Discovering approximate keys in XML data
Proceedings of the eleventh international conference on Information and knowledge management
Strong functional dependencies and their application to normal forms in XML
ACM Transactions on Database Systems (TODS)
Efficient discovery of XML data redundancies
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
XML Constraint-tree-based Functional Dependencies
ICEBE '06 Proceedings of the IEEE International Conference on e-Business Engineering
ACM SIGMOD Record
Consistent data for inconsistent XML document
Information and Software Technology
XML schema refinement through redundancy detection and normalization
The VLDB Journal — The International Journal on Very Large Data Bases
On generating near-optimal tableaux for conditional functional dependencies
Proceedings of the VLDB Endowment
Discovering data quality rules
Proceedings of the VLDB Endowment
Business to business interoperability: A current review of XML data integration standards
Computer Standards & Interfaces
Using transversals for discovering XML functional dependencies
FoIKS'08 Proceedings of the 5th international conference on Foundations of information and knowledge systems
Querying and repairing inconsistent XML data
WISE'05 Proceedings of the 6th international conference on Web Information Systems Engineering
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XML data inconsistency has become a serious problem since XML was widely adopted as a standard for data representation on the web. XML-based standards such as OASIS, xCBL and xBRL have been used to report and exchange business and financial information. Such standards focus on technical rather than semantic aspects. XML Functional Dependencies (XFDs) have been introduced to improve XML semantic expressiveness. However, existing approaches to XFD discovery that have been proposed mainly for enhancing schema design are not capable of dealing with data inconsistency. They cannot find a proper set of semantic constraints from the data, and thus are insufficient for capturing data inconsistency. In this paper we propose an approach, called XDiscover, to discover a set of minimal XML Conditional Functional Dependencies (XCFDs) from a given XML instance to improve data consistency. The XCFD notion is extended from XFDs by incorporating conditions into XFD specifications. XCFDs can be used to constrain data process and also to detect and correct non-compliant data. XDiscover incorporates pruning rules into discovering process to improve searching performance. We present several case studies to demonstrate the effectiveness of our approach.