Determining View dependencies using tableaux
ACM Transactions on Database Systems (TODS)
Principles of Database Systems
Principles of Database Systems
Logic and Data Bases
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PODS '83 Proceedings of the 2nd ACM SIGACT-SIGMOD symposium on Principles of database systems
Incomplete Information in Relational Databases
Journal of the ACM (JACM)
An extension to the relational model for indefinite databases
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Horn tables-an efficient tool for handling incomplete information in databases
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Abstraction in query processing
Journal of the ACM (JACM)
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PODS '84 Proceedings of the 3rd ACM SIGACT-SIGMOD symposium on Principles of database systems
Searching a minimal semantically-equivalent subset of a set of partial values
The VLDB Journal — The International Journal on Very Large Data Bases
A Generalized Relational Model for Indefinite and Maybe Information
IEEE Transactions on Knowledge and Data Engineering
An Exploration of Relationships Among Exclusive Disjunctive Data
IEEE Transactions on Knowledge and Data Engineering
Dependency Satisfaction in Databases with Incomplete Information
VLDB '84 Proceedings of the 10th International Conference on Very Large Data Bases
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VLDB '85 Proceedings of the 11th international conference on Very Large Data Bases - Volume 11
Data exchange: query answering for incomplete data sources
Proceedings of the 3rd international conference on Scalable information systems
Reverse data exchange: Coping with nulls
ACM Transactions on Database Systems (TODS)
Exploiting data dependencies with null values for ontology extraction
ER'12 Proceedings of the 31st international conference on Conceptual Modeling
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An incomplete information relational database combines two types of information about the real world modeled by the database: (a) the information represented by tables with null values ("value not known") allowed as entries, and (b) the data dependencies, which are known to be satisfied in the real world. We view the well known chase procedure as a process which transforms type (b) information into an "equivalent" type (a) form. Assuming that the data dependencies are arbitrary implicational dependencies, we show that this transformation is not quite equivalent, but the corruption of information introduced cannot be discovered if the query language uses the operations of projection, positive selection (i.e. no negation in selection condition), union, natural join and renaming of attributes. This result can be interpreted also as the new important property of chase.The influence of so-called view dependencies on the table with null values is also examined.