Declarative Data Cleaning: Language, Model, and Algorithms
Proceedings of the 27th International Conference on Very Large Data Bases
Potter's Wheel: An Interactive Data Cleaning System
Proceedings of the 27th International Conference on Very Large Data Bases
Answer sets for consistent query answering in inconsistent databases
Theory and Practice of Logic Programming
A cost-based model and effective heuristic for repairing constraints by value modification
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
ConQuer: efficient management of inconsistent databases
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Improving data quality: consistency and accuracy
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Conditional functional dependencies for capturing data inconsistencies
ACM Transactions on Database Systems (TODS)
ICDT'07 Proceedings of the 11th international conference on Database Theory
A revival of integrity constraints for data cleaning
Proceedings of the VLDB Endowment
Conditional Dependencies: A Principled Approach to Improving Data Quality
BNCOD 26 Proceedings of the 26th British National Conference on Databases: Dataspace: The Final Frontier
GDR: a system for guided data repair
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
Data Auditor: exploring data quality and semantics using pattern tableaux
Proceedings of the VLDB Endowment
Handling dirty databases: from user warning to data cleaning -- towards an interactive approach
SUM'10 Proceedings of the 4th international conference on Scalable uncertainty management
Context-aware replacement operations for data cleaning
Proceedings of the 2011 ACM Symposium on Applied Computing
Design by example for SQL table definitions with functional dependencies
The VLDB Journal — The International Journal on Very Large Data Bases
Detecting suspect answers in the presence of inconsistent information
FoIKS'12 Proceedings of the 7th international conference on Foundations of Information and Knowledge Systems
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We present Semandaq, a prototype system for improving the quality of relational data. Based on the recently proposed conditional functional dependencies (CFDs), it detects and repairs errors and inconsistencies that emerge as violations of these constraints. We demonstrate the following functionalities supported by Semandaq: (a) an interface for specifying CFDs; (b) a visual tool for automated detection of CFD violations in relational data, leveraging efficient SQL-based techniques; (c) extensive visual data exploration capabilities that provide the user with various measures of the quality of the data; (d) repair (cleaning) functionality without excess human interaction, built upon CFD-based cleaning algorithms; we show how Semandaq allows for a natural exploration of the quality of the obtained repairs. Semandaq is a promising tool that provides easy access and user-friendly data quality facilities for any relational database system.