IQ Management and Data Governance
■Alignment of IQ with Business Strategies
■Business Process Performance
■IQ Education and Curriculum Development
Methods, concepts, and tools for IQ
■IQ Concepts, Metrics, Measures, and Models
■Method Engineering for IQ
■Trust, Knowledge, and Society
■Data Provenance and Annotation
■Information Product Theory and Practice
■Metadata and IQ
■IQ of Unstructured and Extracted Data
■IQ in Probabilistic, Fuzzy, and Uncertain Data
■IQ in Sensor Networks and Information Fusion
■Data Quality Systems and Tools
Measurement, improvement, and assurance of IQ
■Data Scrubbing and Cleaning
■Record Linkage and Entity Resolution
■IQ Assessment, Policies, and Standards
■Cost/Benefit Analysis of IQ Improvement
■Privacy & Security Issues in Data Cleansing
IQ cases and applications
■IQ Practices: Case Studies and Experience Reports
■IQ in the Web, Data Integration, and e-Business
■Data Warehousing and Business Intelligence
■Master Data Management
■Scientific Data
■Community Input, Pay as You Go, and Crowd Sourcing